p040_Zarnish_Jawad.pdf

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filename: p040_Zarnish_Jawad.pdf, name: Zarnish Jawad, summary: Highly motivated Artificial Intelligence Engineer with a Bachelor's Degree in Artificial Intelligence. | Demonstrated expertise in developing innovative solutions through different projects. Proficient in multiple | programming languages, with hands-on experience in using various tools and frameworks for data analysis, | machine learning, and Ai development. Known for strong problem-solving abilities, adaptability, effective | communication, and teamwork., experience: Intern, AI Engineer | BizzClan | August 2024 - September 2024 | Assisted in developing and deploying AI-based solutions. Contributed to real-world projects involving | computer vision and natural language processing. Collaborated with senior developers on integrating AI | models into software products. | Intern, AI Engineer | National Centre of Artificial Intelligence NCAI | August 2024 - September 2024 | Developing a multi-functional surveillance system that integrates face recognition, vehicle tracking across | cameras, license plate detection, crowd density monitoring, and suspicious activity detection. I used | YOLOv8 for object detection, DeepFace for real-time face recognition, and OpenCV for video feed | processing. I enabled parallel processing for efficient multi-camera analysis and ensured real-time alerts for | anomaly detection., skills_technical: NLP, CSS, HTML, Machine learning, Neural Networks, Mongodb, Computer Vision | Interpersonal Skills: Communication Skills, Analytical Reasoning, Team Work, Problem Solving, education: COMSATS INSTITUTE OF INFORMATION AND TECHNOLOGY ISLAMABAD, PAKISTAN | Bachelor of Science in Artificial Intelligence | CGPA (3.09) February 2022 – Present | ASPIRE GROUP OF COLLEGES, AJK | Intermediate in Pre-Engineering September 2020 – July 2021 | Grade: A | Marks: 1000/1100 | THE LEARNERS SCHOOL & COLLEGE, AJK | Matriculation 2017-2019 | Grade: A | Marks: 1005/1100, projects: Traffic Sign Detection | Tools: Jupyter Notebook, OpenCV, Matplotlib, Keras, Pandas | Description: Developed a Traffic Sign Detection system using a Convolutional Neural Network (CNN) for | the classification of traffic signs. Conducted preprocessing and Exploratory Data Analysis (EDA) using | Python, achieving 90% accuracy. | Gender Classification | Tools: Scikit-learn, Matplotlib, Numpy, Pandas, Visual Studio | Description: Pre-processed data and implemented various Machine Learning algorithms for gender | classification, achieving 96% accuracy. | Netflix Data Analysis | Tools: Scikit-learn, Jupyter Notebook, SQL | Description: Conducted an in-depth analysis of Netflix viewership data using Python to | understand user behavior, content viewership, and viewing patterns. | Hand Gesture Recognition | Tools: Numpy, Pandas, Python, OpenCv, MediaPipe Hands, TensorFlow/Keras, Matplotlib | Description: Trained a CNN based model on a dataset to classify gestures like “fist”, “peace”, “thumbs up” | etc. Used a MediaPipe to extract hand keypoints and fed them into the model for classification. Integrated the | model with OpenCV to enable real time gesture detection via webcam. | E-Diary (Web-Application) | Tools: Node.js, MongoDB, React, Visual Studio | Description: Developed a secure and user-friendly web application for online journaling, enabling CRUD | operations on diary entries. Utilized a modern tech stack for both front-end and back-end development. | Shop Management System | Tools: IntelliJ IDEA, MySQL, Swing | Description: Developed a shop management system utilizing Object-Oriented Programming (OOP) | principles and an interactive GUI. Designed to streamline and automate various shop operations, | ensuring efficient management of inventory, sales, and customer data. | Hospital Management System | Tools: MongoDB, SQL, React | Description: Built a Hospital Management System using a hybrid database approach for flexible patient data | management, structured billing processes, and robust transactions. | Fake News Detection System | Tools: Python, Tensorflow, Keras, Scikit-learn, Pandas, NLTK | Description: Built a binary classification model using LSTM and TF-IDF features to detect fake news. | Applied text preprocessing techniques including tokenization, stopword removal, and lowercasing. | Trained the model on a labeled dataset and evaluated it using accuracy, precision, recall, and F1-score to | ensure robustness. | SmartEye - Intelligent Surveillance System | Tools: MongoDb, OpenCV, YOLOv8, DeepFace, Python, Roboflow, OpenMP, CCTV Feeds | Description: Developing a multi-functional surveillance system integrating face recognition, vehicle | tracking across cameras, license plate detection, crowd density monitoring, and suspicious activity | detection. Used YOLOv8 for object detection, DeepFace for real-time face recognition, and OpenCV for | video feed processing. Enabled parallel processing for efficient multi-camera analysis and ensured real- | time alerts for anomaly detection. | TuteAi | Present | Description: Developing an AI-driven educational mobile application that processes user- uploaded | PPTs/PDFs to generate summaries, flashcards, and quizzes. Integrated a 3D animated character that lip-syncs | and explains content using an NLP-based chatbot. Implementing gamification elements, user assessment, | and age-adaptive explanations.

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