Muhammad Ammar Shahzad

Academic

Career

Verbatim text

Muhammad Ammar Shahzad
Cell: 923208405284 |  Email: ammarshahzad365@gmail.com
LinkedIn: https://www.linkedin.com/in/muhammad-ammar-shahzad-611604165/
Address: HOUSE 35, STREET 6, SWAMI NAGAR, LAHORE , Lahore , Pakistan
PROFESSIONAL PROFILE
Software Engineering undergraduate at NUST with a strong focus on artificial intelligence and machine learning, complemented by
solid experience in full-stack and systems development. Skilled in building and deploying intelligent applications using PyTorch,
TensorFlow, and modern web technologies, with hands-on research experience in adversarial learning and deep neural networks.
Brings a strong mathematical foundation, practical problem-solving ability, and experience translating research and engineering
concepts into scalable, real-world solutions.
EDUCATION
BESE
School of Electrical Engineering and Computer Sciences (SEECS) , Islamabad , 3.5 (2026)
INTERNSHIP EXPERIENCE
GoSaaS Inc.
02-Jun-2025 - 13-Jul-2025
• Developed full-stack features for a containerized log management platform using Node.js, TypeScript, and Oracle JET, including a
user settings module and secure OAuth 2.0 authentication. • Containerized the application stack using Docker and Docker Compose
to streamline development and deployment workflows. • Implemented Redis-based notification queues to monitor log thresholds and
trigger real-time alerts based on application logic. • Collaborated in Agile sprints, participated in daily stand-ups, and managed Git
workflows including branching, rebasing, and conflict resolution.
TUKL R&D Lab, National University of Sciences and Technology (NUST)
01-May-2024 - 16-Aug-2024
• Conducted research on adversarial attacks targeting deep neural networks, including CNNs and LSTMs. • Implemented and
evaluated adversarial techniques such as FGSM and DeepFool to analyze model robustness. • Developed and trained machine
learning models for speech classification and language translation tasks. • Built a text-to-speech pipeline converting textual input into
audio output using deep learning techniques.
Oz Limited
01-Jun-2023 - 18-Aug-2023
• Designed and implemented homepage recommendation systems using collaborative and content-based filtering techniques. •
Applied supervised and unsupervised machine learning algorithms for user personalization. • Integrated trained machine learning
models into an Android application for real-time recommendations. • Worked with cross-functional teams to align machine learning
solutions with product requirements.
FINAL YEAR PROJECT
RentSight: AI-Powered Profitability Estimation for Short-Term Rental Properties
This project aims to build a general-purpose AI-based application that estimates the profitability of residential properties when rented
on short-term platforms like Airbnb. The system will use real estate data—scraped from websites like Zameen.com as a case study—
and apply machine learning to predict expected income, occupancy rates, and investment potential. By analyzing factors such as
location, price, and property features, the application will provide real estate investors with useful, data-driven insights into short-term
rental profitability. This area is still emerging in Pakistan. Although Zameen.com will be used for testing and validation, the system will
be scalable and adaptable for different real estate markets. The project holds both academic value and commercial potential.

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