Zubaria Ayub

Academic

Verbatim text

Zubaria Ayub
+923215346560, zubariaayub634@gmail.com
Lane 5, Peshawar Road, Rawalpindi.
LinkedIn: https://www.linkedin.com/in/zubaria-ayub/
GitHub: https://github.com/zubariaayub634
Education
Bachelor of Science (Computer Science)
Major:
Data Science, Deep Learning, Machine Learning, Mobile App Development, Knowledge Graphs,
Information Security, and IoT.
The City School, Cantt Senior, Rawalpindi
A-Levels (Physics, Chemistry, Mathematics, Computer Science)
The City School, Cantt Senior, Rawalpindi
O-Levels (Physics, Chemistry, Biology)
Projects
Final Project: Uvea Mobile App for Visually Impaired [Flutter Framework, Dart, Tensorflow, Tflite]
A dashboard for Smart City that is data driven & continually sensed, and lets authorities monitor and manage the
accidents in real-time, fix road maintenance issues and monitor citizens subjected to rash driving.
Semester Projects:
ERIMS [Flutter Framework, Dart, Firebase] :
Created an event registration management system for FAST NU Islamabad
SZA Talk Chat Application [java, Javafx, MySQL] :
Built a desktop chat application.
Healthcare System [C++]: Implemented B and B+ trees to build a db for a healthcare system’s data
Work Experience
Mobile App Developer
Developing Mobile Application for SuperMamaPK, a small business run on Instagram
Employer's Profile: https://www.instagram.com/supermamapk/
Nov 2020 - May 2021
SEO Consultant at Premier Pain Centers (USA)
Formulating  and implementing off-page SEO strategy to improve ranking of their website
within search engines which ultimately results in high traffic and more sales.
Mar 2021 - May 2021
Research And Development Intern at IS Lab, FAST NUCES, Islamabad.
Developed an end-to-end solution for scheduling deliveries
Feb 2020 -  Aug 2020
Summer Intern at Nexsys Lab, FAST NUCES, Islamabad.
6 weeks internship working with REACT Native and Native App Development
Jul 2020 -  Aug 2020
Skills & Tools
Professional Skills: Teamwork, Documentation, Team Leadership, Interpersonal Skills, Communication
Technical Skills:
Flutter, Firebase, Python, Tensor Flow, No SQL, Sci-kit Learn, SQL, Java including JDBC,
Java/Swing, ETL, HTML, CSS, Socket programming, Android Studio, UML, Java Android, REACT JS,
JUnit Testing, Pytorch, VS Code, MySQL, Visual Studio, GUnit Testing, Knowledge Graphs, Ubuntu
Achievements
Dean’s Honor List, Rector’s Honor List
Trainings / Certification
Activities
President of NUCS 2020-2021, Head Workshops & Bootcamps of NUCS 2019-2020, Head CS Events for NaSCon 20,
Coordinator CS Events for NaSCon 19, Officer Speed Programming for NaSCon 18
Interests
Listening to podcasts, Color Pencil Art, Playing games, Reading all sorts of books
Class of BS (CS)
Final Year
Projects
Air Defence
In a Ground-Based Air Defense (GBAD) Environment consists multiple Defended Assets (DA’s) on
the ground that need protection against enemy aerial threats. Protection is provided by pre-
deployed weapons. A Fire Control Officer (FCO) is in charge of evaluating the threats and then
assigning the weapon to them. Now this decision making process needs to be really quick and
efficient and since threat evaluation comprises of a number of parameters e.g. velocity, altitude,
heading angle etc. there is a high risk of not assigning the best weapon under stressful condition.
We have developed an Intelligent Decision Support System which will assist the operator in making
a critical decision by evaluating the threat and assigning the most suitable weapon. After research
we have formulated an efficient TE system with additional parameters and an intelligent Machine
Learning Weapon Assignment model. These systems are being used in collaboration with
Geographical Information System (GIS) to simulate the environment and Knowledge Graphs to
derive rule-based reasoning.
Features include:
- Efficient threat evaluation and their categorization
- Calculating kill probability of weapons
- Generating accurate threat-weapon pairs
- Rule based reasoning using knowledge graphs
- Visualization of result in simulated scenarios
Technology Used:
Python, Django, LeafletJS, Scikit Learn,
PostGIS, Protégé, GraphDb
Supervisor Name:
Dr. Amna Basharat (Internal),
Mr. Ali Ezad Abbas (Nescom, External)
Group Members:
Rawan Amjad (i17- 0025)
Adnan Ahmad (i17- 0078)
M. Saqib Ijaz (i17 - 0099)
AR in Kindergarten
ARK is an augmented-reality and deep learning based android application developed with the aim
of promoting independent learning and enhancement of education in pre-school environments.
The target users of this application are children of young age who are aware of a smartphone’s
basic functionalities and can point their phone’s camera at the object of their interest.
The application detects objects – e.g. pictures from a book’s page or static images from a laptop’s
screen – and prepares their dynamic 3D models for deployment.
Once an object has been detected, the child can tap any surface in their camera’s view, such as the
floor, a nearby table, or perhaps a book’s flat page and the augmented reality model will be
generated and deployed at that location.
In addition to this, the child can shrink or enlarge the model, learn about the shape, structure,
distinguishing qualities, the name of the object or concept, phonetics as well as pronunciation of
the object or concept whose model has been deployed on the surface through augmented reality.
The application is written in native Java code and has been designed with simplicity and ease of use
as a top priority in mind. Teachers or parents can easily demonstrate the application’s usage and
benefits to the children so they can use it to learn in their own time.
Technology Used:
Android Studio, ARCore,
TensorFlow, Firebase
Supervisor Name:
Ms. Amna Irum
Group Members:
Muhammad Zaid Ali (i16 - 0042)
Sharjeel Hussain (i16 - 0225)
Sajid Ali (i16 - 0070)
AR Smarthomes
Activity recognition is the prediction of an individual's daily life activities, usually indoors, based on
ambient sensor data. Identifying a smart home occupant’s everyday activity, such as cooking a meal
or watching TV, would enable elderly people to live independently in a safe and comfortable
environment in their homes. A learning classifier's performance can be harmed by imbalanced
activity instances of various classes within the dataset, as well as activities with fewer instances. We
use deep learning techniques and generative adversarial networks in the proposed research to
enhance the recognition efficiency of everyday activities in a smart home. The evaluation of the
proposed approach on publicly available benchmark smart home datasets demonstrates its
superior performance than existing techniques.
Our goal is to apply existing Deep Learning techniques (DLT) to the problem of activity recognition
in smart homes, with the main concern being an imbalanced dataset with some activities having
more instances than others, as well as a small dataset with overlapping activities performed by
multiple residents independently. For research purposes two deep learning models, CNN and LSTM
were implemented on the smart home data, as well as Generative Adversarial Networks (GANs)
technique to generate similar instances from a small dataset.
Technology Used:
Python, GitHub, Kaggle, Spyder
Supervisor Name:
Dr. Labiba Gillani Fahad
Group Members:
Sara Ashraf (i17 - 0285)
Talha Nazir (i17 - 0324)
Amna Zafar (i17 - 0325)
ArchiTech
ArchiTech is an Android Application that at its core will let users convert their 2D architectural
floorplans to 3D models. Users scan their 2D floor plans from the app or upload them to the app.
The user waits while the application recognizes the floor plans and constructs the 3D model. Once
constructed the model will be made available to the user. The user can then navigate the model on
the app or if the user wants, they can view the model in AR. If the user is registered on the
platform, then they can also save their models so they can view it later on. Other than their own
models, they can search for and view models of other users as well. With each model certain
information will also be displayed. This information will be regarding the characteristics of the floor
plan such as number of bedrooms, percentage of covered area etc. Comparison of two plans on the
basis of this information will also be available. Furthermore, with the information that is obtained
from the floor plan brief cost estimations of the grey structure of the construction will also be
provided.
Features include:
 Floor Plan Detection - User will be able to upload a floor plan.
 Model Generation - A 3D model will be generated from the given floor plan
 Model Navigation - The model will be made navigable for the user within the app
 Augmented Reality View - User can also view 3D model using Augmented Reality
 Information Display – Information regarding the floor plan will be displayed.
 User Management - User can create and manage account on ArchiTech
 Platform related interactions – Users will be able to share, view and compare different floor
plans.
 Cost Estimation An estimated cost for the grey structure will be provided.
Technology Used:
Python, TensorFlow, Flask, Android,
Firebase, Java, Unity3D, C#
Supervisor Name:
Mr. Bilal Khalid Dar
Group Members:
Hyder Abbas Naqvi (i17 - 0009)
Shayaan Farooq (i17 - 0093)
Muhammad Bilal (i17 - 0317)
ARoute
ARoute, is an Augmented Reality based indoor navigation, which provides an organization to
increase their services, i.e. by providing an indoor navigation of their users. It will provide the user
to act as an organization, in order to scan an area, and implement indoor navigation on it or to use
indoor navigation of the requested area. The app will build the indoor map using ARKIT and will
show the shortest route from source to destination using Augmented Reality objects.
This app will require the company, who want to provide an indoor navigation for their area, to scan
the entire targeted area for the first time, which will enable the app to make a map of that area and
when the user wants to go from, for example the entrance to the cafe, app will provide the shortest
route by augmenting the path from the source to destination. The app will be widely usable in
multiple locations without requiring high tech equipment to operate it. If you have a modern device
with
internet
facilities,
then our
app
is
ready to
guide
you to
your
location.
Features include:
 Scan any environment, anytime and everywhere
 Find the Shortest Path
 Guidance of path through Augmentation and Voice Navigation
 Significance Surrounding
 Companion Finder
Technology Used:
C#, Unity, ARKIT, Google Cloud, Firebase
Supervisor Name:
Ma’am Noor Ul Ain
Group Members:
Anas Azam Bhatti (i17 - 0043)
Hassan Mahmood (i17 - 0272
Athena
Our Project, Athena, is an automated graph based Knowledge Extraction System that aims to solve
the challenges of linked data by providing users the ability to retrieve and extract meaningful
information without the need of having expert domain knowledge. Our system has successfully
achieved the conversion of raw text from various genres to a well structured Graph format. This has
enabled our users to structure, store, retrieve and analyse data quickly, in runtime. Additionally,
the live Graph Database will be queryable; The main medium for handling these queries will be
Cypher, the robust language backed by Neo4j. Once a cypher query is formulated, information is
passed along from the knowledge graph to the user  via a query interface in an efficient manner.
Features of Athena include:
➢ Knowledge graph construction at runtime
➢ Automatic conversion of unstructured text to a structured form
➢ Robust Querying options
➢ User friendly interface
Conversion of raw unstructured text to a Knowledge Graph
Technology Used:
Neo4j, Python 3.8, Flask, Jupyter Notebook,Google Colab,
PyCharm, HTML,CSS, Javascript
Supervisor Name:
Dr. Omer Beg
Group Members:
Hamza Mahmood (i17 - 0054)
Azfar Bakht (i17 - 0158)
Dania Zahid (i17 - 0175)
Automatic Speech Recognition System to Generate CV
SpeakCV, is an automatic CV generating system for native Urdu speakers that uses speaker’s voice
information as input and generates a professional CV using Neural nets and Natural Language
Processing Techniques.
The user will answer a few questions in Urdu and user’s speech data will be recorded in phone. The
data is then pre-processed and sent to a speaker independent ASR for speech recognition. Once
speech is recognized, it is then corrected using Language Model. The corrected transcript is then
translated to English. Once translation is done, our system will extract CV specific data and
display it on a professional CV template
Main Features include:
• Automatic Urdu speech recognition (ASR) from live audio input
• Transcript correction using Language Model
• Urdu text to English text translation
• Identification of CV specific keywords from translated text
• CV generation from identified Key Words
Technology Used:
TensorFlow, React, Node.JS, Flask
Supervisor Name:
Mr. Umair Arshad
Group Members:
Hamza Ali (i15- 0083)
Talha Mujahid (i16- 0179)
Alina Baig (i17- 0327)
BeMyHand
ByMyHand is a voice and eye-gaze controllable web app built for differently abled people who
cannot use their hands. The idea is to make the web accessible for them by providing them a
complete toolkit which they can use to start working and incorporate self-dependency in them.
First, our app provides a rich text editor where our users can write documents and can apply
different styles to their text. They can also generate and download Docx and PDFs.
Second, our users can maintain an articles directory where they can store their articles and publish
them to share with the rest of the world to showcase their writing skills. They can search articles by
author, topic, title, or article body containing the searched keyword or phrase. They can also search
background images for an article using their voice and embed them in the article.
Third, they can build a professional CV and are provided with three professional templates to
choose from. They can also show their CV in their profile and portfolio. The CV is also downloadable
as a PDF.
Fourth, they can make a portfolio webpage where they can add their work, contact information,
CV, and other necessary information.
AND THIS ALL WITH THEIR VOICE AND EYE GAZE.
Technology Used:
Node JS, React JS, Flask, MongoDB, Python, GitHub
Supervisor Name:
Dr. Hasan Mujtaba
Group Members:
Adil Alam (i17 - 0127)
Muzamil Hussain (i17 - 0191)
Haysam Bin Tahir (i17 - 0228)
Biomedical Text Annotation Using Knowledge Graphs
This project will create a web-based semantic biomedical text annotator using NLP (Natural
Language Processing) and knowledge graphs/semantic web ontologies. This annotator focuses on
two domains of the biomedical literature: diseases and genes. To implement our biomedical
semantic text annotator, we needed to perform the following three major steps: (1) Named Entity
Recognition (NER) to extract the entities of types genes and diseases, (2) Entity Linking (EL) to link
the extracted entities to relevant entities from the selected ontologies (3) Relation Extraction (RE)
to extract relations between genes and disease entities. For NER and RE, we used BioBERT which
gave good accuracies greater than 90%. For relation extraction, we used Personalised Pagerank
(PPR) algorithm supplemented with Gene-Disease relations extracted from text. The user interface
is developed using python-based django web framework. The interface consists of only a single
view.  Using the interface, the user inputs a text. The application will then display the text with the
extracted entities highlighted by their entity types. It will also display a document graph showing
entities as nodes and links between the entities. The application also displays a brief description of
the highlighted entity, when clicked.
Technology Used:
Python, PyTorch, NetworkX, Owlready2,
Transformer, Django Web Framework
Supervisor Name:
Dr. Amna Basharat
Group Members:
Ahmad Wali Bin Saeed (i17 - 0106)
Ahmad Ali Bin Saeed (i17 - 0105)
Farrukh Ahmed (i17 - 0100)
BlindAssistant
Over the years as technology has progressed further and more and more smart solutions have
emerged, assistive technologies all around the world also saw the light of innovation.
BlindAssistant is a solution aiming to cater the challenge of the ever growing technological
advancements in assistive technologies using state-of-the-art techniques such as those in DL
(FCHarDnet) and Computer Vision. Sometimes, the guide canes don’t offer their required safety
levels because they don’t provide perception of the obstacles or objects types and also do not give
information about the walking path. With that in mind, it shall leverage relevant information such
as semantic segmentation map as well as depth map to output real-time feedback to the end user
for various outdoor navigation scenarios. This required looking into various advanced models and
techniques to prototype our main idea accordingly. We incorporated RGBD sensor Kinect XBOX v1
for
obtaining
depth
feed
in
real-time.
Features include:
- Real-time terrain awareness
- Obstacle avoidance system
- Speech Engine for voice feedback
- Flask server for application
Technology Used:
Python, Pytorch framework, Kaggle, Colab,
Flask framework, LibFreenect (XBOX), Photoshop CC
Supervisor Name:
Dr. Asif Naeem
Group Members:
Ali Salman (17i - 0350)
M. Bilal Shabbir (17i - 0124)
M. Sohaib Akhtar (17i - 0330)
Blockchain Based Digital Wallet
A general decentralized application payment system based on Ethereum blockchain technology to
support secure payments, and data security. It can be integrated with any real world application or
startups for its payment purposes. Apart from giving payment services we have built our own wallet
application to provide wallet services through which users can pay each other using Blockchain
Wallet. The Backend is completely developed in solidity language and deployed on Ethereum
Ropsten Testnet Work. For Admin Panel interaction we aim to provide its interface through a web
application using technologies (NodeJS/ExpressJS,ReactJS). In order to integrate it with RealWorld
use
case
we
have
developed
a
CAB-E
application
on
Flutter.
Features include:
- Payment Related Services to any company by managing the wallet of their individual users
- Providing our own generic Mobile Wallet application through which users can transfer payments.
Furthermore It provides management services
Manage Companies and their users
Manage user’s trusted lists
Complete management of system related data on ethereum blockchain written in solidity.
Technology Used:
Flutter, Ethereum(Solidity), ExpressJS/NodeJS,ReactJS
Supervisor Name:
Dr.Amna Basharat
Group Members:
Syed Adil Hassan (i17 - 0096)
Waqar Shakeel (i17 - 0249)
Aadil Moeen (i17 - 0243)
BrandHub
BrandHub is web application that connects the world of shopping with all the brands at one place.
One can search their favorite clothing items, make comparisons and choose the best products on
one platform! This project combines various technical challenges such as Web scraping, Image
Detection, Machine Learning, Color Analysis, Data Categorization & Analysis.
Features:
● Search by text: Type in what you want and get products that match the description.
● Search by image: Upload an image of the item you want and get visually similar products.
● Make a Match: Upload an image of an item that you want a match with and get the best
matched products based on aesthetic color matching.
Wishlist: Add items to the wishlist that are out of stock or out of your budget and get notified as
soon as they go on sale or get restocked.
Technology Used:
Python, MongoDB, React,
Flask, BeautifulSoup
Supervisor Name:
Mr. Hassan Mustafa
Group Members:
Hamza Bin Khalid (i170 - 0022)
Mariam Khalid (i17 - 0165)
Zahra Akhtar Aziz (i17 - 0316)
Business Insight and Visualization Assistant
Business Insight & Visualization Assistant (BIVA) is a Business Intelligence oriented web-based
application that'll facilitate the business owners to interact with their sales data and provide them
with their business insights. These insights, in technical and statistical terms are the analysis
reports, data trends, network graphs, statistical plots and business decision predictions. It is a
complete Data Warehouse based analysis solution dedicated to a the user’s Business and built
specifically for it, hence allowing low tech and lay audience to interact directly with their data
through an intuitive user interface.
Technology Used:
Mysql, Python, Pandas, Bokeh, Django,
Visual Studio Code
Supervisor Name:
Dr. Asif Naeem
Group Members:
Hassan Ali (i17 - 0143)
Ahsan Shakeel (i17 - 0150)
Salib Raza (i17 - 0171)
CHAINIFY
Chainify platform has been developed with an aim to decentralize the systems of various industries
and provide them with a secure platform where they can easily build and deploy their custom
blockchains using modular consensus algorithms. The project is split into two parts consisting of a
centralized Chainify server and Decentralized blockchain nodes.
Our central server stores user information in a central database, For the central server we have a
REST API backend through which users can Sign Up, Login , Create Chains and can fetch the core
info of their blockchains through a GET API endpoint.
Our decentralized server can cater two interfaces, either through CLI or through a web based
frontend. This decentralized server can connect or disconnect with other nodes, request their
updated blockchains, and flood mining information to all nodes. Features include:
- 2-way connection of nodes in a P2P network. (Flooding, Blockchain Synchronization, Bi-directional
Communication, Secure Message Verification, )
-  Automatic port forwarding using UPNP protocol to allow incoming connections from external
networks.
- Users can make a new chain, deploy that chain and make new transactions
- Users can choose a consensus algorithm for their chain from 3 provided algorithms i.e., proof of
work, proof of stake, open consensus.
- Users can tune the consensus algorithms according to their own requirements in terms of mining
rate, complexity etc.
- Users can make their chains public or private.
Technology Used:
Go Language, Svelte JS, React Native,
Dockers, PostgreSQL
Supervisor Name:
Dr. Ehtesham Zahoor
Group Members:
Daniyal Hassan (i17 - 0411)
Mughees Awan (i17 - 0311)
Saad Zahoor (i17 - 0046)
CharityGO
CharityGo is made for easing the difficulties faced in the donation process across the globe. It is
made for Donors/ individuals as well as Non-profit Organizations and has two views respectively.
NGOs can initiate projects and campaigns adjusting different variables. Individuals on the other
hand can only create Campaigns. Both users can search projects and campaigns and can use chat to
start interacting with the Project/Campaign creating user. Likes and comments on different projects
will generate ratings of the Organizations.
Donor/ Individual Features:
-Profile Creation and Editing Preferences
-Filter Search for getting accurate results
-View Ratings of NGOs for selecting the best Project
-Chat box for interaction between the Donor and NGO
-Campaign Creation and getting maximum visibility
NGO/ Organization Features:
-Profile Creation and management
-Project Creation for getting maximum reach
-Quick Campaign Creation for getting maximum visibility
-Getting Reviews based on Project Performance
Technology Used:
HTML, JS, Bootstrap, Node JS,
MongoDB Express, Angular,  Figma, Adobe XD,
Supervisor Name:
Mr. Jawad Hassan
Group Members:
Ahsan Mehdi (i14 - 0233)
Nauman Afzal (i14 - 0203)
Tahir Bilal (i16 - 0121)
Cloud Safe
In the digital era today, there is a need to secure important information that can be in the form
confidential reports, business plans and other documents that require to be safe from malicious
access. Information security has therefore been a common use in computing and will continue to
be in the future. The massive increase in the use of large-scale distributed systems such as the
Cloud have led to security challenges. The most important concerns all cloud users face is related to
security and this causes a hindrance in the adoption of Cloud. The aim of our application is to make
the cloud more secure by helping users identify, analyze and visualize their policies. The users will
get to know where there are problems in their policy and will be given advice and warnings based
on their policies. The project will be a web-based application which can import existing AWS IAM
policies. The application will fetch all AWS IAM policies. Users shall be able to have their policies
visualized and analyzed by our algorithms. Users will be able to identify where the anomalies in
their policies lie. Application would give hints on what could cause problems and even warn if policy
is problematic.
Features include:
•
Users will access it on Web Based Application.
•
Allow the users to import/upload AWS IAM policies.
•
Allow the users to analyze their policies by showing users the possible anomalies in their
policies.
•
Allow users to know their anomalous policies by getting their policies highlighted wherever the
policies are problematic.
•
Allow users to visualize their policies in the form of tables or interactive graphs.
•
Directly place warning indicators on potentially problematic portions of a policy.
Give hints to users on what could cause problems and even warn if the policy is problematic.
Technology Used:
Python, SvelteJS, Docker,
Kubernetees, Monoco Editor, Rust
Supervisor Name:
Dr. Ehtesham Zahoor
Group Members:
Rajaa Aamir (i17-0339)
Taha Firoz (i17-0323)
Talal Qayyum (i17-0118)
CloudXplor
A monitoring system for on premise distributed environments. This system allows its users to
monitor multiple end users systems in a distributed environment, and then view their metrics in a
single dashboard. Our problem statement is that:
1) Difficulty of monitoring multiple systems/servers in an industrial environment.
2) Combining monitoring data from multiple systems in a single dashboard.
3) Getting insight into efficiency of deployed code.
4) Getting insight into efficiency and health metrics of Database Servers.
Our solution involves a single web application which combines different system metrics from
multiple sources. Retrieving and displaying metrics in real time. Code profiler for getting code
related metrics and efficiency insights.
We have limited our scope to monitoring only linux based systems, with Databases running on the
MySql environment, and profiling Java codes. The system operates flawlessly with multiple end
user systems connected, and displays the data collected in the form of informative graphs and
tables. This helps the user to easily identify the performance issues of their deployed machines and
code
.
Technology Used:
Java springboot, Mysql, ReactJS, Linux kernel,
MySql Sys_schema, Linux sysstat
Supervisor Name:
Mr. Ahmed Nawaz, Dr Muhammad Asim
Group Members:
Furrukh Khan (i17 - 0085)
Omar Ahmed (i17 - 0040)
Syed Mustafa Ali (i17 - 0253)
DigiLab
DigiLab is an Augmented Reality based application that enables students of Secondary Level to do
their lab experiments of Physics using just their Android phones. When a user opens the app, a list
of available practicals will be shown to the student. Then, the apparatus for the chosen practical
will be displayed to the student along with a 3D simulation of the step-by-step practical. Students
can also change the size, weight, etc. of the tools involved in the practical like the mass of the bob,
etc. The measurements will be updated according to data updated by the student.
The step-by-step calculation will be shown at the end of the experiment. A Student can also change
the objects involved in the experiment from the predefined library of objects or by scanning objects
in real-time.
Features include:
 View and perform the Physics practicals
 Detection of any real-life object
 Use the detected object in practical
 Save and View experiment history
 Take Notes.
Quiz Module to see the learning curve of students.
Technology Used:
Blender, Unity 3D, AR Core, C#, TensorFlow
Supervisor Name:
Miss Noor ul Ain
Group Members:
Abdul Hanan (i17 - 0131)
Ahmed Bajwa (i17 - 0237)
Syeda Sana Fatima (i17 - 0341)
E-Utility Service Application
EUSA is a platform, in which we aim to provide fast and responsive solutions for customers where
they can search for a number of services; Electrician, Plumber, AC Repair, Mechanics, Carpenters.
Location of these service providers will be available through map, customers will be able to contact,
book and visit(location) the aforementioned service providers at the tap of a button. Users will be
able to login as either a customer or a service provider and consequently have their own menu to
use the application. The application will provide convenience to both service providers and
customers. The service provider’s exposure will increase and now not only walk in customers will be
catered but also online customers will help him earn more. On the customer’s end, he now doesn’t
need to find the required service providers to help him solve his problems. Lots of time will be
saved. He just needs to open the app, see the map and hire the nearest service provider.
Features include:
-
User Search
-
Book, contact, locate service providers
-
Promote and rate service providers
-
User management
Technology Used:
Android Studio, Java,
Firebase, Python, Adobe XD, GPS technology
Supervisor Name:
Mr.Bilal Khalid Dar
Group Members:
Akash Ali (i17 - 0019)
Shehroz Mughal (i17 - 0187)
Salman Qureshi (i17 - 0282)
ExRaDe(Expose Racism Detection)
Racism detector is a web application that helps the social media users to check their tweets before
posting it on the twitter either it contains racism or not. More importantly, it is for Roman Urdu. A
deep learning model LSTM is used for tweet classification either its racial or non-racial. The purpose
of this application is to facilitate the users to avoid the posts that spread racism of any kind and in
this way we can move towards a better future. We collected the dataset from Kaggle and then
annotated it according to our problem. It was labelled by three of our team members so, it can
have labels that are opinion based and have a subjective type which means someone can say its
racial while it non-racial on the basis of other person’s opinion. We are working on an extension
which will automatically count the tweets on the twitter that contains racism posted by the user on
the twitter platform.
Features include:
- A front end which takes an input tweet from the user.
- Preprocess the tweet taken as input. A model at backend will check the tweet and then will
determine its class and will tell class of tweet to the user. Since it’s a binary classification therefore,
there will be only two classes 0 and 1 where 0 stands for non-racial and 1 stands for racial class.
The application will classify only the tweets in Roman Urdu as the model is trained on that specific
dataset. Contextual based classification will also be performed in which the model will keep the
track of history of the text taken as input.
Technology Used:
Python3, Flask, Keras, TensorFlow,
Pandas, HTML, CSS, Jupyter-notebook
Supervisor Name:
Mr. Jawad Hassan
Group Members:
Asad Dar (i16-0261)
Sabeeh Ali Akbar (i16-0017)
Imran Haider (i16-0247)
Fashion Hunt
Fashion Hunt is a web application based on deep learning and image processing that allows the
users to search desired clothing items available online.
User can upload image that has his/her desired clothing. After uploading, the System will perform
image segmentation and convert it into multiple clothing segments. The user can view the
segmented images separately and can select the required clothing segment. The System retrieves
similar images based on closeness and then recommends links where the selected clothing item can
be purchased. Each link will have complete information about its respective clothing e.g. price,
availability, size etc. The user can make buying decisions after comparing different links based on
color, price etc.
Features include:
● Giving the user an intuitive interface where users can upload an image
● System will display segmented images of the original image
● User can select any segment and system will output visually similar images and links
Users can view a list of ecommerce websites where they can buy desired clothing online
Technology Used:
PyTorch, Selenium, MYSQL,
Angular ,Django Web framework, GitHub
Supervisor Name:
Dr. Omer Ishaq
Group Members:
M. Hassam Asif (i17 - 0007)
Aimen Inam (i17 - 0156)
M. Yaseen Mughal (i17 - 0276)
Fashion Recommendation System
A Fashion Recommendation System which helps users to find their favorite dresses instantly on the
basis of latest trends and individual’s personal sense of dressing. Moreover, system helps user to
find clothes by searching through an image of the dress. This is where technology comes into the
field to provide a solution to this problem. Shop Spot is an application that would help people to
search items by image anytime, anywhere. It allows the users to input images into our
multiplatform dynamic Web and Mobile Application and our system; comprising AI components
compares the features of the image with maximum possible items from the local market and
provides the links to online stores on which the item is available with lowest prices.
Features include:
 Real time data scraping and streaming.
 Search products by image from Database.
 Product Recommendation using Wardrobe Collection.
 Add items to Wishlist
 Sell Preloved goods.
 Give links to stores where the searched item is available on sale.
Implementation of Deep Learning Algorithms to search by image feature
Technology Used:
MERN Stack, Apache Kafka, Python, Machine Learning,
Beautiful-Soup, Visual Studio Code
Supervisor Name:
Ms. Amna Irum
Group Members:
Hammad Afzal(i17-0190)
Jawad Ali (i17-0268)
Ghulam Jillani (i17-0148)
FIT- Framework for IoT application
FIT is a framework that allows users to create IoT applications that involve stream processing, event
processing, and complex event processing. FIT is a diverse and generic framework aimed to be
usable by the diverse users of CEP. A GUI is built upon the framework for generic as well as specific
applications. Our GUI enables users to add some components to create the application's pipeline.
These components include:
•Virtual Sensors (it will provide data in the form of streams).
•Operators (which contain functionalities such as object detection Algorithm, fall detection
Algorithm, Analyse patient's recent records and give insights on it, etc.)
•Alerts (Messages/Triggers).
As a proof of concept we have added different virtual sensors, operators and alerts that can be
found in old homes. This will enable caretakers to create complex scenarios by using a simple
configurable graphical user interface. It will help them to automate old homes according to the
needs of each individual resident. Our framework will also help users to deploy and run these
scenarios on different remote machines.
List of available Virtual Sensors: Pulse Sensor, Accelerometer, Gyroscope, Surveillance Camera
List of available Operators: Filter, Fall Detection, Activity Recognition, Logical Operator
Technology Used:
Python, AngularJS, Django and KAFKA
Supervisor Name:
Dr. Adnan Tariq
Group Members:
Zahid Iqabal (i17 - 0035)
Noman Nasir (i17 - 0062)
Sibghat Ullah (i17 - 0291)
FruitVegFreshness
FruitVegFreshness is an android application that allows the users to take images of fruits and
vegetables either by capturing the photo directly by using the mobile camera or by loading it from
the mobile gallery. These images are then forwarded to the remote server on which the object
detection model is already deployed, where the model analyzes, locates the objects in the images
by drawing bounding boxes around them and predicts the freshness level (fresh, medium or rotten)
along with guessing the fruit/vegetable type like apple, banana etc. Finally, after the prediction has
been made, the server returns the image with predictions that contains bounding boxes around
objects along with labels, to the client user. This resultant image with predictions is finally
presented on the screen of user’s device.
Features include:

Interactive UI for taking picture using Camera and loading of image from Gallery.

Accurate and precise YOLOv5 Object Detection model deployed on server.

Localization of fruits and vegetables in the image by drawing bounding boxes around them.

Classification of freshness and type of fruits and vegetables present in the image like fresh
apple, rotten apple etc.
Zooming in and out from the resultant images with predicted bounding boxes and labels.
Technology Used:
Python, Java, Android Studio,
Google Colab & PyTorch
Supervisor Name:
Dr. Labiba Fahad
Group Members:
Usama Zafar (i17 - 0012)
Usama Rasheed (i17 - 0212)
Hafsa Saqib (i17 - 0321)
GoNotes
GoNotes is an R&D based project which generates precise notes from video lectures. It extracts the
audio from video lectures, transcribes the text from audio, and then extracts accentuated regions
using emphasis detection to generate precise notes. In emphasis detection, audio features such as
frequency and amplitude are analyzed and the keywords from the text are extracted to choose
important parts of the lecture.
Features:
● Transcription of the audio of a video lecture
● Generation of notes
● Extraction of keywords
● Finding key sentences
Highlighting important parts of the lecture transcription
Technology Used:
Python, Flask, HTML, CSS, Google Colab,
Pydub, Wav2Vec2
Supervisor Name:
Dr. Omer Beg
Group Members:
Sarah Ejaz (i17 - 0082)
Areej Fatima (i17 - 0084)
Sher Bano (i17 - 0104)
GoVitae – A Blockchain based CV verification System
Our application is created to facilitate verification of CV for companies, especially in an open house
environment. Our project’s phenomena is that after completion of each course the course work
done by each student will be inserted in the node of a blockchain which will happen each semester
till the completion of degree. The approved stakeholders will be able to search all the work done by
students during their degree tenure. Our project is using the private, permissioned and a custom
built Blockchain framework to achieve the mentioned goal. Blockchain technology will provide us a
decentralized and secure P-2-P system. The reason for using this technology is to provide
authenticity, transparency to the work done by the student at the end of his degree. Major plus
point is the time saving and transparent record keeping for both the university and the employers.
Features include:
 Employers at open house could search for specific projects and specific skills they want from
our app/website without any hassle of verifying or testing the candidate themselves
 Coursera/Udemy projects can also be added to the University's Blockchain after proper
evaluation by respective instructors.
 University own repository ( like Github ) can be integrated with the Blockchain system to keep a
thorough history of what and when the student made the project so that the same project can
be used in Future.
Verifiable CV’s can be given to GlassDoor so that international employers can also easily verify local
employees.
Technology Used:
Angular, Heroku, Go Language, Git, Atom
Supervisor Name:
Dr. Ehtasham Zahoor
Group Members:
Mohtasim Asad (i17 - 0057)
Abdul Mueed (i17 - 0132)
Muhammad Hamza (i17 - 0181)
HemaRays
In hospitals everywhere , patients with disorders require frequent blood draws.In case of leukemia
or anemia , doctors are interested in measuring hemoglobin levels in a patient's body. To obtain
such measurement , medical personnel use invasive approaches such as intravenous lines , or
specialised machines that draws out blood and measures hemoglobin levels.HemaRays aims to
bring a non-invasive approach that removes factors of blood tests and provide patients with a
reliable, cost effective. anywhere available mobile application.This mobile application uses the
phone's built-in flashlight and camera unit to detect colour absorption, it uses the absorption of
different colours and light to detect the PPG signal.The user simply places a finger on the flashlight
and camera lens, making a solid contact, and user presses the record button and app uses the
flashlight and camera of the phone to record a video to detect specific features that point to the
amount of hemoglobin levels in user’s body.
Technology Used:
Android Studio,React Native,
JavaScript, Python, Tensorflow, Keras
Supervisor Name:
Dr. Kifayat Alizai
Group Members:
Asfandyar Barki (i17-0202)
Zarak Mahsud (i17 - 0515)
Muhammad Nauman (i17 - 0079)
Image Inpainting Using Deep Learning Models
A multi-platform-based app is being which is used to denoise, colourise B&W images along with
super resolution and restoration of images. The app is using deep learning models at back-end to
perform the following actions. There are two interfaces, web interface where user can select what
he wants to do with the image and then upload the image and let it process. After process is
complete, the user will be displayed with the processed image which he can save by right clicking
on it and hit save image. The second interface is a mobile app where user can select the action he
wants to perform and then given option to give image from camera or select from gallery, after
which the image is uploaded on server and processed and user can view the processed image on
the final screen. The backend is deployed on cloud to ensure stability and since it requires high
computational
power,
cloud
is
the
best
option.
Features include:
 Multi-platform app
 Denoise Images
 Colourise black and white images
 Super resolution of pixelated images
 Restore damaged images.
Take live pictures from mobile camera and process
Technology Used:
Python, Flask, Flutter, GitHub, TensorFlow, Keras
Supervisor Name:
Dr. Irum Inayat
Group Members:
Faheem Ashraf (17I-0061)
Muhammad Mehlab (17I-0188)
Talha Muneer (17I-0229)
Insider Threat Management System
An insider threat management app is being made, whilst keeping the perspective of sensitive
organizations like NESCOM in mind. This is a web application to detect data exfiltration events. This
is to make sure an organization does not lose assets and important information due to a trusted
employee within the organization turning malicious. It can only be accessed by a highly authorized
person i.e. admin with login credentials for the app. The admin can check the users involved in
malicious activities by monitoring activities done on sensitive data and also, check for its
movement. Moreover, the admin can track the external devices that have been connected along
with monitoring activities like movement to and from the device. The user involved in such
malicious activities can be detected by the identity management module.
Features include:
- Identity management: Information about each system captured and stored along with logon and
logoff times.
- Real-time monitoring of sensitive data. Capturing events such as renaming, creation, deletion and
modifying of data.
- Tracking sensitive data movement locally within the system. Capturing old and new paths.
- Tracking and monitoring user application usage.
- Real-time monitoring of new device connections internal and external to the system along with
data movement monitoring.
- Deployment of application as a service to run silently in the background.
External connection
-External info extraction
-External movement
-Integration of modules
-Database setup
-Remote server setup
-Web app development and testing
Technology Used:
C#  .NET Framework 4.7.2 Python 3.9.4 HTML, CSS,
JavaScript Django Web Framework 2.2.10
Visual Studio, Atom Editor
Supervisor Name:
Internal: Dr. Muhammad Asim
External: Ms. Sameera Amjad (NESCOM)
Group Members:
Myra Rafique Khan (i17 - 0129)
Mujeeb Alam (i17 - 0164)
Amina Siddique (i17 - 0289)
LookOut – Safety Application
LookOut application was created after taking into consideration all the safety prospects of our
users. The application is twofold containing a separate user and an admin view. The user view
consists of a dashboard and a side drawer for navigating to different activities of the application.
The dashboard contains quick dials that connect the user to the respective authorities, whilst also
containing an alert button in the middle to send an SOS Message with user’s location to the
emergency contacts as well as the volunteers, and a RedZone request is also sent with the user’s
current location to the admin for approval. From the side drawer the user view and manage their
account, register/unregister as volunteer, view nearby emergency facilities, add/remove
emergency contacts, search map, view RedZones and provide feedbacks. Furthermore, the admin
can view all the notifications, approve/decline volunteer/RedZone requests and can view all the
users, admins, and the volunteers. Rest of the admin functionalities are on the server side.
Features:
Realtime background and foreground notifications.
Information sharing across devices.
Realtime RedZone updates.
Audio/Video Recording.
Technology Used:
Android Studio, FCM, Firebase, SQLite, Java, Google APIs
Supervisor Name:
Mr. Saad Salman
Group Members:
Irfan Karim (i17 - 0006)
Hamza Ayad (i17 - 0041)
Ahsan Naseem (i17 - 0186)
MedsParency
The idea behind MedsParency is to keep the supply chain of medicines transparent using a
blockchain to prevent counterfeiting. MedsParency has three data entry points; first one for the
Store Man or the Warehouse guy who is responsible for receiving raw materials from a credible
source and entering the detailsof those raw materials into the blockchain through an interface. The
second data entry point is for Manufacturing Unit Officer, who enters the manufacturing details of
the drug once it has been manufactures. The third data entry point is for Quality Asurance Officer
who adds the packaging and pricing details into the blockchain after the drug has been packaged. In
this way, the users can ensure the originality of the drug they are about to use. Additionally, the
pharmaceutical officers can also ensure transparency throughout the process.
Features include:
-
Transparency of supply chain of medicines
-
Medicines verification request handling
-
Price Control
Traceability of accountable person in case of any malpractice
Technology Used:
Hyperledger Fabric 2.2, Node JS, Javascript, React
Supervisor Name:
Dr. Shujaat Hussain
Group Members:
Hamza Bin Zafar (i17-0307)
Shahzaib Ayyub (i17-0251)
Noor Ul Huda (i17-0153)
MeetingScheduler
MeetingScheduler is a Chatbot based virtual assistant, embedded within a web application, that
takes away the hassle of scheduling meetings from its users and manages the schedule on its own.
The chatbot manages and updates its users’ calendars and informs users about upcoming meetings,
as well as provides suggestions on which contacts to add in the meeting. The chatbot interface
provides an ease of communication to the user so that the user just needs to tell the chatbot for
meetings and the rest of the work will be taken care of.
The main features of our application include:
- Filtering and identifying meeting emails for the users
- Automating the process of scheduling meetings with recipients
- Updating user calendar
- Notifying  user and displaying upcoming meetings
- Allow cancellation and rescheduling of meetings
- Provide suggestion for participants to involve in meetings
Technology Used:
Python, TensorFlow, PyTorch, Flask, HTML, CSS, RASA
Supervisor Name:
Ms. Amna Irum
Group Members:
Muhammad Ammar Masood (i17 - 0002)
Rabeah Zubair (i17 - 0005)
Adeena Bilal (i17 - 0299)
Obstructy
Obstructy is an android native mobile application which provides standard video editing features
packaged with the salient speciality of “obstruction removal”. It is aimed at young adult users, users
who spend significant time on social media, or users who are photography enthusiasts; but it can
effectively be useful for anyone who uses a smart phone. The app is based on a recent
breakthrough
Deep
Learning
paper
titled
“Learning
to
see
through
obstructions”
[https://www.youtube.com/watch?v=ICr6xi9wA94&t=18s]. Our app’s core function is obstruction
removal from short videos; it takes in a short video clips and returns de-obstructed frames. This is
done by employing 4 interconnected tensorflow deep learning models which remove unwanted
obstructions (fences, raindrops, reflections only) using depth and angular information from short
videos by identifying background and foreground layer, estimating their pixels’ flow over time, and
reconstructing both layers/flows separately. A major goal thus is to deploy the model as a docker
instance onto SageMaker, Amazon Web Services, or even deploy it on a simple AWS instance as
proof of concept. Our app’s interface was inspired after humble UX analyses such as from
competitor apps and also from informal user analyses. Our final UI leverages the Google Materials
library.In addition to the deep learning model, our app also manipulates bit streams in mp4 videos
for video editing, and provides the following features:
-
Obstruction removal (short videos to images/frames)
-
Video trimming
-
Video filters
-
Video audio manipulation; removing audio, adding music Video speed control
Technology Used:
Java, Python, Tensorflow, C/++ (FFMPEG),
Android, Android Studio, Amazon Web Services
Supervisor Name:
Mr. Shoaib Mehboob
Group Members:
M. Huzaifa (i17 - 0305)
Yumna Javaid (i17- 0215)
Raja Salman Tariq (i17 - 0322)
OJO – Smart Surveillance System
OJO is a web-based surveillance detection system. OJO which means an “Eye” in Spanish is a a
project that aims to enhance the detection and prevention of crimes in organizations, like a
Company or bank, by exploiting the full potential of video surveillance systems.
Features include:
 Web-Based Admin Dashboards:
We will provide friendly Admin Dashboards for the following people to monitor the
Activity.
1. Security Staff (Control Room Staff)
2. Manager (Administrator of the Website i.e. Security Manager)
 Weapon Detection:
 Aggressive Behaviors Detection:
 Alert of Activity:
If our system will detect any behaviors like this then our system will generate a prompt
On the screen by making the screen red. Our system will have 3 options/level:
Level 0:
If the detection is caused by the security Staff. The Administrator will
Simply ignore it.
Level 1:
The Administrator will have an option to alert the near police station by an
Emergency number.
Level 2:
If the Security Staff will not respond then it will send a notification via
SMS to the Manager. This feature will be available only for the Staff’s dashboard,
Not the Manager’s.
 Detected Activity Log/Report:
 User Logs:
Add/Remove/Update Resource Management:
Technology Used:
Flask Framework, jQuery, Open CV,
Pytorch, Models (Yolo V3, Conv LSTM)
Supervisor Name:
Mr. Hassan Mustafa
Group Members:
Muhammad Shehroz Wali Khan (i17 - 0308)
Tauseef Nawaz (i17 - 0149)
Muhammad Shurahbeel (i15 - 240)
Pilot Buddy
PilotBuddy is a fault-injection and detection framework for real-time anomaly detection in the
course of a UAV flight. The framework is a web-app linked externally with FlightGear Simulator,
through socket programming, for better visualization. The framework allows users to connect to
the simulator and inject aileron, rudder, elevator or engine faults into the flight simulation and
study its effects on the UAV’s flight. Furthermore, PilotBuddy comes integrated with a model
trained on the changes in the different parameters of a UAV, before and after fault injection. This
helps our framework recognize faulty behavior and generate an alert when any anomaly is detected
in
a
real-time
flight,
so
recovery
actions
may
be
taken.
Features include:
- Real-time connection with FlightGear simulator to directly visualise the effects
- A Fault Injection Framework to enable users to inject faults in-real-time and study their effects
- Visualization of parameter changes during the course of a flight in graphical form, for better
understanding
- Detection of actuator and engine failures
- Display fault diagnosis information against injected failures
Technology Used:
Python, Flask framework,
Socket Programming, Google Colab, Github
Supervisor Name:
Dr. Irum Inayat
Mr. Shoaib Ashraf (external)
Group Members:
Ayesha Ateeq (i17 - 0010)
Namrah Rasool (i17 - 0018)
Rafsha Mazhar (i17 - 0028)
PowerUI
We envision to create a product that can perform black box testing of UI display issues of mobile
apps with the flexibility to detect 5 most common issues in the mobile UIs and supports different
mobile platforms. There issues are kept in mind that affects the user experience adversely. Most
such testing apps are focused on testing system level issues such as crashes or out of bounds issues.
Our project will make UX better by helping developers find the bug so that users don’t leave the
app because of these small issues that are usually overlooked. Therefore, it will be beneficial for
businesses.
Following are the features that are present in our project:
 Exploring App
 Issue Detection
 Issue Localisation
Web based Front-End
Technology Used:
Pytorch, Python, Flask, HTML, CSS, OpenCV
Supervisor Name:
Dr. Atif Jilani
Group Members:
Usama Mehmood (i17 - 0011)
Sheikh Ibrar (i17 - 0192)
PsychicAI
Our chatbot android application is being made to meet the growing need of mental health support.
BroBot uses AI and Natural Language Processing (NLP) techniques to learn from therapeutic
conversations to provide sympathetic encounters that are psychologically related. Our app in its
essence is an interactive, contextual, and AI-assisted chatbot that simulates supportive
conversation and encourages authentic disclosure and makes therapy readily accessible. The user
creates an account to gain access to our app’s features like personalized recommendations,
emotional
state/history
as
well
as
individual
context.
Features include:
- Users will be able to view dynamic mood/emotional history represented as a graph.
- Users will be able to benefit from personalized recommendations based on user preferences and
context.
- Users will be able to enjoy and feel better with light but engaging conversations with our smart
therapeutic chatbot.
- Users will be allowed to use text as well as voice as input for the chatbot.
- Users can write a journal about their day which will help model with recommendations and mood
History.
Technology Used:
GPT, RASA, Django, Firebase, Android
Supervisor Name:
Ms. Amna Irum
Group Members:
Shaheer Hassan (i17 - 0271)
Armaghan-Ur-Rasool (i17 - 0055)
Muhammad Valeed (i17 - 0081)
RandecII
RandecII is a ransomware detector which has been made to focus on hybrid analysis. Being
implemented with our own four machine learning algorithms, RandecII accepts file uploads and
processes these files to ultimately classify them as malicious or benign. This enables users to
comfortably know if any ransomware even part of the PUP family has been downloaded or installed
in their device. Different malicious files that are part of legitimate files can also be tested and be
correctly classified. The datasets used in training were taken from VirusTotal and Kaggle.
Features include:
- Realtime testing of malicious files
- Cloud storage and its benefits
- Hybrid analysis to ensure that the benefits of static and dynamic malware detection can be
achieved.
- Detection of obfuscated code.
Technology Used:
NodeJS, Python, Visual Studio Code, Eclipse, Angular
Supervisor Name:
Mr. Jawad Hassan
Group Members:
Usman Ali (i16 - 0164)
Afaq Asif (i17 - 0217)
RARRoad
RARroad is a computer vision based system that will assist the driver as road awareness is added in
the rover using deep learning algorithms implemented on Raspberry Pi. The RAR system will detect
and recognize traffic signs in real-time. The system will send its output to the mobile application
that will generate alerts to inform the driver and then arduino will change the rover behavior
according to the sign caught. It will significantly increase driver safety and road awareness. The
objectives of RARroad are:
1. Create a lane following the rover.
2. Create an AI-based system that enables traffic sign detection and recognition in real-time.
3. Create an “Alert Generation System” using an android application that alerts and notifies the
drivers whenever a traffic sign appears.
Create an IOT based system that will change the rover behavior according to the sign caught.
Technology Used:
Deep learning, Computer vision,
IOT, Android development.
Supervisor Name:
Dr. Adnan Tariq
Group Members:
Areeba Nasir (i17 - 0052)
Syeda Ramen Bukhari (i17 - 0086)
Mahnoor Shahzad  (i17 - 0241)
RATAR
RAT-AR is an augmented reality based remote assistance platform. It will change the way
technicians work on maintenance and repair operations. RAT-AR platform allows customer care
agents or technicians to work remotely, executing common technical tasks and maintenance
procedures in real-time. The display of real-time 3D annotations on environments and objects help
teams solve problems efficiently and with no extra relocation costs. For example, a customer can be
guided
to
troubleshoot
his
internet
or
set
up
a
security
camera.
Features include:
- Video/Audio calling by creating or joining a channel
- Ability to draw AR annotations that will be rendered on other user’s screen
- Live Forum where users can post problems and helpers can help them by joining the channel
- Real-time chat feature if a helper wants to share any technical documents/manual in order to help
the user
Technology Used:
Java, ArCore, Agora.io, Nodejs,Firebase, Android Studio
Supervisor Name:
Mr. Bilal Khalid Dar
Group Members:
Zaid Ali (i17 - 0226)
Aqeel Ejaz (i17 - 0364)
Ahsan Saleem (i17 - 0303)
Rehnuma
An interactive chatbot for admission inquiries in Roman Urdu
Roman Urdu is a resource-poor language and hasn’t been enough researched and worked upon by
researchers and developers. No intelligent chatbot for Roman Urdu is developed yet. Mostly the
existing chatbots understand only a limited number of static queries and give only a limited number
of static responses.
So, we developed an interactive and intelligent chatbot that understands and gives dynamic
responses to students’ queries in Roman Urdu. Our chatbot can handle different spelling variations
of Roman Urdu words, detect offensive language, and handle out-of-scope questions. Chatbot also
asks follow-up questions if the query is unclear or not enough information is provided. It then
extracts the required information from the query, uses that information to calculate or predict the
answer, and then replies to the user.
It also remembers the context of the conversation. We used the RASA framework for the
development of our chatbot and we got average accuracy of around 94% and an average F1 score
of around 84% for all the user intents.
It handles questions/queries falling in more than 50 different categories which include closing
merit, programs offered, merit list date, financial aid, entry test schedule, entry test pattern, sports,
scholarship, admission procedure, admission requirement, fee structure, semester system info,
refund policy, admission open, admission deadline, campus life, hostel info, transportation, grading
system, societies, facilities and many more.
Technology Used:
python, pyCharm, RASA framework
colab, github, React
Supervisor Name:
Mr. Umair Arshad
Group Members:
Muhammad Usman Zafar (i16 - 0430)
Okasha Khan (i17 - 0176)
Zain-ul-Abideen (i16 - 0064)
Scalable Aggregation of Text using big data tools
ScAT is real-time web based application which aims to save the Reader’s time while simplifying
redundant news articles. A user can read news from 2 or more news channel, by doing this he
waste a lot of time to study similar news articles. ScAT rectify this problem classifying news articles
to provide ease to the Reader . For this we employ big data tool such as Apache Kafka and Apache
Spark to streamline the News Articles from different news sources and perform Clustering,
Aggregation and Summarization upon them. Fetched articles streamed by kafka and make them
readily available for spark engine Processing.
1-Backend of the System is implemented in python with the help of Apache Kafka and Apache
Spark
2-GUI contain web portal which further comprised of two parts
2.1-Blog: It contain category wise Unique News and Similar News Articles in different tabs. Further
more summary is also provided of similar news Articles.
2.2-Analytic: It contain graphs which explain the raw and processed text in numerical and graphical
form. It provide comprehensive analytic of the text.
Technology Used:
Python, Pyspark, Apache Kafka, Apache Spark,
Pycharm, Angular and android
Supervisor Name:
Dr. Kifayat Ullah Khan Alizai
Group Members:
Mohammad Shahid Shakeel (f17 - 8001)
Asad Arshad (i17 - 0312)
Hassan Murtaza (i17 - 0368)
Scout Rover
Scout Rover is a 4-wheeled differential drive rover. It’s purpose is to explore unknown indoor
environments completely autonomously - without any human intervention. For this purpose, it uses
only a single front-facing depth camera as an input sensor. The visual data from the input is
processed to estimate the location of the rover in its environment by measuring relative movement
in consecutive video frames. This information is also used to simultaneously generate  a two-
dimensional (2D) map. The map shows occupied and open spaces in the environment.
Hardware setup:
- Arduino (on rover) is used to control the motor driver and move the rover
- Raspberry Pi (on rover) gets the data from Kinect (input sensor) and forwards it to server
- Server processes the data and sends movement commands back to the Raspberry Pi which is
relayed to Arduino and then to the motor driver.
Technology Used:
Raspberry Pi, Arduino, Microsoft Kinect,
Python, OpenCV, Flask
Supervisor Name:
Dr. Muhammad Adnan Tariq
Group Members:
Hamza Mukhtar (i17 - 0023)
Muhammad Musa (i17 - 0037)
Ahmed Mustafa Malik (i17 - 0227)
SHIFT DRIVE
A user-friendly mobile application that recognizes the make and model of a car by providing
image/video of the car, detects damage parts of the car and then estimates a repair cost for the
damage repair. Moreover, our application also allows workshop owners to get bid on the repair
cost which makes workshop procurement for customers, smooth.
There are two potential users of ourapplication i.e. Car owners& Vendors/Mechanics.
-
Car owners will be the core activators of the system. They can get the make and model of a car
by providing car image, damage parts of the car and get estimated cost on the damage repair.
-
Vendors/Mechanics get the damaged image/video of the car and then bid appropriate repair
cost against the damage of car according to their analysis.
Features of our application are the following:
1. Car Recognition: Recognize the car’s make and model through the provided image bythe user.
2.     Damage Detection: Detect any physical damage on the car’s body through an image.
3.    Repair Cost Estimation   Estimates a suitable cost for the damage repair.
4.    Workshop procurement:
Workshop owners shall be able to get the damaged images/videos of the car and can bid the repair
cost.
Our application detects three commonly observed types of car damages i.e. bumper dent,
windshield damage and headlight damage. So far, we have restricted our model to some specific
Technology Used:
[Java, Python,PyTorch, Google Colab,
Microsoft Azure,Android Studio]
Supervisor Name:
Dr.ShujaatHussain
Group Members:
Hamza Amir(i17-0125)
Rimsha Faisal(i17-0154)
Usama Mehmood(i16-0190)
SmartEye
A camera attached on top of a medium-sized ad (bus stop ads, subway ads) sends image frames to
a server. The server then processes those frames through multiple algorithms to detect and extract
features from a person’s face. The extracted features are attraction to ad, interest towards ad
(based on time for which person looks at ad), age group, gender. These features are then used to
generate a report that helps a company to evaluate the effectiveness of it’s ad placement.
Features include:
-Detects and localises head of people passing by the ad
-Estimates pose of their face to tell where are they looking
-Computes how many people saw the ad and how many did not
-Records time for how long each person spent looking at the ad
-Classifies gender and age of interested persons
-Based on the above mentioned statistics generates a report which summarizes how successful that
specific ad is through various visualizations and calculations.
Technology Used:
Python, OpenPose, Pytorch, Flask
ReactJS, Google Colab, VS Code
Supervisor Name:
Mr. Shoaib Mehboob
Group Members:
Rehan Azhar (i17 - 0003)
Mohsin Zaidi (i17 - 0216)
Saud Rais (i17 - 0344)
Smart Gharana
Smart Gharana is an automated home assistant in a single application that will help the user save
time by simplifying daily tasks. The system uses natural language processing and image processing
techniques to automate and assist users. Our system will help visually impaired people by
integrating voice commands which can be used to perform daily physical tasks such as, turning
on/off fans, lights, tv/radios and opening or closing doors. Our system will also act as a security
assistant detecting motion or any activity at odd hours and then notifying on app.
Features include:
- Control of home appliances using voice commands
- Security system using face detection/recognition and motion detection
- Reminders about set tasks and events
- Trained model recognizing Urdu commands
Technology Used:
Flutter, Flask REST, Arduino, Raspberry Pi, OpenCV,
CMUSphinx, Google TTS API
Supervisor Name:
Mr. Shoaib Mehboob
Group Members:
Mohammad Hamza Awan (i17 - 0110)
Farhan Khalid Butt (i17 - 0242)
Zain Tanvir (i17 - 0255)
SmartSlides
SmartSlides is an ecosystem where we have made it possible to store all the precious whiteboard
notes a teacher makes during their lecture. Those notes are stored very intelligently along with
each slide. To do this we carry on device real-time machine learning from the custom recorder app
to record a lecture in the classroom and run an ML model we have trained to detect whiteboard
notes, slides, and humans. Additionally, it stores only the useful frames compressing the recorded
data up to 90%. Then, we sent this data to servers where two more models are deployed to
compare slides and extract notes to attach with their respective slides.
Once processed, the slides are sent to the SmartSlides portal where students and teachers can carry
out threaded discussions, and invite others to their portal to view the SmartSlides shared for each
courses’ lecture.
Features include:
- Mobile optimized Machine Learning Models
- One-click operation to upload the recorded slides
- SmartSlides Portal’s Responsive Design
- Threaded discussion system
- Single UI to show slides and notes
Technology Used:
Flutter, Python, TensorFlow Lite, Firebase, Kotlin, Git
Supervisor Name:
Mr. Shams Farooq
Group Members:
Salman Mustafa (i17 - 0111))
Ali Hamza (i17 - 0254)
Hammad Ali(i17 - 0329)
Tailor Master
Tailor Master app is a system that trains itself on a 2D video of a user. It then uses the trained
model to generate 3D measurements identical to the user's original body measurements in the 2D
video input provided to it. We are going to provide a mobile application for this, which will make it
very easy for user to get their body measurements and customized dress design report. The
application will take a small 15-20 second video of a customer standing straight. The person has to
rotate around 360 degree slowly starting from the right and taking a 2 second pause at every 90
degrees. Besides this, the application will ask about the height, the body type and gender of the
person. These credentials will be used to get reference points to extract measurements. On the
other hand, the customer will be given a drawing platform where he/she can draw his customized
design for the dress on an outline of a dummy human or enter an image of a dress too. The
customer can enter manual details as well if he/she wants. At the end the app will generate a
report of the measurements and the selected design. Furthermore, there will be a recommendation
module that will help customer get dress design recommendations from the internet based on their
preferences.Features include:
- Extract 3d measurements from the 2d-video clip of the user
- Enter measurements manually
- Upload dress design image
-Draw customized dress designs
-select designs from the internet
-view report to the user of his/her measurements and dress design
Technology Used:
Python, Jupyter Notebook, Spyder, Google Colab, GitHub,
TensorFlow, OpenCV, SQLite, Android Studio, Firebase
Supervisor Name:
Dr. Mirza Omer Beg
Group Members:
Zainab Aftab Chaudhry(i17-0225)
Ahmed Feroz Manj (i16-0183)
The Autonomous Flight Supervisor
The Autonomous Flight Supervisor (TAFS) is an Artificial Intelligent agent designed to aid and
augment the operations of Air Traffic Controllers (ATCOs) during Approach and Departure phases of
flights. Air Traffic Control (ATC) is a highly complex, laborious, and error prone process which
requires the careful monitoring of entire teams to ensure flights travel safely and smoothly. TAFS
automates some of the routine tasks of ATC during Approach & Departure via Knowledge Graphs
and also presents a novel rule-based algorithm for Conflict Resolution in the said phases.
Features include:
❏ SID/STAR assignment based on runway, traffic, distance, destination/origin, and wind
❏ Runway vectoring for incoming flights
❏ Conflict Detection
❏ Conflict Resolution for flights that have lost separation
❏ Detection of false positives during Conflict Resolution
TAFS achieves humanlike performance on several metrics and traffic conditions.
Technology Used:
Python, JavaScript, Neo4j, CypherQL, openScope
Supervisor Name:
Ms. Amna Basharat
Group Members:
Muhammad Saad (i17 - 0033)
Muhammad Soban (i11 - 0058)
Muhammad Rassam (i17 - 0258)
Threatify – Threat Detection Using CCTV
Security is a huge concern in the modern world, since crime is increasing. To prevent crime, CCTVs
are installed everywhere along with CCTV operators to monitor the screens. This, however, isn’t
feasible at homes & shops because we cannot have an operator watching the footage 24/7. Having
CCTVs but still being unable to report crime either not viewing it at that instance or being under the
influence of gunmen could cause lots of damage.
We plan to develop a deep learning-based system which is capable of detecting threats the
moment it occurs and report the crime to the corresponding authorities as fast as possible. This
could result in minimizing the response time resulting in less damage, such techniques would have
high demand in this digital world.
Features include:
● Threat detection using CCTV feed.
● Threat classification. (Arson & Explosion, Fighting, Gun-Event)
● Web application.
● Android Mobile App
Notifying and sending location to the client and authorities about the threat.
Technology Used:
Pytorch, OpenCV, Python 3, Django, Android Studio Java
Supervisor Name:
Dr. Omer Ishaq
Group Members:
Muhammad Abdullah (17I - 0038)
Haasha Bin Atif (17I - 0183)
Muhammad Ahmed (17I - 0184)
Transcribing calls and Differentiating in between multiple speakers using
NLP techniques
Project aims at providing call transcription by not only doing exceptional continuous speech
recognition but also the identification of multiple speakers using various Natural Language
Processing (NLP) techniques. Sentences. The user will speak or provide audio and the website will
provide the text of the spoken words. This will help users to further store and use the transcribed
data and apply other Natural Language Processing techniques to obtain meaningful data. We intend
to build up a strong, steady, and normal scientific establishment for vigorous ASR for Urdu
language, underlining the strategies demonstrated to be fruitful and expected to continue or
extend their future materialism
Features include:
● To Gather large amounts of data that covers maximum words ·To recognize urdu words
● Formation of urdu sentences ·Automatic speech recognition for providing call transcription
Differentiating between speakers.
Technology Used:
Kaldi FrameWork,Git,Flask,Python
Supervisor Name:
Mr. Umair Arshad
Co Supervisor Name
Dr.Mirza Omer Beg
Group Members:
Muhammad Mazarib(i17-0004)
Muhammad Tauseeq(i17-0277)
Amna Zahid(i17-0286)
True Detective
True Detective is a system for disguised face recognition in CCTV footage with respect to bare face,
glasses, hats, fake beard and face masks as disguises. It is a deep learning based system which
makes use of keras library and dcnn models. The data include 11 individuals [male, female and
children] with 250 pictures each. The system consists of four modules. In module-1, it uses MTCNN
for face detection. It divides the faces into aligned and un-aligned and makes two separate face
databases. In module-2-3, it passes each database to a dcnn and extract the features from it. The
extracted features are combined and then passed to a CNN. In module-4, the cnn then trains on
these
extracted
features
and
give
results
on
test
data.
Features include:
- Realtime Face Recognition on the following:
 Bare Face
 Glasses
 Hats
 Fake Beard
 Face Mask
Technology Used:
Keras, sklearn, Python, Deep Learning
Google Colab
Supervisor Name:
Ms. Noor Ul Ain
Group Members:
Syeda Laiba Urooj  (i17 - 0219)
Hafiz Abdul Rehman Saad (i17 - 0346)
Ruhma Tariq (i17 - 0348)
TryItOut
TryItOut is a virtual platform to modify, tailor and try out dresses. It is a web application which has
4 modules, the user can choose TextureMod, TailorMod, Garment Transfer or Motion Transfer.
In TextureMod, the user will provide the image of the garment and the pattern and with the help of
image processing techniques such as thresholding, blending and clustering etc. the pattern will be
mapped on the target garment while keeping the details conserved. People who are into fashion
designing, they can try out different prints and patterns before creating them.
In TailorMod, the user will provide the source and target images and with the help of machine
learning model, image processing techniques and transformations, the neckline of source image
will be replicated on the target image. This feature will assist fashion designers, as they will be able
to tailor clothes virtually before taking any risk.
In Garment Transfer, the user will provide the source garment image and the target user image and
with the help of DensePose it will transfer the garment on the target image body. This feature can
be incorporated with any clothing website. It will enhance the online shopping experience of
people. Motion Transfer is like Garment Transfer, the only difference will be the target video in
place of target image, the user can test the Garment Transfer on their video.
Technology Used:
Image Processing, Computer Vision,
Machine Learning, HTML, CSS, Flask
Supervisor Name:
Ms. Noor Ul Ain
Group Members:
Rabbia Ijaz (i17-0293)
Armaghan Bashir (i17-0147)
Muhammad Hassan Bilal (i17-0281)
Uvea-  Image to Speech for the visually impaired
Uvea is an image to speech accessibility mobile application for the blind and visually impaired,
utilizing object detection and classification via deep learning techniques.
The visually impaired face different challenges in their lives.  A lot of them are simple day-to-day
tasks such as money counting, moving without collision knowing what macro objects are in their
path, etc.
In 2010, WHO estimated that about 285 million people are visually impaired, of whom 39 million
are blind. It is also predicted that by 2030, the numbers would rise to 330 million, and 55 million
respectively. With an ever increase in visually impaired people, the need for technology that assists
this very large market would also rise continually.
Features include:
Money Counter - allow users to count their money using the phone’s camera.
Collision Prevention - Object detection and classification in pre-set zones to prevent collision. It’ll be
limited to an indoor environment. The included objects are the following:
● Furniture: sofa, table, bed, chairs
● Walls
● Doors
Staircase Detection - Detection and classification (upstairs, downstairs)
Feedback via voice - to listen to the instructions, detected objects and current perspective
Input via haptic touch - to get instructions and switch perspective
Technology Used:
Flutter, Dart, Tflite, NumPy, Tensorflow, Python
Supervisor Name:
Dr. Omer Ishaq
Dr. Kashif Saghar
Group Members:
Mesha Farrukh (i17 - 0048)
Zubaria Ayub (i17 - 0231)
Mishaal Naeem (i15 - 0326)
Vehicle Speed Checking System
Road accidents have been very common in the present world with the prime cause being the
careless driving. Over speeding vehicles are major issues for road safety and needs proper
addressing to minimize the accidents. Excessive Speed is a factor in one third of all fatal crashes.
Therefore, to minimize such road accidents, we have developed a system to detect the vehicles
which are being driven above the given maximum speed limit that the respective roads or highway
limits. The overall project is divided in three categories: speed detection, image acquisition and
transfer and image processing.
Following are the features of VSCS:
 The system detects the speed of the moving vehicles on roads/highways.
 It detects the vehicle whose speed exceeds the speed limit of the highway/road on which the
vehicle is moving.
 It detects the number plate of the vehicle whose speed exceeds the speed limit.
 The system recognizes the registration number / licence plate number of the vehicle.
 System recognizes the brand of the vehicle.
 The system recognizes the type of the moving vehicle.
Technology Used:
Python, Flask, HTML,
PyCharm, Google Colab
Supervisor Name:
Dr. Irum Inayat
Group Members:
Syed Ali Javed (i16 - 0267)
Muhammad Saad (i17 - 0030)
Mian Khubaib (i17 - 0247)
Virtual Classroom (VClass)
The VClass application is being made to provide a more classroom like experience to the students
and teachers from the comfort of their homes. Our objective is to combine the features of multiple
platforms that students have been using for online sessions in one place, as well as create a more
interactive and immersive experience through virtual reality technology.
The application is being made with 3 views that can be logged into based on credentials, the
administrator, teacher and student views. The administrator will have the functionality to initialize
timetables, set up accounts, register teachers and students and manage the courses offered and
the student and teacher views will be able to perform classroom related tasks and functions.
Features include:
● Timetable viewing
● Shared Virtual whiteboard
● Assistance Button
● Attendance Marking
● Recourse Sharing
● Task submission and feedback
Virtual Reality environment
Technology Used:
Android Studio, Unity game engine, Firebase,
Google Cardboard
Supervisor Name:
Mr. Bilal Khalid Dar
Group Members:
Mustafa Shoaib (i17 - 0204)
Mubeen Khan (i17 - 0071)
Ahmed Abdullah (i17 - 0120)
Virtual Classroom
The Virtual Classroom is a web-based platform for digital education and off-campus classes. It
solves several problems faced by the current virtual classrooms such as attendance, measuring the
attentiveness of students during the lecture. Our virtual classroom aims to solve these problems by
solving these modern-day problems. For solving these problems, we are introducing automated
attendance with eye-tracking and facial recognition. By using these two features, we will calculate
the percentage of presence of a student during a lecture and automated attendance will be
marked.
Along with that, we also aim to introduce a feature of data analytics. In this feature, a student's
progress such as his grades in assignments, quizzes, grades, subjects, and other things like his
attendance, etc will be shown to the faculty for improvements overall in a course.
Features include:
- Basic Virtual Classroom (such as registering courses, online lectures, assignments, quizzes, etc).
-Automated attendance through Facial Recognition and eye-tracking.
-Provide a Dashboard to mentors to visualize the result of analyses.
Technology Used:
Django, Python, Html, CSS, Bootstrap,
JavaScript, MySQL.
Supervisor Name:
Sir Jawad Hassan
Group Members:
Fasih Saeed (17i-0245)
Uzair Ibrar(17i-0300)
Ahsaan Ullah(17i-0133)
VisualCircuit
VisualCircuit allows users to program robotic intelligence using a visual language application. Users
can follow the same design approach (connected blocks, dataflows) as FPGA programmers and
synthesize the circuit into a Python application. It follows this divide and conquer approach in
programming applications related to robotics, deep learning and computer vision. Each block is
considered as a separate and functional part of the system which is running independently at fast
iterations. The modular design helps the user to think in terms of blocks running concurrently which
can then be easily connected using wires which act as shared memory. This tool allows the user to
think and produce more effective applications, reduce development time and experiment with
more
solutions
in
a
short
period
of
time.
Features include:
- Block frequency monitoring and control.
- Enable/Disable wires for dynamic reconfiguration of the circuit.
- Block composition.
- User defined blocks, editable code and parameters support.
- 50+ blocks related to computer vision, deep learning and robotics.
- 3 Gazebo simulations demonstrating VisualCircuit to program reactive robot behaviors.
- Cross Platform: Windows, MacOS, Linux.
Technology Used:
Python, AngularJS, NodeJS, ROS, Gazebo,
OpenCV, Tensorflow, Electron
Supervisor & Co-Supervisor Names:
Dr. Atif Jillani
Jose Maria Canas
Group Members:
Muhammad Taha Suhail (i17 - 0045)
Faizan Ahmed (i17 - 0275)
Humaiz Tariq (i16 - 0133)
High Achievers
Class of BS (CS)
Adnan Ahmad (i17-0078)
Hailing from a small city in Southern Punjab opportunities were scarce for me from the start.
Somehow, I ended up at FAST where I found my fellow students having a great knowledge of
Computer Science already. That head start which many of my fellows got was missing for me.
I’ve been a fighter throughout my life. Challenges excite me and at that point in my first semester
completing a degree in FAST became a challenge for me. In my first semester I joined the
Computing Society. It really helped me polishing my managerial skills and opened doors for me to
enter the extra-curricular activities going around in the university. From organizing my first trip to
later on taking teams to Air University for competitions, I learnt a lot while with working the
amazing team of National University Computing Society.
By the end of my first two semesters at FAST I had improved myself a lot. I was totally a changed
person in terms of my knowledge of computer science my participation in co-curricular activities
and so on. The hard work and dedication I put on in improving my habits in my first year helped me
all the way to the final semester and it finally paid off when I got a Gold Medal in 7th semester.
I have seen both ups and downs in FAST. I started my journey from 2.75 in the first semester and
4.0 in the seventh semester. The supportive culture of FAST where from faculty to your seniors
everyone tries to uplift you is really amazing and close to my heart.
There are two months left in my graduation and I was offered jobs by multiple companies from
which I selected the one of my preference. It all was a result of what FAST taught me in terms of
hard and soft skills and the way FAST helped me groom myself.
Concludingly, I will always remember the memories I made at FAST and cherish the beautiful
moments spent with friends in NaSCon, Adventure Gala and Qawali Nights.
From being a student with a little knowledge of CS to making me a professional in Computer
Science, this is how I’ll remember this beautiful chapter of my life.
Ali Salman (i17-0350)
A piece of machine instilled a sense of fascination in me even as a toddler and raised a series of
exclamations on how incredibly it makes our life comfortable but also imprinted the “How”
curiosity to it. During middle school, the quest to curiosity slowly began to unveil when we were
supposed to take at least one class of Computer Science. Later in high school, the best thing I
encountered was Visual Basic programming which further boosted my expedition for answers and
passion for learning. Being the turning point of my life, it made me realize my inner potential and
my true passion.
With the motivation to grow in the field of Computer Science, I applied to multiple universities and
was selected by FAST National University, Islamabad. I accepted the offer and came to Islamabad to
pursue a bachelor’s degree in Computer Science. At first, it was onerous to adjust in the
competitive environment. The hostel life and homesickness were the main problems I was facing at
the start. In the first week of university, I was depressed when I interacted with my fellows, most of
them were from an A-Level background and I underrated myself and had a fear for my future. Fear
of competition and homesickness oppressed me, and made me apply for the transfer application to
the Karachi campus owing to it being near to my hometown, Hyderabad.  I tried my best, but it
could not happen. As time passed by, I learned to grow with my classmates and after the first
competitive exams I was sure that we all were on the same level, and it is solely the personal effort
and willpower that help us grow. I’m thankful to my professors who admired me in any way, which
helped me grow in the field of Computer Science. Most of them always encourage students to go
deeper into the concepts of Computer Science, placed their hands on their shoulders and helped
them when they needed them. Programming became my passion when I started to enjoy it. To
remain self-motivated, I always completed my assignment and project first in my circle and then
helped my friends to solve their issues and errors. It not only helped them but I also learnt a lot
when I guided them and listened to their queries. I’m thankful to the community FAST has provided
and strength. While spending my 4 years in between them, I learned their culture and acquired
their good habits.
It is my perception that entertainment and extracurricular activities are as important as studies.
Before the time of COVID-19, I participated in NaSCon as a board member to arrange a Speed
Programming Competition, and being a part of NUCS (National University Computing Society) I held
seminars to help juniors understand programming. I enjoyed the assignments and projects of
management courses i.e. AD designing, digitalizing current business, and social work. These
activities boosted my soft skills further and connections which would help me in my professional
life.
In the last semester, fear of a job is always there for a graduating student therefore FAST arranges a
Job Fair for the graduating batch. I am glad to share that I had gotten various offers before the Job
Fair Alhumdulillah. Their recruitment processes were primarily focused on both technical and soft
skills. This is the blessing of Allah, the sacrifices of my parents, and the motivation of teachers and
friends who remained with me in this whole journey.
Aimen Inam (i17-0156)
Joining Fast NUCES for Bachelors was my best decision. I knew that it will be tough to score in Fast
and that many students struggle a lot to clear courses; I was ready to face this challenge and I knew
I will not regret my decision.
My 1st semester was the toughest. Even though I had studied ICS, still I was not able to do
programming. I barely clear ITC course. Many people told me to repeat the course but I turned the
deaf ear to them. I believed in myself that one day I’ll be as good programmer as the Students with
A & A* in programming courses. In my CP (Computer Programming) course, I again lost hope of
clearing the course with good grade. I remember my teacher encouraged me a lot when I was upset
by looking at my midterm marks. Those words meant a lot for me. I completed the project and my
final exam with good scores and my grade for CP was better than ITC. The 3rd semester was a game
changer for me. I got a grip of programming because of the tough assignments and project of Data
Structures. I became a much better coder. I did face many problems/challenges in programming
courses, but I was able to solve them eventually. From 4th semester and onwards, my GPA was
improved Alhamdulillah!
On the other hand, my TAship experience helped me inculcate a sense of responsibility along with
my studies. Also, taking part in NASCON and doing Web Internship are amongst the wonderful
experiences I have had in Fast.
One thing that my Seniors have told us and now I tell my juniors is that we will not regret the
pressure of workload we faced and the struggle we made here; Fast NUCES has groomed us
professionally which we will learn in the days to come.
Areeba Nasir (i17-0052)
Coming to FAST was my aspiration from the very beginning. After doing my ICS, I applied for four
big, renowned universities of Islamabad and got selected in all four universities. But I was
determined to come to FAST from the outset. People around me used to say that FAST is a
challenging place, and I should not go there. But I knew that challenges could never retard me. I
believe that we cannot grow when things are easy; we grow when we face challenges.  So, this
belief brought me to FAST.
When I came to FAST, I instantly realized that it is indeed a challenging place. I was coming from a
year system, and adjusting into the semester system was very hard for me. I was always a high
achiever in my academics. I secured the 2nd position in the Rawalpindi Board of Examination in
HSSC. But I was having a hard time adjusting in FAST because of its semester system. At the end of
the first semester, I was very anxious and I even once thought of leaving FAST because of the
workload and burden. But when my result came, I was included on the Dean’s List. This
achievement drove me, and I regained my lost motivation to perform even better in the future.
FAST is also notorious for its challenging assignments, exams, and strict grading scheme. But what I
have learned is that determination and persistence are the keys to success. I believe that you
should never leave till tomorrow that which you can do today. This is the strategy I have always
followed, and Alhamdullilah I have been on Dean’s list throughout my four years. Being a computer
science student, I also identified that my interests are software engineering, android development,
machine learning, and UI/UX design.
FAST increased my learning in many ways. But one ability that stood out for me is Multitasking.
FAST taught me to perform multiple tasks simultaneously without getting panic. It also taught me
that how I can handle difficult situations tactfully.
When I reflect on my four years journey, I would say that FAST had a great impact on my
personality growth and development. It helped me polish my interpersonal and communication
skills and boost my confidence in dealing with people and different situations.
Daniyal Hassan (i17-0411)
The renowned institute, FAST NUCES, dedicated to the relentless pursuit in the name of computer
science has been a perfect place to learn and grow. FAST was never just an alma-mater, it has
always given a sense of home.
Post-secondary education is not just about academics. It's about the entire social, practical,
interpersonal, and academic experience which grooms the personality of the students. The
experience at FAST comes with a lot of extracurriculars. Some of the societies like NUCS are well
reputed and well known not just within the university. There are regular events, seminars, training,
industrial visits and much more on a weekly and monthly basis. Apart from that, our flagship event
roof. Other societies like FAST Adventure Society, Dramatics Society, and Production Society keep
organizing inter university events and keep us engaged.
institute, I came across some of the wonderful educators that actually helped me rebuild my hope
Omer Beg, Dr. Ehtesham Zahoor, Dr. Sibt ul Hussain, Dr. Hammad Naveed, Dr. Omer Ishaq and
more who are much more than just professors. Growing under the tutelage of such minds was an
extraordinary experience.
Apart from the academics, the beautiful green campus is something that I will miss alot. The
campus, both in the open area as well as building architecture is stunning. Over these 4 years, FAST
has also evolved and improved for the better. The mesmerizing new building with state of the art
labs and learning resources offers the perfect classroom experience. In terms of academics, there is
amazing research on the latest state of the art technologies like cloud and blockchain etc.
Over the course of my academic career, I have picked up and developed various sets of skills that
have helped me to achieve more, in and out of the classroom. I’ve been awarded multiple gold and
bronze medals and I’m a member of the Dean's and Rector’s list. The institute has a huge network
of reputed alumni which aids its students to be welcomed warmly at the industry. Thanks to that, I
have almost 2 years of industrial experience before graduation. FAST has provided me with a safe
haven to achieve academic excellence and develop an amazing and diverse skill set which will help
me emerge triumphant in my ambitions of life. Every moment spent over the course of 4 years
brings cherishable memories and I look forward to pay back this university, as an alumnus, to
further improve as I recognize its potential to produce amazing humans and computer scientists.
Muhammad Soban Raza Gillani (i17-0058)
FAST undoubtedly enabled my intellectual transfiguration yet the decision to major in Computer
Science was quite an impulsive one. I enrolled at PIEAS and after writing a couple of "Hello World"
programs, I had an epiphany and I knew I wanted to do CS for a living. Yeah, that impulsive.
Anyhow, the decision was made and I joined FAST.
I earned a Silver Medal in my first semester and that was...fortuitous. For better or worse, it kept
compelling me, forcing me to earn more medals in the subsequent semesters. It took continual
effort but I was able to earn a spot on the Dean's or Rector's List every semester. It was probably
worth it.
FAST, my friends and my professors nurtured my passion for Computer Science and cultivated my
love for technology. They made sure that stagnation was not an option and growth, academically or
otherwise, the only choice. I have been able to explore most, if not all, areas of Computer Science
with substantial rigor and enthusiasm and my journey here, in retrospect, has been most
productive. FAST's effectiveness lies in its challenging academic life. Those who are gallant enough
to take on the challenge will definitely be ahead of the game in the IT industry.
Anyway, four years of academia has drained me. I look towards an auspicious (and hopefully
lucrative) future in the industry, towards a path for which my journey at FAST would provide many
impetuses. Perhaps, one such impetus has been being able to secure a good job 3 months prior to
graduation.
Mariam Khalid (i17-0165)
Thinking about my journey at FAST, it would be an understatement that it has been a roller coaster
ride. However, my story is extremely different from most of the other high achievers. It all started
when I joined FAST in 2017 because of its reputation for Computer Science. I had mild knowledge of
computers but always found it interesting that how the applications work and the logics behind
them. I’ve always been a high achiever and won certificates for the outstanding results that I got in
my Matriculation and Intermediate studies. However that changed when I joined university. In first
semester, the whole semester system was very new to me so I had a hard time adapting to it. I
survived every course except the first programming course, i.e ITC and faced my first ever failure in
life when I was given an F in that course. After that, I lost hope and even thought of leaving FAST at
a point. However, in third semester I told myself that leaving and giving up is not an option and that
I had to stand up again after what felt like a thunderstorm. From that day onwards, began my
journey to work day and night just with the intention to graduate with a respectful GPA as well as
good technical skills and learning. That was probably the phase in my life when I’ve worked the
hardest and I had never been this consistent and organized. The first milestone was when I got an
A+ in my second programming course. My GPA began to improve every semester, giving me more
and more faith in myself. However, in 5th semester all that hardwork payed off when I was awarded
a medal for an SGPA of 3.93.
FAST has not only enabled me to manage stress and extreme work situations but has also provided
me with the soft skills including communication skills, time management, creativity, responsibility
and most importantly, adaptability. I now understand in true sense what the Alumni of FAST mean
when they say “It’s a long journey but it’s worth it”.
Mesha Farrukh (i17-0048)
Ever since I first started thinking about what I wanted to do with my life, Computer Science was
definitely on top of the list. Majoring in Computer Science meant picking the best university for
myself after studying from the best institutes prior, and naturally, the choice without a thought was
FAST.
My journey here at FAST has been strenuous and exhausting for sure, but just like how diamonds
are made under pressure, I can also say the same for myself. The person I am today, FAST has
played a major role in helping me grow into it. Almost 4 years ago, I entered this place, lost and
anxious, not knowing anyone. Like everyone else, I struggled, faced setbacks, and eventually got
back up too but all this helped me grow and discover my passions. The same girl who had stage
fright and barely could give a presentation in a room of 10 people now could talk to a crowd with
confidence which FAST helped me gain. As this confidence in myself grew so did my GPA and along
with that came the dean’s list, rector’s list, bronze, and a gold medal.
While it made me realize my true potential, it also made me discover my love for design and how to
incorporate it into my degree and take them side by side. Other than that, it carved out the
perfectionist in me that I didn’t know I had, made me a better leader, and enhanced the
hardworking aspect of my personality. The key to achieving all of this is balance, balancing your life
with your academics is a harder struggle I thought it was which FAST helped me learn, and while I
excelled academically, I also became part of FDC, NaSCon, expanded my social circle, and did part-
time freelance work which all also aided in improving my social skills.
Now, 4 years later, I’m leaving with heaps of knowledge, confidence, and passion, ready to do
wonders. All of this wouldn’t have been possible without this university and for that, I’ll always be
grateful.
Mahnoor Shahzad (i17-0241)
I entered the university life as a student who was always interested and curious but not exactly an
ambitious person. When people around me used to tell what they want to become, I always
thought about how it felt to have a dream and clear goals in front of you. The only thing I wanted to
do was to select a challenging field to test my limits, and FAST BSCS proved to be perfect in this
way. In Matric and even in FSc, I never took computer subjects and wanted to get into an
engineering field, this all seemed impossible, but now when I look back it is as if Allah had planned
this for me.
When I first started the degree, I was completely new to the world of computers, where as
everyone around me had strong basic knowledge and were proficient in the skills. I never claimed
myself to be an intelligent person, but I could seriously feel myself lacking and as a result frustrated
with myself. If everyone was at level 4 than I would have probably been a level 0. I struggled hard to
keep up during first three semesters. People usually say that hard work and dedication leads to
success, and I fully agree with this as hard work is what led me to where I am now Alhamdulillah.
FAST has played a very important role in preparing me to be ready to face the world by providing
such a supportive environment where I was able to flourish, develop skills in all aspects of
computer science, and make friends along the way.
What started as a challenge, has now become my passion. Me being an un-ambitious person,
having equal to zero knowledge related to the field of Computer Science, now being able to stand
here today was only possible with prayers and mercy of Allah. This was not an easy journey but the
platform and continuous support from FAST made it worth it. Now being in the final semester and
seeing the end in front of me, I am ready to start a new chapter in my life by making a career in this
industry. I’m passionate about contributing in the society from what knowledge I have earned and
the support I have received.
Muhammad Bilal Shabbir (i17-0124)
On joining FAST, an ambivalent feeling of hope and fear sparked off, the fear of not being
graduated on time, facing the high competition, and the hope of sitting with the great minds of
around me. As time passed by, I learned more and more regarding the technical and moral stuff
from great teachers having comprehensive knowledge and ample experience. Starting off as an
average student, the campus's wide cognitively intellectual environment made me self-aware of my
own strengths and weaknesses, leading me to be a more expressive individual after fathoming non-
trivial capabilities by comprehending the contestable deepness of logics and by envisioning rational
problems from different perspectival angles.
The benign air of cordial trees, the exercisable and conspicuous extracurricular activities, the
symphonious chant in the prodigious cafe, the sound of silence in the colossal library, all corners of
the campus taught me something unique and helped me to be gradable. If I summarize my overall
journey with one informal word, I would state it as 'Supercalifragilisticexpialidocious'.
Myra Rafique Khan (i17-0129)
My journey at FAST-NU has been the greatest learning opportunity of my life; and I do not mean it
only academically.
I chose Computer Science as a major simply out of my love for messing around in computers and
solving technical problems for my siblings and parents that no one else seemed to understand.
However, when I started this degree, I had not expected it to be as time-consuming or tough as it
turned out to be. Even though I knew a lot about computers, the only programming I had ever
come across was the MSWLogo programming language in primary school. In my first semester, it
felt like everyone had the problem-solving skills needed for this degree and understood the tools
and technologies except for me. It made me feel like I was lacking the talent that computer
scientists had.
It was a time to decide whether to give up or to work hard enough so as to never fall behind again.
The thing is, giving up was never the answer for me. If I started something, especially because I was
genuinely interested in it, I was not going to quit it simply because others were better at it than me.
I felt like if I gave up on this, I would forever be giving up on things.
So, along with my university projects, I started taking online classes on platforms like Coursera and
edX. During this journey, I managed to equip myself with some of the strongest time-management
skills; I was carrying out my university life, my self-learning projects and my personal and social life
together.
I managed to learn how to communicate with my teachers and my peers when I got stuck in a
problem. This was one of the most important skills I acquired because, due to my competitive
nature, I had always wanted to do everything by myself. Moreover, I learned teamwork by working
with all kinds of individuals including friends, colleagues and people I had never talked to before. I
learned how a good leader can even make a team of freeloaders produce quality work; the way to
assign tasks, arrange meetings and demos with teachers, and take on the team leadership role.
At the beginning of this journey, I was doubtful about all my skills. I wasn’t sure if I had it in me to
ever work hard for anything. But during these four years, FAST has tested and polished my skillset
in every possible way. Along with this my parents’ support in every phase of my life has made me
extremely confident about my competence and my ability to make anything happen when I put my
mind to it. I am sure that as I enter my professional life, everything I have learned here would be
very useful.
Mohammad Taha Bin Firoz (i17-0323)
When I look back to one of my oldest memories, I see myself sitting in a chair, observing my father
and elder brother intently as they are getting our first family PC built at a store. I was blessed with a
father who understood the importance of computers and what they meant for our future. By giving
his children access to a personal computer at a very early age, he kindled our need to learn and
understand the world of computers. Him being a very early programmer, it was typical to find
archaic sheets of hand written assembly, 5 inch floppy drives and books on programming littered
around the house.
This environment had driven all my elder siblings to learn some skill on the family machine,
whether that was learning to browse on dial-up internet or even make digital art. Though every
sibling had their own contribution in building my interest in the big white tower, my sister had by
far the most influence. Watching her manipulate images in Photoshop and learn HTML over a
weekend amazed my young mind. My first foray involved me clicking around the desktop and
tinkering with programs. I learnt flash animations at the ripe age of 6 years old, and started
exploring the World Wide Web by then. While a majority of my time was spent playing online flash
games, I'd spend the rest of my time using Google to learn about how things worked. As I grew
more acquainted with the machine, I had this constant urge to learn how it worked. I was always
looking for answers to questions like; ‘How do computers work?’ or ‘How are games made?’. That's
when my journey with programming began, I started to learn my first programming language C and
C++ at the age of 10. My life was inevitably tied with the world of programming when a good friend
of mine introduced me to a relatively new game called Minecraft. I spent a better part of my
childhood playing that game and modding it. This led to my first steps into my second language,
Java, at age 13. I'd spend days pulling my hair making the tiniest change in the game and
celebrating when it worked.
My grades, however, had always remained average because I wasn’t interested in the education I
got at school. I started working hard when my A levels began and by that time I’d already started
learning my third programming language Python and was ecstatic to learn that it was a part of my
Computer Science course. My sister had sent my application for Computer Science in Fast, which I
was skeptical about initially. I spent the rest of my time working hard and studying in remembrance
of my late father who had passed away from cancer a couple of years ago.
It's not a surprise that I did end up flourishing in Fasts programming heavy environment. I’ve had
very few teachers who I can say had a strong impact on my life, and I found a majority of them at
Fast. Having those great professors motivate me and push me to achieve my potential, I was able to
balance working full time, while also working on a startup and completing my degree in BSCS.
Without the help of Allah SWT, my mother, my siblings and the support of my closest professors I
would not have been able to become what I am today.
Namrah Rasool (i17-0018)
Success is not final, failure is not fatal; It is the courage to continue that counts. (~Winston
Churchill) This quote truly summarizes my life in a sentence. I was a brilliant student who always
had a great academic performance and whose parents wanted her daughter to become a
Neurosurgeon but unfortunately I wasn’t able to achieve the required merit to be admissible into a
medical college. After taking a gap year, my father advised me to take Additional Mathematics
papers and apply for Engineering universities, and now I am, graduating from FAST-NU as a
computer scientist. It was all meant to happen and I was destined to become a computer scientist.
In the first semester, I got a silver medal followed by another silver medal in the 3rd semester, a
bronze medal in the 5th Semester, and got 4 SGPA in the 6th semester. Allah has been kind and I
am so grateful to Him for all the successes I am blessed with. Moreover, I got a fully-funded
scholarship from a government organization from 3rd semester onwards. Coming to Fast Nu proved
to be a great decision made by Allah which made my parents feel proud and regain the trust that I
lost in the past year. Alhamdulillah, these four years at Fast-NU happened to be the best years of
my life.
Noman Nasir (i17-0062)
I had heard a lot about FAST being the number one university when it comes to computing and I
can claim that now without a doubt that truly it has been a phenomenal journey for me. FAST not
only taught me how to excel in my practical life but moreover they taught me about the core values
and ethics of professionalism. I learned to think out of the box to solve real life problems and help
the community. Yes, it is true you will get a tough time while studying here but that is a blessing in
disguise because when I see myself now at the end of my journey, I can see the benefits of it such
as high demand in market, polished skillset and an ethical human being, ready to face any
challenges professional life throws at me.  Life at FAST is not all about studies, I have met great
people in my life here from so many different regions of the country and made life-long friendships.
Best part about FAST is that there is no such thing as biasness here, if you do good, you are bound
to get reward for it and the whole administration is so cooperative and supportive towards
students and whole system is transparent and fair ground for all students.
I cannot thank FAST enough for giving me this opportunity to study among the best of people and
best of mentors. It has been a rollercoaster ride that lasted 4 years and it has taught me so much
through practical and theoretical knowledge that I can say that this is one of the best universities
that takes the future of their students seriously and ensure we secure a good position in future.
Noor-Ul-Huda (i17-0153)
Taking a decision about your future and your career is the hardest to make for some people.
However, luckily, for me I decided to be a computer scientist or a software engineer from a very
small age. Even when I didn’t even know what it meant to be a software engineer. When the time
came to apply for different universities, I wanted to go to FAST since I heard that it’s really good in
the field I wanted to apply for. Fortunately, I got into two renowned universities but after a few
suggestions and taking advices from people, I finally decided to join FAST. Little did I know, this
decision would become a source of a roller coaster journey for me in my time in FAST.
In the beginning, I had some troubles settling in because of the work load. The first two semesters
started off as a rough start but even then I managed to get a good GPA Alhamdulillah. In all the
stressful times, my parents and friends would always support me and so the journey from 3rd
semester onwards became a bit easier than before. Now I am in my last semester, about to
graduate in a few months, and looking back at my journey now, I have a lot to thank FAST for. Every
little push, every assignment, every task played its part in what I know now. Such things seem a bit
hard when you are in the moment, but with time, you get to know how everything polishes you and
your skills. Studying in FAST not only polished me in my field but also in my interpersonal skills.
The journey after this part seems a bit hard, applying for jobs in different companies, but I can't
wait to find out what the future has in hand for me. Allah has been so merciful to bless with me
with all the opportunities, to have been studied from FAST, to have such a supportive family to
make everything easier for me. And so, whatever the future holds for me, I know I will always thank
everyone and FAST for making it all possible.
Rawan Amjad (i17-0025)
Looking back at my FAST’s journey bring all kinds of flashbacks from crying alone to laughing loud
with my friends. It has been a journey full of ups and downs like a rollercoaster but there isn’t a
single incidence that I am not grateful for. Each experience has helped me become what I am today
and if I had the chance I wouldn’t have changed anything. At the beginning like many other
individuals, it was not easy for me to settle in the new environment. After maintaining a good
academic record throughout my life I had high expectations of excelling from the very start. In the
first semester there was immense pressure and I could only manage to score a reasonable sgpa but
this experience gave me great confidence to face my fears and enhanced my problem solving skills.
Over the time, I learned to work well under pressure and put in my best efforts to learn new stuff.
This resulted into a consistent increase of each semester’s gpa over the last semester and then
finally scoring a silver medal in the final year. FAST provided me the opportunity to explore my
interest by offering all sorts of courses ranging from data science to software development. The
courses are structured according to the latest market trends and technologies. I am grateful for all
the amazing fellows and mentors I have met here which were always there to guide me and never
failed to be a source of inspiration. Along with my studies I also participated in co-curricular
activities throughout my university life. I chose my lifelong passion of designing and served as Head
Graphic Design for FIRS. I have also been designated as Vice Lead Design for Google DSC Club.
These roles helped me in polishing my leadership and communication skills. I learned to balance all
aspects of life and not just stick to course work all the time. FAST helped me bring out the sides of
my personality that I didn’t even know existed, it taught me the most important skill to never give
up in my life no matter how tough the situation gets. It has boosted my confidence and I am fully
prepared to step into professional life without feeling intimidated by the new challenges ahead. I
am thankful for all the memories that I have made here and indeed remembering them would
always be a source of joy for me.
Rafsha Mazhar (i17-0028)
When I was younger, my mom would help me prepare my notebooks for the new term and she’d
always write some motivational quotation on the first page, something along the lines of “Nothing
is impossible for a willing heart”. She believed in always aiming for a hundred percent. At that time,
I used to argue that no matter how hard I try, or will, I could never get a hundred percent. That
some things were, in fact, impossible. And somewhere along the way, I started giving more weight
to what I had told her than to what she had taught me.
Back in 2017, when I got admission at FAST NUCES, I was still exploring my career options and
wasn’t so sure either about FAST or about Computer Science. To top it off, everyone had created
this image that you could never get good grades here no matter how hard you try, that you may
excel in the industry post-graduation but never within the university. Already unsure about my
career path, this negativity only added to my demotivation and convinced me to not even try, in my
first semester here. Needless to say, I didn’t get an appreciable GPA that semester.
The following semester, I had no plans to improve because I hadn’t quite realised the fault in my
judgement then but I put in a slight effort for my grades anyway, rather than completely being
hopeless about them. That semester, both my SGPA and CGPA increased significantly, which came
out as a huge surprise for me. That is when I realised my mistake and started aiming for goals I had
previously deemed unattainable. I challenged myself every semester to break my own record and
pushed myself to continuously improve. I knew focusing on my studies or challenging myself to
better myself continuously shouldn’t affect my co-curriculars so I learnt about management and
balance and about prioritising the right thing at the right time. And above all, I developed a can-do
attitude. I figured I shouldn’t ever let anyone else’s experience affect mine because everyone has a
different story and I figured that staying positive and steadfast despite everyone telling you
otherwise, is the key to success, not only at FAST but anywhere and everywhere. I learned that you
don’t really lose if you fail but if you let the negativity overpower you and you start doubting your
own capabilities that is when you truly lose. Success isn’t about how far you have come in a race
against everyone around you but it is about how far you have come from where you started;
everyone’s journey is unique and so must be their success story.
I’ll forever be grateful to Allah, and to my parents, my teachers and my mentors, my colleagues and
my friends and to everyone else who helped me grow and learn and stay positive through my
journey. I couldn’t have done this without them. I learned and unlearned a lot in these four years
and above all, I grew as a person. Now as I am stepping out into my professional life, I hope I
continue to push myself and challenge myself to advance in my knowledge, career, understanding
and faith, and to always be a source of pride for my parents and my mentors. I hope to put in my
best and to bring value to wherever I go next, and to finally put all the knowledge and skills I have
gained here, to professional use.
Syed Hammad Ali Shah (i17-0329)
It has been a wonderful 4 year journey at FAST. I was passionate about Computer Science and stuff
related to it since I was 7. So, I joined FAST to learn more about it but I have learned a plethora of
useful skills along with the mandatory courses. We learned about leadership, being ethical,
compassionate about your work to name a few. I became friends with like-minded people which
helped me a lot to find new opportunities in real life.
At FAST, you are challenged to your absolute best every day. You learn about your new limit, what
you thought was not achievable by you is now your second hand job. The great teachers here give
you an immense level of exposure not only from an academic perspective but from real life career
and problems perspective. So, when I started this journey and was pushed to my limits, I got scared
with a fear of failing. But, that fear drove me into working harder and harder every day. So, I started
overcoming this fear bit by bit in just a semester. With all this hard work and effort, I got 4 gold and
1 silver medal. I believe that the exposure and learning I got from FAST is a bigger reward than a
medal. I’m very thankful to my teachers, parents and friends who supported me in this long
journey. I wish best of luck to all the students and want them to know that each bit of their hard
work would not go to waste. So, keep excelling!
Sher Bano (i17-0104)
Although the journey at FAST can never be summed up in one page, I will try to encapsulate it to
the best of my ability.
Right from the start of my educational journey, I was quite sure about pursuing a career in
Computer Science and FAST made it possible. This incredible journey was possible with Allah's
guidance, support of my parents especially my father and the right mentorship of my instructors.
When I told people that I am pursuing a career in Computer Science, I received remarks like “Why
not become a Doctor or an Engineer?”. Clearly, they did not think of CS as an important field. But
Alhamdulillah I am very satisfied with my decision.
I have always been a high achiever throughout my educational career. I secured 2nd position in the
Federal Board in HSSC examination. At FAST, I was able to make my way to Medal holders and
remained in the Dean’s and Rector’s list of honors throughout. FAST provided me with a number of
other opportunities to further polish my skills. FAST also introduced me to the GHC (Grace Hopper
Celebrations) Scholarship which is the world's largest gathering of women technologists. Women
fortunately I was one of them. As a GHC’19 Scholar, I got the opportunity to attend the GHC
Conference at Orlando, Florida. It really improved my confidence, communication skills and
interpersonal skills. At FAST, I also participated in extracurricular activities like arranging workshops
and events. I was an active member of FAST Women in Computing (WIC). I also served as a Vice
Head of Welfare Department in FAST Islamic Revival Society (FIRS).
The first semester at FAST was a bit challenging for me. FAST is famous for its demanding and
stressful environment. At first, I was also overwhelmed by the huge workload, assignments, quizzes
and projects but eventually I got used to it. In my first mid exam, I got minimum marks in ITC which
was considered basics for Computer Science. It was indeed a challenging time but instead of giving
up, I did not lose hope. I worked hard and Alhamdulillah learned a lot from it. Now I can easily face
these types of challenges and that’s the beauty of FAST. It polishes the students so well that after
this drill of four years, students embrace the stressful situations with a strong will power and
courage.
The journey at FAST was quite tough but Allah (SWT) guided me at every stage. He always showed
me the right way and helped me with His absolute knowledge. Alhamdulillah He has blessed me
with amazing teachers, friends and mentors who guided me throughout my journey. I will definitely
miss FAST and all it has given me. Although it is my story, many students at FAST feel like giving up
and lose motivation to cope up with challenges. Hopefully, they can find comfort in my story and
get inspiration from it.
Saad Zahoor (i17-0046)
Being a bright student from the very start of my education it was apparent that the people around
me had high expectations from me and my grades in O and A levels further strengthened their
hopes of a prosperous future for me. When I completed my A Levels I wasn't sure of what career
path to choose but computer science wasn't a choice I thought I would make but fate had other
plans.
When I started my journey in Fast as a computer scientist I faced a lot of difficulties because of my
lack of knowledge in the computing field and adapting to the semester system. This led to a poor
performance in the first two semesters. It was a huge setback for me as it not only lowered my
morale but also had a devastating impact on my parent’s expectations. Eventually I realized that the
only choice I had was to either keep doubting myself or working hard to gain knowledge so that I
could overcome the barrier which restricted my growth.
The situation started to get better as I began to develop interest and I had continuous support and
help from my class fellows and teachers which assisted me in cementing my position in the Dean’s
Honor list for the 1st time in the 3rd semester. I also got an opportunity to work as an internee at
Planet beyond in the software development department. This further boosted my confidence which
along with the constant hard work contributed to my increasing GPA in the next semesters and
finally achieving a medal in my 2nd last semester.
Fast has transformed me into a person who refuses to give up and believes there exists a solution
to every problem not only in programming but also in real life. It has also taught me time
management and how to handle pressure. Moreover it has turned me into a skillful professional
ready to step into work life.
Apart from studies I got the exposure of extracurricular activities by working at various positions in
events such as Nascon, Adventure gala, FUDC etc. I was mostly the head or vice head of teams such
as marketing, sponsorship etc. and the outbound activities linked with these teams enhanced my
communication, persuasion and leadership skills.
To anyone who is reading this, let me tell you that you will fall, you will feel like giving up, you will
fall again. But the most important advice I can give you is to keep standing up because it will pay
off. Take that from someone who started off with a low GPA and ended up scoring a medal.
As I look back on my journey in fast I see struggle but I also see good learning experience, good
company of friends, guidance by exceptional teachers and a time well spent. I will always be
grateful to Fast for composing me into the individual I am today.
Zubaria Ayub (i17-0231)
Coming to FAST was a very unexpected decision considering how I dreamt of going to NUST for as
long as university existed in my world. I still remember telling my father, ‘I am telling you with a
heavy heart that I choose to go to FAST, not NUST because it’s better for CS. Please bear with my
rants but this is my final decision.’ To this day, I don’t regret my decision. I started off as a
somewhat arrogant bookworm and today I am a leader, an adviser, a team player, and proud of my
transformation. This wouldn’t have been possible if it weren’t for FAST and everyone associated
with it. It’s an emotional journey that I would love to document in deep detail someday but this
FAST is well known for its ‘raggra’ and I must say that the foundations for this publicity are not
weak. Day after day, week after week, month after month, and ofcourse semester after semester,
FAST did not fail to throw a new challenge at us, the students. While going through all that, the end
of the world seemed like it was right around the corner but as the semester ended, we were able to
sigh in relief for missing the end of the world by a millimeter. And without even realizing it, we’ve
come out as polished individuals.
Another well-known fact about FAST is how helpful and approachable our faculty is. And through
these amazing faculty members I was able to attain priceless internship experience without having
to step into the private industry. My internships are with Info Systems Lab to develop a scheduling
engine for newspaper delivery and with Nexsys Lab working on mobile app development. Not only
were they a chance to learn technical skills but also groom myself on the soft skills front as well.
Very early on during the degree, I realized I want to do more than just academia. However, I was
intimidated by interviews and never showed up for them. One fine day, a senior called to ask me to
show up for an interview and that’s when I stumbled upon NaSCon. Things went only uphill from
there. I gained so many soft skills such as team work, team leadership, and time management
under the umbrella of NaSCon and it also paved the way for me to join NUCS. And today, I am
eternally grateful to be the first female President of NUCS which has led to some pivotal changes in
the standard of how societies should be run.
Today, I am happy that 4 years ago I chose FAST for its repute in the industry and got a lot more
than just the affiliation with the good name. I made epic memories, found amazing friends, and last
but not least, grew to become a person I am proud of in all aspects. There is surely a long way to go
still but I feel ready to face the world especially after a roller coaster of 4 years. A few months ago,
while the realization of the degree ending was still far away, I didn’t think I would say this but thank
you FAST, for everything.
PosiƟon Holder
Class of BS (CS)
Medal Holders of Bachelor of Science (Computer Science)
Batch 2017
S.No
Roll-No
Name
Fall-17 Spring-18 Fall-18 Spring-19 Fall-19
Fall-20
17I-0231
Zubaria Ayub
Gold
Gold
Gold
17I-0018
Namrah Rasool
Silver
Bronze
Silver
17I-0058
Muhammad Soban
Raza Gillani
Silver
Gold
Bronze
Gold
Gold
17I-0228
Haysam Bin Tahir
Bronze
Silver
17I-0411
Daniyal Hassan
Bronze
Bronze
Gold
Bronze
Gold
17I-0329
Syed Hammad Ali
Shah
Silver
Gold
Gold
Gold
Gold
17I-0062
Noman Nasir
Bronze
17I-0104
Sher Bano
Bronze
Silver
Gold
Gold
17I-0153
Noor-ul-Huda
Silver
10 17I-0165
Mariam Khalid
Bronze
11 17I-0048
Mesha Farrukh
Bronze
Gold
12 17I-0241
Mahnoor Shahzad
Bronze
13 17I-0052
Areeba Nasir
Gold
14 17I-0078
Adnan Ahmad
Gold
15 17I-0124
Muhammad Bilal
Shabbir
Gold
16 17I-0129
Myra Rafique Khan
Gold
17 17I-0156
Aimen Inam
Gold
18 17I-0025
Rawan Amjad
Silver
19 17I-0323
Mohammad Taha Bin
Firoz
Silver
20 17I-0350
Ali Salman
Silver
21 17I-0028
Rafsha Mazhar
Bronze
22 17I-0046
Saad Zahoor
Bronze

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