Final Year Project
Projects
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Departments
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Supervisors
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Batches
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| S.No | Department | Program | Project Code | Project Name | Supervisor | Designation | Mapped SDG | Tools & Technologies | Domain | Batch | Abstract | Students |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Electrical Engineering | BE Electrical | Solar-Powered EV Charging with Battery Swapping Technique (Control Part) | Engr. Raza A. Jafri | Associate Professor | Lithium-ion Batteries (48V), Battery Management System (BMS), Microcontroller, IC’s, Arduino IDE, Real-Time Dashboard. | Renewable Energy / Electric Vehicle Technology / Smart BMS | Fall 2022 | This project presents a solar-powered EV charging and battery swapping system designed to charge 48V, lithium-ion battery packs of electric bikes using solar panels. Each pack includes its own Battery Management System (BMS) and microcontroller to ensure safe and reliable charging. The microcontroller connects the BMS with the dashboard for real-time monitoring. The system addresses one of the most common EV challenges, long charging times. Operating entirely on solar power, it reduces grid dependency, lowers carbon emissions, and enables sustainable, efficient, and convenient electric mobility through battery swapping. | *Muzahir Hussain* (22FA-002-PE) | ||
| 2 | Electrical Engineering | BE Electrical (Electronics) | Real-Time Accident Detection and Alert System for Bikes | Engr. Raza A. Jafri | Associate Professor | Arduino IDE (C/C++), ESP8266 Microcontroller, MPU6050 Sensor, GPS Module, GSM Module,12volt battery, Push button, LEDs, Buck converter, Buzzer, Micro SD card module, Veroboard. | Embedded Systems, IoT | Fall 2022 | The Accident Detection and Alert System for Bikes is a safety focused project developed to ensure quick emergency response and minimize fatalities during road accidents. The system employs a NodeMCU ESP8266 microcontroller as the central processing unit and an MPU6050 accelerometer and gyroscope sensor to continuously monitor the bike’s motion and orientation. When a sudden impact or abnormal tilt is detected, the system interprets it as a potential accident and immediately activates a buzzer and LED indicator to alert the rider. | Muhammad Huzaifa Arshad (22FA-004-EE), Zoya Khan (22FA-009-EE) | ||
| 3 | Electrical Engineering | BE Electrical (Computer Systems) | FYP-22B-CE | Design And Development of a compact freeze dryer | Dr Abid Kareem / Engr. Syed Muhammad Zia Uddin | Dean / Assistant Professor | Vacuum Chamber • Vacuum Pump • Condenser (Cold Trap) • Heating Pad • Temperature and Pressure Sensors • Microcontroller | Software and Hardware | Fall 2022 | The goal of this project is to design and create a small, reasonably priced freeze dryer that can be used in small-scale industrial and laboratory settings. By freezing materials and subjecting them to vacuum, which causes the ice to sublimate, a process known as “freeze drying” (lyophilization) eliminates water from the materials. Important parts of the system will include a temperature control unit, condenser, and vacuum pump, all of which will be managed by a microcontroller. With potential uses in food preservation, pharmaceuticals, and scientific research, the project aims to produce a working prototype that can effectively preserve heat-sensitive biological and chemical materials. | Name: Uzair Siddiqui (22FA-004-PE) Name: M.HAMMAD (22FA-042-CE) Name: Salateen Ali Soomro (21B-061-CE) Name: Muhammad Abdullah (22FA-067-CE) | |
| 4 | Electrical Engineering | BE Electrical (Power) | Solar-Power Charging System with Battery Swapping Technique (Power). | Engr. Raza A. Jafri | Associate Professor | Solar Panels, Charge Controller (MPPT), DC-DC Converter, Lithium-ion Battery, Protection unit | Lithium-ion Batteries (48V), Battery Management System (BMS), Microcontroller, IC’s, Arduino IDE, Real-Time Dashboard. | Fall 2022 | The project focuses on designing a solar-based charging system for an electric bike to promote clean and sustainable transportation. Solar panels convert sunlight into electrical energy, which is regulated through a charge controller and stored in the bike’s battery. The system reduces grid dependency, utilizes renewable energy, and contributes to environmental conservation. Performance will be analyzed under varying weather conditions to determine efficiency and charging time. | · Syed Haider Abbas (22FA-009-PE), · Syed Subhan Reahn (21B-023-PE), · Abdul Hadi Ghori (22FA-007-PE) | ||
| 5 | Electrical Engineering | BE Electrical (Computer Systems) | FYP-22B-05-CE | Glove Talk: Smart Two-Way Communication System for Deaf and Mute Individuals | Engr Dr S Talha Ahsan / Engr Aimen Naseem | Associate Professor / Assistant Professor | 9, 10 | • Flex Sensors, IMU (ADXL345) • Arduino / ESP32 Microcontroller • Bluetooth (HC-05/06) • LCD Display, Vibration Motor • Python (ML Model), C++ (Arduino Programming) • MIT App Inventor / Android Studio (Mobile App) • Google TTS / STT APIs | Assistive Technology, Embedded Systems, Artificial Intelligence (Machine Learning), Human–Computer Interaction | Fall 2022 | This project develops a smart glove with flex and IMU sensors to recognize sign language gestures using machine learning. Sensor data is transmitted via Bluetooth to a mobile application that translates gestures into text and speech (Urdu/English) for hearing individuals. For reverse communication, the hearing person can type or speak through the app, which converts it into a gesture message displayed on the LCD screen of the glove, with vibration feedback. The system is designed to be affordable, localized for Pakistan, and inclusive, bridging the communication gap between deaf/mute and hearing communities. | Syed Talha Khurram, Syed Saad Ullah Ahmed, Laiba Ali Khan, Ahmed Ali Ashbal |
| 6 | Electrical Engineering | BE Electrical (Computer Systems) | FYP-22B-01-CE | AI based food recognition and nutrition estimation plate | Dr. Engr. M. Ghazanfar Ullah | Professor (EL) | 3 | • Pi Camera • Raspberry Pi • LED Matrix Display • Python (AI & ML Model) • Digital Image Processing | AI and Digital Image Processing | Fall 2022 | This project develops an AI-based Smart Food Recognition and Nutritional Estimation System using Raspberry Pi. The system uses a camera to for image aquisition to capture a food plate. The system then detect food items in real time using AI and Digital Image Processing techniques, and, estimates their nutritional content (calories, protein, carbs, and fat) using a fixed-weight model and a preloaded offline database. | 1. Laraib Khan (22FA-025-CE) 2. Ayesha Naveed (22FA-054-CE) 3. Ilsa Zeeshan (22FA-078-CE) 4. Mohib Najam (22FA-037-CE) |
| 7 | Electrical Engineering | BE Electrical (Computer Systems) | FYP-22B-07-CE | Autism Spectrum Disorder | Dr. Engr. M. Ghazanfar Ullah | Professor (EL) | 3, 9 | • EEG Headset • Computer + LCD Display • Python (AI & ML Model) • Digital Signal Processing • Cloud Computing | AI and Digital Signal Processing | Fall 2022 | The project introduces a smarter, more caring approach. Using a simple EEG headset, we gently record brain activity and let AI analyze the signals to spot patterns linked to autism. The system is designed not only to identify early signs but also to detect the different stages and levels of ASD such as mild or moderate making diagnosis more precise and meaningful. The goal is simple: give families and healthcare providers a tool that makes diagnosis faster, more accurate, and accessible for both children and adults. By recognizing autism early and understanding its stage, timely interventions can begin helping individuals grow, learn, and live with better support every day. | 1. Sameer Mohsin (21B-151-CE) 2. Ammar Raza (22FA-003-CE) 3. Abdullah Ali (22FA-001-CE) 4. Maryam Tariq (22FA-085-CE) |
| 8 | Electrical Engineering | BE Electrical (Computer Systems) | FYP-22B-09-CE | VR Based Lab Simulator for Digital Logic Design | Dr. Engr. M. Ghazanfar Ullah | Professor (EL) | 4, 9 | High-end computer system, VR headset, Unity for VR Environment, Blender for modeling, C# for scripting, | Computer Graphics, Digital System Design | Fall 2022 | In many educational setups, students face challenges in performing practical experiments due to limited lab resources like lack of equipment, or insufficient lab time. This creates a gap between theoretical knowledge and practical understanding, especially, in subjects dealing with digital design for example, Digital Logic Design. As a result, students often miss out on developing strong problem-solving and hands-on skills. This project aims to address these challenges by developing a Virtual Reality (VR)-based lab simulator that provides an interactive and immersive environment for learning. Using a VR headset, students will be able to enter a virtual lab where they can pick components such as ICs, breadboards, wires, LEDs etc., place them on a virtual workbench, build logic circuits, and test their outputs. The simulator will provide instant feedback on whether the circuit is correct or incorrect, making the learning process engaging, practical, and error-driven just like in a real lab. The solution will not only improve conceptual understanding but also make practical learning accessible in schools, universities, and remote learning setups where hardware labs are limited. Additionally, it reduces costs of physical components, electricity, and maintenance while providing a scalable platform that can later be extended to other courses. This project promises to enhance the overall learning experience, bridge the gap between theory and practice, and provide institutions with a cost-effective and reusable lab solution for the future of digital education. | 1. Ali Irfan (22FA-036-CE) 2. Muhammad Sheharyar (22FA-048-CE) 3. Muhammad Annas (22FA-012-CE) 4. Ibrahim Hussain (22FA-013-CE) |
| 9 | Electrical Engineering | BE Electrical (Computer Systems) | FYP-22B-10-CE | AI based Aeroponic System | Engr. Salman Jafri / Engr. Aimen Naseem | Senior Assistant Professor / Assistant Professor | ESP32, DHT11/DHT22, pH & EC sensors, Python, C/C++, scikit-learn, Arduino IDE, Firebase, | AI , Embedded Systems | Fall 2022 | This project integrates artificial intelligence with a vertical aeroponic system to automate plant | Ayesha Asim, Hadia SIddiqui, Usma Arshad, Areeb Alvi | |
| 10 | Computer Science | BS Computer Science | CS01 | Proactive Defense Mechanism (AIS Threat Intelligence) | Engr. Jawad Ahmed Bhutta | SDG 9 (Industry, Innovation & Infrastructure) | Python, Flask, STIX/TAXII, Wireshark, TShark, Python Tkinter, Cybersecurity, Threat Intelligence, Network Security | Network | Spring 2022 | This project presents a Proactive Defense Mechanism using an AIS-based Threat Intelligence System that enhances cybersecurity through automated threat information sharing. The system collects logs and Indicators of Compromise (IOCs) from multiple endpoints and analyzes them to detect potential attacks such as flooding, spoofing, and scanning. It applies the Common Vulnerability Scoring System (CVSS) to prioritize threats based on their severity (Low, Medium, High, Critical). Once prioritized, the system automatically generates security rules, which are then forwarded to the Information Security Engineer for validation and approval. After review, the rules are sent to the Network Administrator to be enforced on defensive systems, ensuring both accuracy and controlled deployment. The platform also includes features such as a secure login system, visualization dashboard, alert reports, and cross-organization threat intelligence sharing. Overall, the system minimizes response time, strengthens proactive defense, and promotes collaborative cybersecurity practices. | Fatima Farid (22sp-001-cs), Ashar Shahid (22sp-002-cs), Rija Qazi (22sp-038-cs) | |
| 11 | Computer Science | BS Computer Science | CS02 | CYBER QUEST (Gamified Cybersecurity Learning) | Engr. Fauzan Saeed | SDG 4 (Quality Education) | Unity, C#, Mixamo, Avaturn, SketchUp, Blender, CyberSecurity, E-Learning | Education, Network | Spring 2022 | Cyber Quest is a gamified cybersecurity learning platform developed using Unity3D. It transforms traditional awareness training into an interactive, story-driven desktop game where users learn cybersecurity fundamentals through engaging gameplay. Cyber Quest is primarily targeted at beginners and individuals with little or no prior knowledge of cybersecurity or real-life digital threats. With immersive scenarios, avatar-based interactions, dynamic scoring, time-based challenges, hints, badge rewards, and progressively increasing complexity, it provides an enjoyable and impactful way to build practical cybersecurity skills. | Muhamil Hussain (22SP-011-CS), Abdul Ahad (22SP-010-SE), Asher Abid (22SP-062-CS), Bushra Khalid (22SP-060-CS) | |
| 12 | Computer Science | BS Computer Science | CS03 | Sign Language Translator Using Myo Sensor | Dr. Muhammad Wasim | SDG 10 (Reduced Inequalities) / SDG 4 | Python, myo sensor, flutter, E-learning | Education | Spring 2022 | Sign language translator using Myo sensor with AI is a project that we CS students are creating to bridge the communication gap between us and the deaf and mute community of our country in the field of education. This project utilizes electromyography (EMG) signals acquired from the Myo armband to develop a gesture recognition system for sign language interpretation corresponding to alphabets and common words in both English and Urdu Pakistani sign language. | Saad Alam (22sp-016-cs), Huzaifa Ahmed (22sp-033-cs), Rabail Khan (22sp-012-cs), Somal Farhan (22sp-057-cs) | |
| 13 | Computer Science | BS Computer Science | CS04 | Live Walking Pattern Analysis | Zeeshan Saleem Khan | SDG 3 (Good Health & Well-being) | Python, OpenCV, MediaPipe, Streamlit, Firebase, Computer Vision, AI | Health, Medical | Spring 2022 | This project focuses on building a real-time system that analyzes human walking patterns through live video streams. The goal is to automatically capture gait data and use it for applications such as identification, health monitoring, and behavioral studies. The process begins with acquiring live video from a webcam, followed by pose estimation techniques to detect key body joints and movements. These features are then extracted and structured into datasets that can be used for machine learning and recognition tasks. The system emphasizes automation, accuracy, and efficiency, making gait data collection simpler and more standardized. The interface is designed to be user-friendly, enabling researchers and developers to visualize walking patterns, track datasets, and manage outputs with ease. In short, this project provides a practical solution for real-time gait analysis and dataset generation. | Hashir Ul Wara (22SP-025-CS), Eesha Tir Razia (22SP-061-CS), Shajia Fatima (22SP-063-CS) | |
| 14 | Computer Science | BS Computer Science | CS05 | InterviewSense (Emotion & Body Language Insights) | Ms faiza / Talha Ahmed | SDG 8 (Decent Work & Economic Growth) | OpenCV, MediaPipe, FER, TensorFlow, Librosa, Python, AI | Business | Spring 2022 | This project focuses on building a real-time system that analyzes candidates’ emotions, body language, and speech patterns during online interviews. The goal is to provide a complete evaluation by capturing soft skills such as confidence, honesty, and engagement, which are often missed in traditional interviews. The process begins with acquiring live video and audio, followed by facial emotion recognition, pose estimation, and speech analysis to detect key behavioral and emotional cues. These features are then structured into meaningful insights that reflect the candidate’s confidence, stress levels, and communication style. The system emphasizes real-time analysis, accuracy, and fairness, making the interview process more transparent and data-driven. The interface is designed to be user-friendly, enabling interviewers to monitor behaviors instantly and review post-interview reports with ease. | Syed Muhammad Naqvi (22SP-028-CS), Amal Nasir (22SP-014-CS), Irtiza Yawar (22SP-047-CS), Areej Tahir (22SP-050-CS) | |
| 15 | Computer Science | BS Computer Science | CS06 | UVMVerifier (Hardware Verification Automation) | Dr. Farhan Ahmed Karim | SDG 9 (Industry, Innovation & Infrastructure) | Electron, Python, Langchain, JS, QLora, LLM, ROCm, AI, Design Verification | Software Industry | Spring 2022 | UVMverifier is a desktop application that streamlines the hardware verification process by automating UVM testbench generation. Users can upload specification documents and RTL design files, which are then processed by the system through text extraction, chunking, and embedding generation. A local LLM analyzes the specification to identify key verification features, which are subsequently mapped to relevant RTL components, ensuring traceability between design and requirements. The tool assists in generating UVM testbenches based on these extracted contexts, significantly reducing manual effort and errors. Built with Electron.js, the application offers a modern, multi-page interface, Overall, UVMverifier enhances verification efficiency by combining AI-driven feature extraction with automated testbench support. | Abdul Rehman (22sp-052-cs), Syed Saad Akhtar (22sp-029-cs), Kinza Fatima (22sp-032-cs) | |
| 16 | Computer Science | BS Computer Science | CS07 | CloudNOOE (Infrastructure as Code Generator) | Zeeshan Saleem Khan | SDG 9 (Industry, Innovation & Infrastructure) | Python, Django, JS, TS, NextJS, Langchain, LLM, AWS, AI and Cloud Computing | Software Industry | Spring 2022 | A solution that simplifies the cloud infrastructure design and deployment process. The core idea behind this solution is to fine-tune a Large Language Model (LLM) to understand user requirements and translate them into Infrastructure as Code (IaC) specifically for AWS. Apart from generating IaC through natural language prompts, the system includes a drag-and-drop editor for users to modify the generated design visually, live costing for services, optimization recommendations, and collaboration between stakeholders and engineers. | Hadi Haider (22sp-031-cs), Ubaid ur Rehman (22sp-023-cs), Subul Raza Zaidi (22sp-041-cs), Taha Ali Zuberi (22sp-037-cs) | |
| 17 | Computer Science | BS Computer Science | CS08 | ShellSweep (Reverse Shell Detection) | Engr. Fauzan Saeed | SDG 9 (Industry, Innovation & Infrastructure) | Python, Nodejs, Typescript, LLM, Nmap, React, Vite, Networking & Cybersecurity | Network | Spring 2022 | ShellSweep is a security suite designed to help system administrators detect and mitigate reverse shell attacks, one of the most overlooked yet critical cybersecurity threats. Its primary focus is on identifying suspicious outbound connections, unusual port usage, and process anomalies that indicate a potential reverse shell, providing admins with realtime alerts and mitigation options. Beyond reverse shell detection, ShellSweep extends to IoT environments, where lightweight devices are often prime targets due to weak security. It strengthens defenses by mapping network traffic, monitoring device behavior, and cross-checking malicious IPs against public databases as well as a locally trained AI model. As a compact yet powerful tool, ShellSweep empowers organizations with proactive visibility into underlooked attack vectors, offering both detection and mitigation capabilities to strengthen their overall security posture. For IT and security teams, it acts as both a detection system and a mitigation framework, enabling quick responses to threats that traditional solutions often miss. | Syed Ahmed Haroon (22SP-035-SE), Hassan Javed (22SP-018-CS), Faraz Hashmi (22SP-017-CS), Daniyal Mirza (22SP-024-CS) | |
| 18 | Computer Science | BS Computer Science | CS09 | Haptic VR Simulator with RPG-7 for Military Training | Dr. Farhan Ahmed Karim | SDG 16 (Peace, Justice & Strong Institutions) | Unity3D, VR Headset (Oculus), RPG-7 Replica Controller with Haptic Feedback, C++, Military Training Simulation, Virtual Reality, Defense Technology | Education | Spring 2022 | This project is centered on developing a hyper-realistic VR simulator that integrates haptic feedback and RPG-7 functionality to transform military training. The simulator addresses the challenges of traditional live-fire training, including high costs, safety risks, and limited ammunition availability, by providing an immersive virtual environment that replicates real-world combat conditions. Using a high-fidelity VR headset, a custom RPG-7 replica controller, and advanced motion-tracking technology, the system enables trainees to practice authentic weapon handling, aiming, and firing in a safe yet realistic manner. By incorporating accurate rocket trajectory modeling and stability algorithms, the simulator enhances decision-making, muscle memory, and tactical awareness. Ultimately, the solution reduces training expenses, improves safety, and makes rocket launcher training more accessible, scalable, and effective for military personnel. | Hamza Shahid (22SP-045-CS), Laiba Ata (22SP-048-CS), Laiba Khalid (22SP-066-CS) | |
| 19 | Computer Science | BS Computer Science | CS10 | QYBERIAN (Fingerprint Encryption) | Engr. Fauzan Saeed, Mirza Farrukh Waheed Baig | SDG 9 (Industry, Innovation & Infrastructure) | GoPQ or liboqs-go, crypto/aes, OpenCV, mediapipe, SQLite, Cybersecurity, Image Processing | Software Industry | Spring 2022 | This project focuses on extracting fingerprints from normal images (such as those uploaded on social media), enhancing them for clarity, converting them into secure digital vectors, and encrypting them using a hybrid cryptographic model. The system uses YOLOv7 and MediaPipe for hand and fingertip detection, image processing techniques for enhancement, AES for encryption, and Kyber ML-KEM for secure key exchange, ensuring quantum-resistant data protection. | Saad Bin Ejaz (22sp-054-cs), Haroon Pervaiz (22sp-049-cs), Anas Anwer (22sp-006-cs), Syeda Akfa Feroz (22sp-046-cs) | |
| 20 | Computer Science | BS Computer Science | CS11 | Batsman Pro (Cricket Shot Highlights & Tracking) | Ms. Shiza Hassan | SDG 3 (Good Health & Well-being) / SDG 9 | Python, LSTM, Pose Estimation, YOLOv8, Flutter and Cloud Storage, AI and Computer Vision | Sports | Spring 2022 | Batsman Pro is an AI-powered mobile application designed to give grassroots and amateur cricketers access to professional-level performance analytics. The system analyzes practice videos to automatically detect cricket shots, identify bat-ball contact, and evaluate footwork and posture. It generates automated highlights along with contextual feedback, enabling players to refine their techniques without costly equipment or manual video editing. Built on computer vision and machine learning, with mobile accessibility through Flutter and cloud integration for storage and scalability, Batsman Pro makes advanced cricket analytics simple, affordable, and accessible to everyday players. | Muhammad Wahaj (22SP-059-CS), Muhammad Ahmed (22SP-064-CS), Afnan Inayat (22SP-051-CS), Ahmed Saarim (22SP-004-CS) | |
| 21 | Computer Science | BS Computer Science | CS12 | VISTA (SOAR-based Security Cluster) | Engr. Fauzan Saeed | SDG 9 (Industry, Innovation & Infrastructure) | VirtualBox, pfSense, CAPEv2, HTML5, MongoDB, Redis, Pydantic, Uvicorn, Bash, Python 3 (asyncio), FastAPI, aiohttp, CSS, JS, Loadbalancer, Wazuh, Cyber Security, Threat Intelligence, Networking | Network | Spring 2022 | We are building a SOAR-based security cluster that combines Wazuh SIEM/IDS, a custom load balancer, and CAPEv2 sandboxing. Suspicious files and logs are quarantined and analyzed through CAPEv2, while alerts are visualized on Grafana dashboards for better clarity. The setup runs on multiple virtual machines, simulating a scalable and real-world SOC environment. | Afnan Abbas (22SP-060-SE), Layba Asif (22SP-062-CS), Abdullah (22SP-005-CS), Rehma Rehan (22SP-022-CS) | |
| 22 | Computer Science | BS Computer Science | CS13 | UIT University Virtual Tour (VR) | Dr. Muhammad Wasim | SDG 4 (Quality Education) | Unity Engine, Blender, VR | Education | Spring 2022 | Experience UIT University like never before with our immersive Virtual Reality (VR) Campus Tour. This innovative digital experience allows prospective students, parents, and visitors to explore our state-of-the-art facilities, classrooms, laboratories, and vibrant campus environment from anywhere in the world. The VR tour offers a realistic and interactive way to get a closer look at the academic and social life at UIT University, making it easier to envision your future with us. | Muhammad Yahya Khan (22SP-067-CS), Zoha Mumtaz (22SP-027-CS), Bazila Kazim (22SP-026-CS), Rehman Nadeem (22SP-008-CS) | |
| 23 | Computer Science | BS Software Engineering | SE01 | SOFTWARE PQ TESTING | Usman Waheed | SDG 9 (Industry, Innovation & Infrastructure) | React, TypeScript, Node.js, Express, PostgreSQL, Drizzle ORM, Python, Mimesis, JMeter, Playwright, AWS, Docker, Performance Testing | Software Industry | Spring 2022 | A web-based platform that simulates real-world traffic to test performance with real-time insights and reports. | Shehzad Razzaq (22SP-037-SE), Umair Ahmed (22SP-001-SE), Rafia Hasan (22SP-040-SE), Areeba Ahmed (22SP-050-SE) | |
| 24 | Computer Science | BS Software Engineering | SE02 | YOUSOLUTION (AI BASED VIDEO SEGMENTATION) | Dr Adnan Ahmed Siddique | SDG 4 (Quality Education) / SDG 9 | FLASK, OPEN AI API, YOUTUBE API, WHISPER, PYVIDEO AI | Software Industry | Spring 2022 | YOUSOLUTION IS AN AI BASED VIDEO SEGMENTATION TOOL THAT WORKS ON QUERIENG THE SEGMENT YOU WANT TO RETRIEVE FROM A LONGER FORMAT VIDEO | Sawaiz Kamal (22sp-011-se), Saniya Waheed (22sp-052-se), Bilal Iqbal (22sp-044-se), Amin Jawed (22sp-027-se) | |
| 25 | Computer Science | BS Software Engineering | SE03 | Automated Hallucination Reduction for LLMs | Dr. Farhan Ahmed Karim | SDG 9 (Industry, Innovation & Infrastructure) | pytorch, Transformers, js, scikit-learn, ROCM, AI | Software Industry | Spring 2022 | A research-driven system designed to minimize hallucinations in large language models (LLMs). The project leverages a generator-discriminator framework, combined with data cleaning pipelines and model fine-tuning, to detect and filter out inaccurate or fabricated outputs. It supports CUDA acceleration for efficient training and is part of a broader ai4org toolkit aimed at improving the reliability and trustworthiness of AI-generated content. | Shehroz Kashif, Saad Maqsood, Adeia Saif, Maha Rehan | |
| 26 | Computer Science | BS Software Engineering | SE04 | Automated UML Diagram Generator | Adeel Ali | SDG 9 (Industry, Innovation & Infrastructure) | Flask/Streamlit, SQL, PlantUML, spaCy, NLTK, AI | Software Industry | Spring 2022 | The UML Diagram Generator project aims to develop a tool that automates the transformation of user stories into UML diagrams. These diagrams are fundamental in software development, providing a clear and structured representation of system functionalities and relationships. | Qamaruddin Qureshi (22sp-045-se), Muhammad Imran (22sp-009-se), Abdul Basit Farooqui (22sp-015-se), Muhammad Jawad Hussain (22sp-007-se) | |
| 27 | Computer Science | BS Software Engineering | SE05 | AI At Scale (Recommendation Engine) | Adeel Ali | SDG 9 / SDG 8 (Decent Work & Economic Growth) | Flask, streamlit, scikit-learn, python, transformers, docker, Algorithms: BERT + FAISS | E-commerce | Spring 2022 | “AI at Scale” is an AI-powered recommendation engine for a shopping platform that suggests the most relevant products to users. It uses Natural Language Processing (NLP) to understand and narrow down vague queries or user inputs, turning them into accurate searches that match what the user is actually looking for that suggests the most relevant products to users based on their search, preferences, and filters. | Huraira Riaz (22sp-036-se), Areeb Mohsin (22sp-054-se), Hafsa Noor Muhammad (22sp-051-se), M Zain (22sp-012-se) | |
| 28 | Computer Science | BS Software Engineering | SE06 | LungsLensAI (Thoracic Disease Classification) | Dr. Muhammad Wasim, Ms. Maham Ashraf | SDG 3 (Good Health & Well-being) | Framework & Language: Python, Django; Deep Learning: TensorFlow, Keras; Data Handling: NumPy, Pandas, SciPy, H5py; Image Processing: OpenCV; Model: DenseNet-121; Training: Google Colab; Visualization: Matplotlib, Seaborn, Grad-CAM; Tools: Excel, VS Code, Git & GitHub | Medical Health | Spring 2022 | LungsLensAI is an AI-based diagnostic system that classifies thoracic diseases such as pneumonia, atelectasis, cardiomegaly, and pleural effusion from chest X-ray images. The system uses a fine-tuned DenseNet-121 architecture with preprocessing techniques like CLAHE to enhance image quality and improve detection accuracy. Users can upload X-rays through a single interface to receive automated predictions, confidence scores, heatmap-based visual explanations, and downloadable diagnostic reports. Designed to be lightweight and efficient, the system can run on local servers, making it suitable for hospitals and clinics in resource-limited settings. | Eman Atiq (22sp-055-se), Midhat zehra (22sp-039-se), Hafsa Shahbaz (22sp-038-se), Dua Faisal (22sp-046-se) | |
| 29 | Computer Science | BS Software Engineering | SE07 | UITU Website Renovation with AI Chatbot & 3D | Adeel Ali | SDG 4 (Quality Education) / SDG 9 | Frontend: Tailwind CSS, Bootstrap, Three.js; Backend: Node.js, PHP, Python, JavaScript; Database: MySQL; AI/Chatbot: Meta’s LLaMA; Cloud: Firebase, WebSocket, Hostinger/GoDaddy; Other: GitHub | Education | Spring 2022 | This project focuses on renovating the official UITU website by integrating an AI-powered chatbot and 3D interactive elements. The goal is to enhance user experience, improve navigation, and provide real-time support for students, faculty, and visitors. | Muhammad Hassam Bin Zahid (22sp-019-se), Ruba Syed (22sp-053-se), Abhia Sultana (22sp-026-se), Hasnain Arshad (22sp-061-se) | |
| 30 | Computer Science | BS Software Engineering | SE08 | Mediconnect (Fracture Detection & Appointments) | Ms Rabia Zuberi | SDG 3 (Good Health & Well-being) | Frontend: Flutter, Dart; Backend: Node.js, Python, PHP; Database: MySQL; AI/Diagnostics: Python with Computer Vision + ML for pelvic bone fracture detection | Medical Health | Spring 2022 | MediConnect is a smart healthcare application that connects doctors and patients on a single digital platform. Designed to be simple, secure, and user-friendly, it provides smooth login and signup functionality built with Flutter. The app not only streamlines communication and appointments but also includes an advanced medical module: it can detect fractures in the pelvic bone and measure their size. This makes MediConnect a reliable digital solution for both everyday healthcare needs and specialized medical diagnostics. | Sehar Arshad (22sp-062-se), Hafiza Aisha Khan (22sp-063-se), Hamza Khan (22sp-029-se), M Umer Farooq (22sp-014-se) | |
| 31 | Computer Science | BS Software Engineering | SE09 | CodeBox (Collaboration Platform) | Dr Adnan Ahmed Siddique | SDG 9 (Industry, Innovation & Infrastructure) | GitLab API, Socket.io, OpenAI API, WebRTC, Cloud Storage (local), NodeJs, React, Express | Software Industry | Spring 2022 | CodeBox is a web-based platform for project management and collaboration. | Ikram Ullah Ghouri (22sp-042-CS), Anas zubair (22sp-055-CS), Sheikh Altamash (22sp-056-SE), Syed ashab mavia (22sp-003-se) | |
| 32 | Computer Science | BS Software Engineering | SE10 | Sketchify Code (Hand-drawn UI to Code) | Dr Adnan Ahmed Siddique | SDG 9 (Industry, Innovation & Infrastructure) | Frontend: Html, Css, javascript, react.js, Tailwind CSS, Monaco Editor; Backend: Python, OpenCV/PIL, Tensorflow/PyTorch, Transformer, MangoDB/Firebase; AI Models: CNN, YOLOv5, Canny; LLM: GPT based model; APIs: Github, postman, firebase | Software Industry | Spring 2022 | It is a web-based system powered by Large Language Models (LLMs) that converts hand-drawn UI sketches into functional front-end code by detecting UI elements. | Maheen Muntajib (22SP-048-SE), Sidra Mohsin (22SP-058-SE), Munib Ahmad (22sp-021-cs) | |
| 33 | Computer Science | BS Computer Science | CS01 | AI Enhanced Educational Content Generator and Assessor | Talha Ahmed | SDG 4 | Javascript(React), Python(Flask), AI | Education | Fall 2022 | This project is about creating an AI-powered web application that helps teachers reduce their workload by automating key educational tasks. The main goal is to make content creation and assessment faster and simpler for educators, so they can focus more on teaching rather than manual, repetitive work. The system analyzes uploaded PDF documents using NLP and automatically converts them into clean, well-structured slide presentations. It also generates dynamic question papers directly from the PDF content, saving teachers time in exam preparation. In addition, the application can automatically grade answer sheets and produce clear feedback reports, helping teachers complete assessments more efficiently. The project includes an easy-to-use web interface, secure authentication, database integration, and smooth communication between the frontend, backend. In short, this project provides an AI-enhanced solution designed to support teachers by automating slide creation, question generation, and grading — making educational tasks faster, smarter, and far more efficient. | Umer Abdul Rehman (21B-232-CS), Hafiz Muhammad Harmain (21B-231-CS), Ahmer Khan (21B-079-SE), Sobia Yameen (21B-201-SE) | |
| 34 | Computer Science | BS Computer Science | CS02 | AI Skin Disease Detection System | Engr. Naveed ul Haq | SDG 3 | Python, OpenCV, Cameras, PyTorch, AI and Computer Vision | Medical Health | Fall 2022 | This project centers on developing an AI-Based Skin Disease Detection System that helps identify both common and serious skin conditions through image analysis. Skin diseases remain a major public health issue, especially in developing countries like Pakistan, where limited access to dermatologists and diagnostic facilities often leads to delayed or inaccurate treatment. The goal of this project is to create an intelligent diagnostic tool that can accurately classify various skin diseases using artificial intelligence and image processing techniques. The system leverages Convolutional Neural Networks (CNNs) and transfer learning to analyze dermatological images and detect conditions such as acne, eczema, and melanoma. | SYED SUHAIB ULLAH (21B-169-CS), ARHAM ATHER (21B-069-CS), ABDUL SAMAD QURESHI (21B-123-CS), MOHIB HASSAN (21B-177-SE), AFFAN ALI (21B-230-SE) | |
| 35 | Computer Science | BS Software Engineering | SE01 | MAKKHIMETER 2.0 (Drosophila Research) | Dr. Muhammad Wasim | SDG 3 (Good Health & Well-being) / SDG 9 | Python (Django), AI, ML, Computer Vision, Bio Research | Medical | Spring 2021 | MAKKHIMETER 2.0 offers modern modules such as Image Colorization, Eye color detection, body color detection, and Gender Detection to researchers to speed up their research work on Drosophila Melanogaster. All the modules have been carefully created with the intention of enhancing the efficiency and accuracy of experimental analysis enabling the researchers to advance more in studying the genetic and behavioral aspects of this model organism. Our platform is to provide researchers with comprehensive features to elevate their studies in Drosophila Melanogaster genetics and biology, regardless of whether they are investigating phenotypic changes or genetic mutations. | Syed Moosa Raza Rizvi (21A-002-SE), Muhammad Hassan (21A-008-SE), Syeda Neha Zafar (21A-017-SE), Zahir Sheikh (21A-023-SE) | |
| 36 | Computer Science | BS Software Engineering | SE02 | Data Cleaning for Large Language Model | Dr. Farhan Ahmed Karim | SDG 9 (Industry, Innovation & Infrastructure) | Python, AI, NLP, LLM | Finance, Business | Spring 2021 | This project introduces an automated data preprocessing platform for Large Language Model (LLM) training, tackling issues like noise, redundancy, and irrelevant content in multi-source datasets. Featuring secure authentication, a user-friendly dashboard, and seven specialized cleaning pipelines—such as URL filtering, text extraction, and deduplication—the system ensures high-quality, reliable data. Real-time progress indicators and visual comparisons enhance transparency, delivering refined datasets for optimal Generative AI performance. | Sawera Fazal (21A-026-SE), Tayyaba Anwer (21A-022-SE), Nida Fatima (21A-028-SE) | |
| 37 | Computer Science | BS Software Engineering | SE03 | Human Resource Management System | Zulfiqar | SDG 8 (Decent Work & Economic Growth) | MERN, React Native | Business | Spring 2021 | The Human Resource Management (HRM) System is an integrated software solution designed to streamline and automate an organization’s HR processes. It supports end-to-end employee management, including recruitment, onboarding, payroll, benefits, performance tracking, attendance, and resignation handling. With employee self-service features and robust reporting tools, the system enhances HR efficiency, improves employee experience, and enables data-driven decision-making through a user-friendly and reliable interface. In addition, a dedicated mobile application was developed to keep employees informed in real time—especially by sending notifications for their upcoming interviews—further improving accessibility and engagement within the HR workflow. | Arham Ahmed (20B-001-SE), Muhammad Talha Iqbal (20B-002-SE), Muhammad Danish Khan (20B-042-SE), Daniyal Muhammad (20B-043-SE) | |
| 38 | Computer Science | BS Software Engineering | SE04 | HIREXCEL (Recruitment & Assessment Platform) | Ms. Maham Ashraf | SDG 8 (Decent Work & Economic Growth) / SDG 4 | Python (Django), AI, Talent Acquisition | Education | Spring 2021 | HIREXCEL revolutionizes the recruitment landscape by leveraging data-driven insights and Knowledge, Skills, and quality-based assessments to streamline the hiring process for both recruiters and job seekers. This empowers data-driven decision-making, ensuring a more objective and efficient talent acquisition experience. HIREXCEL features engaging questionnaires as part of its comprehensive assessment collection to evaluate candidates’ cognitive abilities, personality traits, and job-specific technical aptitudes. Utilizing innovative and latest technologies, HIREXCEL analyzes assessment data, including insights from Big Five and DISC personality tests, to generate automated scoring and initial job seekers’ performance results. The platform seamlessly integrates with the job applications, allowing job seekers to access pre-interview assessments directly through job postings, creating a smooth and efficient workflow. HIREXCEL goes beyond individual evaluations by offering assessments designed to measure a job seeker potential fit within a team dynamic. It prioritizes the job seeker experience by providing personalized feedback and potential learning paths based on assessment results. For recruiters and hiring managers, HIREXCEL reduces hiring time and costs while enhancing the quality of job seekers’ selection through objective data-driven insights about potential hires while empowering job seekers to assess their weaknesses and strengths. | Mehmood Sheikh (21A-001-SE), Muhammad Shazim (21A-004-SE), Zainab Mansoor (21A-025-SE), Asma Rafiq (20B-040-SE) | |
| 39 | Computer Science | BS Software Engineering | SE05 | Image Encryption using Butterfly Keychain | Dr. Muhammad Wasim | SDG 9 (Industry, Innovation & Infrastructure) | Python (Django), DES, IFFT | Business, Medical | Spring 2021 | The project introduces a novel technique, the “Butterfly Technique,” to establish such a secure platform for the exchange of visual data, as prior implementations have focused on audio and text data, we are focusing on Image data. The name “Butterfly” given to this technique is due to the structure the algorithm creates after performing numerous iterations, which resemble butterfly wings. The proposed work is a dual-mode framework consisting of two modules, Encryption and Decryption, also encompassing the Data Encryption Standard (DES) mechanism for key generation followed by the Fast Fourier Transform or Butterfly Technique for grayscale image data encryption. The Data Encryption Standard (DES) mechanism will be applied for key generation to generate a strong key for encryption purposes to prevent unauthorized attacks. Further, the Inverse Fast Fourier Transform (IFFT) will be applied on the image utilizing the same key generated while encrypting an image which results in full restoration of the original image. This novel technique follows a systematic approach to information security, using signal processing algorithms to protect sensitive information and provide a secure channel for individuals and organizations to improve data exchange. | Noor ul Aain Hanif (21A-007-SE), Mashaim Javaid (21A-027-SE), Fatima Shaikh (21A-029-SE), Areeb Iqbal (21A-031-SE) | |
| 40 | Computer Science | BS Software Engineering | SE06 | Query Craft (NL to SQL) | Ms. Shiza Hassan | SDG 9 (Industry, Innovation & Infrastructure) | Python (PyTorch, TensorFlow), Reactjs, AI in Database Management | Software Industry | Spring 2021 | QueryCraft is an AI powered tool that converts natural language into accurate SQL queries, making database interactions simple for both technical and non-technical users. It helps users generate, optimize, and debug SQL queries instantly, reducing manual effort and improving productivity. With intelligent NLP models, QueryCraft turns everyday language into actionable database commands fast, precise, and userfriendly. | Taqi Mirza (20B-117-SE), Muhammad Shaheer Zaman Khan (21A-003-SE), Muhammad Huzaifa (21A-013-SE), Sherhyar Muhammad (19B-061-SE) | |
| 41 | Computer Science | BS Software Engineering | SE01 | CodeNova AI (AI Coding Assistant) | Ms. Maham Ashraf | SDG 9 (Industry, Innovation & Infrastructure) | React, Electron, Node.js, Python (FastAPI), Docker, Git, AI | Software Industry | Fall 2022 | This project, CodeNova AI, is a smart desktop application that helps developers write, refactor, and manage code using artificial intelligence. It allows users to describe what they want in simple natural language, and the system automatically generates clean, functional code. The application also detects issues in existing code, suggests improvements, and lets users preview changes before applying them. With built-in collaboration and version control features, CodeNova AI streamlines the entire development process. In short, it’s an AI-powered coding assistant designed to make programming faster, smarter, and more efficient. | Mahad Ahmed Abbasi (22FA-040-SE), Hamza Nayyer (22FA-036-SE), Mehma Maqbool (22FA-051-SE) | |
| 42 | Computer Science | BS Software Engineering | SE02 | ClimaX-AI (Greenhouse Gas Prediction) | Ms. Maham Ashraf | SDG 13 (Climate Action) | PyTorch, SHAP, LIME, Pandas, AWS/Firebase, Plotly, AI | Environmental Sciences | Fall 2022 | This project is about a new web app called ClimaX-AI that uses advanced artificial intelligence to predict greenhouse gas emissions. The main goal is to make climate data clear and understandable for everyone, especially policymakers. The project works by first collecting high-quality climate data from reliable sources. It then uses powerful AI models to analyze past trends and forecast future emission levels. A key feature is its use of Explainable AI, which helps users understand why the model makes a specific prediction, moving away from complex “black box” systems. The core of the project is a user-friendly dashboard where all these forecasts and their explanations are shown through easy-to-understand charts and graphs. This allows users to see not just what will happen, but also the reasons behind it, helping them make better decisions for climate action. In short, ClimaX-AI offers a new, transparent way to track and understand emissions, making vital climate insights accessible to all. | Muhammad Khubaib Raza (22FA-001-SE), Syed Muhammad Umar (22FA-018-SE), Syed Muhammad Mehdi (22FA-019-SE), Hashir Ahmed (22FA-069-SE) | |
| 43 | Computer Science | BS Software Engineering | SE03 | Teach Assist (AI for Teachers) | Dr. Lubaid Ahmed | SDG 4 (Quality Education) | Tensor flow, fire base, rule based nlp | Education | Fall 2022 | Teach Assist is an AI-powered web application designed to support teachers in managing academic tasks efficiently. It helps automate quiz generation, lecture summarization, and student query handling while supporting Outcome-Based Education (OBE). The system intelligently maps Course Learning Outcomes (CLOs) with teaching content and assessments using keyword detection and NLP techniques. | UBAIDULLAH (22FA-011-SE), NABEEHA AYAZ (22FA-025-SE), ALYANUDDIN (22FA-053-SE), OMAIMA IRFAN (22FA-060-SE) | |
| 44 | Computer Science | BS Software Engineering | SE04 | Project Management through Agentic AI | Zeeshan Saleem Khan | SDG 9 (Industry, Innovation & Infrastructure) | Taiga, Python, Django, OpenAI, LangChain, React, PostgreSQL, APScheduler, Chart.js, Docker, CI/CD, AGENTIC SOFTWARE PROJECT MANAGEMENT | Software Industry | Fall 2022 | This project develops an AI-enhanced extension for an open-source Scrum tool to streamline workflows for small teams. It uses AI to analyze business reports and product backlogs, verifying completeness and offering advisory suggestions on priorities and risks, while ensuring collaborative task selection by the team, product owner, and Scrum master. Tickets are auto-generated upon user story selection, with a desktop agent monitoring developer activity to track time and capture IDE snapshots, posting updates to the tool’s boards for real-time progress visibility. Key features include burndown charts, task dependency graphs, deadline alerts, and performance dashboards, promoting efficient and adaptive Scrum practices. | SYED MEERAN KHAN (22FA-049-SE), SIDQIAH JESSICA JOHN (22FA-030-SE), WOOSQA SOHAIL (22FA-042-SE), SYEDA YUSRA ARSHAD (22FA-032-SE) | |
| 45 | Computer Science | BS Software Engineering | SE05 | Physiotherapy Guidance System | Dr. Muhammad Wasim, dr tariq (physiotherapist) | SDG 3 (Good Health & Well-being) | Python, React, Next.js, MediaPipe, TensorFlow MoveNet, OpenCV, gTTS / pyttsx3, (AI & Computer Vision) | Medical, Health | Fall 2022 | A web-based physiotherapy guidance system that uses computer vision to detect incorrect postures during exercises and provides real-time feedback through audio alerts to help patients perform physiotherapy safely at home. | Roha Pathan (22fa-009-se), Laiba Laeeq (22fa-047-se), Manail Ghouri (22fa-059-se) | |
| 46 | Computer Science | BS Software Engineering | SE06 | PairPilot: AI Coding Companion | Ms Marvi jokhio / Engr. Jawad Ahmed Bhutta | SDG 9 (Industry, Innovation & Infrastructure) | Python, PyQt5, OpenAI API, Flask, SQLite, TensorFlow, AI | Software Industry | Fall 2022 | Pair Pilot is an AI-powered coding companion integrated into a modern IDE environment that assists developers in writing, debugging, and optimizing code in real time. It supports multiple AI models (like GPT, Gemini, and Grok) to provide comparative suggestions, design recommendations, and architectural guidance. The tool allows developers to write questions, review AI responses, and generate or refine code within a unified workspace — making coding faster, smarter, and more collaborative. | Rameez Ahmed (22FA-014-SE), Syed Mannan Ali Ajmi (22FA-007-SE), Hamna Mujahid (22FA-017-SE), Ehsan Afzal (22FA-004-SE) | |
| 47 | Computer Science | BS Software Engineering | SE07 | ProctorVision (AI Automated Proctoring) | Dr. Muhammad Wasim | SDG 4 (Quality Education) | Python, OpenCV, DeepFace, YOLO, Flask, CCTV (RTSP), CNN Models, Artificial Intelligence (AI) | Education | Fall 2022 | ProctorVision is an AI-based automated proctoring system that uses CCTV input to monitor students during exams without a human invigilator. It detects cheating behaviors such as talking, phone usage and identifying unusual movement patterns that indicate suspicious activity. A separate attendance system based on facial recognition automatically marks student attendance before exams. | Nabiha Fatima (22Fa-008-Se), Abdul Raahim Sheikh (22Fa-039-Se), Fatima Amin Siddiqui (22Fa-046-Se), Ahmed Muarij Siddiqui (22Fa-062-Se) | |
| 48 | Computer Science | BS Software Engineering | SE08 | Web Based RL Playground for Custom 3D Environment | Farhat Hasnain Naqvi | SDG 4 (Quality Education) / SDG 9 | Three.js, Cannon.js, Node Graphs, PyBullet, Stable-baselines3, FastAPI, Websockets, Webhooks, REST API, AI (Reinforcement Learning) | Education | Fall 2022 | Our project is a web-based Reinforcement Learning (RL) playground that enables users to create custom 3D environments through an intuitive drag-and-drop interface. Users can design their environments by selecting elements from a built-in library that includes both agents (such as bots, droids, cars, and humans each with distinct action sets) and objects (like lights and obstacles) that are fully interactable with the agents. A visual scripting engine, inspired by Scratch and node-based graph systems, allows users to define the logical flow and behavior of their environment. The user-defined node graph is automatically converted into a JSON payload, encapsulating information about the environment’s configuration, agents, and objects. Users can also choose from popular RL algorithms, such as PPO and Q-Learning, to train their agents. The generated JSON payload is sent to a Python backend, where a physics engine (PyBullet) interprets it, constructs the environment, and integrates with RL frameworks like Stable Baselines to initiate the training process in the cloud. Once the training is complete, users receive a notification and can simulate the trained model directly in the browser. The simulation is rendered using Three.js for 3D visualization and Cannon.js for real-time physics handling. | Ezhan Javed (22FA-023-SE), Muhammad Suhaib (22FA-055-SE), Usman (22FA-003-SE), Sharjeel (22FA-068-SE) | |
| 49 | Computer Science | BS Software Engineering | SE09 | NUTRIFIT AI (Nutrition & Fitness Coach) | Farhat Hasnain Naqvi | SDG 3 (Good Health & Well-being) | Flutter, Python (Machine Learning), TensorFlow, flask API, MediaPipe, Firebase, Artificial Intelligence (AI) & Health Tech | Health | Fall 2022 | NutriFit AI is an intelligent mobile application that acts as a personal AI-based nutrition and fitness coach. It provides personalized 3-time meal and workout plans based on each user’s health data, goals, and medical conditions. The system automatically calculates BMI, BMR, and TDEE, identifies weight status, and recommends safe daily calorie targets. It creates customized meal plans (breakfast, lunch, dinner) with complete nutrition breakdown — proteins, carbohydrates, fats, vitamins, and minerals — tailored to conditions like diabetes, hypertension, and allergies. The fitness module uses AI pose estimation (MediaPipe) to monitor user posture during exercises and provides real-time feedback to ensure proper form and safety. The app also handles cheat days — users can upload images of meals they eat, and the system analyzes calorie intake to generate compensation meal and workout plans. NutriFit AI continuously adapts diet and workout recommendations every 15 days based on user progress and health tracking. It includes a smart chatbot assistant for instant guidance, motivational alerts, streaks, and badges to boost user engagement. A central dashboard visualizes nutrition intake, workout performance, and progress trends for a holistic fitness journey. | Summiya Hania Jafri (22FA-034-SE), Areesha Feroz (22FA-057-SE), Hamza Mujeeb (22FA-040-CS) | |
| 50 | Computer Science | BS Software Engineering | SE10 | IoT Device Security Monitoring & Threat Detection | Muhammad Timur | SDG 9 (Industry, Innovation & Infrastructure) / SDG 11 | Hardware: Raspberry Pi 4 / 3B+, PoE adapters / network TAPs, USB-to-Ethernet NICs; Software(s): Zeek / Suricata, FastAPI / Flask, PostgreSQL / SQLite, MQTT / Redis / Kafka; Libraries: Scikit-learn, TensorFlow, PyTorch, Pandas, NumPy, pyshark, scapy, JWT, TLS, OpenSSL; AI, Computer Network and Network Security | Network | Fall 2022 | Despite the availability of many IDS tools, most do not cater to the low-power, protocol-diverse, and bandwidth-sensitive nature of IoT devices. The gap lies in the lack of unified platforms that can perform device fingerprinting, real-time threat scoring, auto-mitigation, and forensic logging simultaneously—especially using edge-level hardware. This project addresses that gap by designing a system that uses Raspberry Pi–based hardware for passive data collection and server-based machine learning for real-time threat detection and response. It supports dynamic deployment, offline fallback, CVE-based risk scoring, and integration with compliance systems. Key features include passive traffic monitoring, deep packet inspection (DPI), behavioral anomaly detection, auto-quarantine actions, forensic timelines, and SOAR-based automation for threat response. | Muhammad Ahsan (22FA-045-SE), Rizwan Aleem Tahha (22FA-013-SE), Moiz Ahmed (22FA-065-SE), Sam Asad (22FA-070-SE) | |
| 51 | Computer Science | BS Software Engineering | SE11 | Automated Football Match Analysis System | Engr. Naveed ul Haq | SDG 3 (Good Health & Well-being) / SDG 9 | Python, OpenCV, Yolov8, scikit-learn, Matplotlib, React, Pandas, numpy, PyTorch / TensorFlow, AI (Artificial Intelligence) | Sports | Fall 2022 | The Automated Football Match Analysis System using Deep Learning and Computer Vision aims to make football match analysis faster, smarter, and more accessible. It automatically processes match videos to detect and track players and the ball, identify teams, and map movements across the pitch. By analyzing player positioning, team formations, movement intensity, and key events, the system generates clear visual and statistical insights into how teams play. The main goal is to reduce the time, cost, and subjectivity of traditional manual analysis used by coaches and analysts. This project helps coaches evaluate tactics, players understand their performance, and analysts or researchers study match dynamics objectively. It provides outputs like heatmaps, formation maps, event summaries, and performance reports — offering a low-cost, automated alternative to professional analytics tools such as Hudl or TRACAB. Ultimately, it bridges the gap between advanced AI technology and practical football decision-making. | Usaib Ahmed (22FA-038-SE), Ameer Mavia (22FA-058-SE), M Huzaifa (22FA-067-SE), Aakash Ali (22FA-037-SE) | |
| 52 | Computer Science | BS Software Engineering | SE12 | Intelligently Adaptive CACAO Playbooks | Engr. Jawad Ahmed Bhutta | SDG 9 (Industry, Innovation & Infrastructure) | Wazuh, Shuffle, PFSense, Cyber Security | Network | Fall 2022 | This project will build playbooks that will be creating rules to tackle attacks that are coming towards the system. The playbooks will be getting the information from the SIEM and the playbooks will be integrated in the SOAR platform. The playbooks will be executed and altered according to the situation that is faced by the system. The SIEM used in the system will be Wazuh, the SOAR platform will be Shuffle and firewall platform will be PFSense. | Syed Abdul Munim UL Hasan (22FA-063-SE), Hamza Ahmed Siddiqui (22FA-043-SE), Huzaifa Shahid (22FA-044-SE), Syed Ali Raza (22FA-066-SE) | |
| 53 | Computer Science | BS Software Engineering (NED) | SE01 | CodeMate (Logical Error Assistance Tool) | Talha Ahmed | SDG 4 (Quality Education) / SDG 9 | Flask, Python AST (Abstract Syntax Tree) Parsing | Software Industry | Fall 2022 | CodeMate is an intelligent code-analysis tool designed to help programmers identify syntax errors and receive logical improvement suggestions. It does not detect logical errors directly (because logical intent cannot be known by a machine), but instead uses pattern recognition, AST parsing, and ML-based suggestion models to highlight potential improvements in loops, conditions, and code structure. The system provides syntax error detection, structural suggestions for if-else and loops, and educational guidance for beginner programmers to write better code. | Wajahat Siddiqui (21B-087-SE), Syed Ali Haider (21B-143-SE), Syed Ali Askari (21B-144-SE), Rahima Jawwad (21B-044-SE), Danish Ali Zardari (21B-050-SE) | |
| 54 | Computer Science | BS Software Engineering (NED) | SE02 | AI-Powered Image to Website Conversion Tool | Muhammad Timur | SDG 9 (Industry, Innovation & Infrastructure) | TensorFlow, PyTorch, OpenCV, YOLO/Faster R-CNN, Tesseract/EasyOCR, React.js, TailwindCSS, Flask/Django, Docker, AWS/GCP, AI / Computer Vision / Web Automation | Software Industry | Fall 2022 | This project generates a complete, clean, and responsive website automatically by taking a URL as input. The system fetches the webpage, extracts its structure, content, styles, images, and scripts using intelligent web scraping and LLM-based analysis. It then regenerates the website’s layout in a modern frontend framework using optimized and reusable HTML, CSS, and JavaScript code. The tool can also clean outdated code, remove unnecessary scripts, modernize UI components, and produce a fully functional, editable version of the website. This solution helps developers, designers, and businesses quickly clone, redesign, or analyze websites in minutes—saving time, cost, and manual effort. | Maaz Akhter (21B-215-SE), Bilal Malick (21B-051-SE), Rabi Malik (21B-204-SE), S.M. Ahsaan (21B-093-CS), Bilal Khan (21B-131-CS) | |
| 55 | Computer Science | BS Computer Science | CS01 | TradePilot (Automated Trading Bot Generator) | Ms. Laiba Mughal | SDG 8 (Decent Work & Economic Growth) / SDG 9 | MQL, Python | Finance | Fall 2022 | Retail traders and non-technical investors often struggle to design, test, and deploy automated trading strategies. Most platforms demand technical knowledge, such as programming, market indicators, and broker APIs, making them inaccessible to the average user. There is currently no system that allows traders to create bots using simple natural language based on their risk level, preferred assets, and trading goals. TradePilot solves this by introducing an intelligent, intent-driven bot generation and deployment platform. This will allow users to generate fully functional trading bots based on a simple natural language prompt. By extracting trading intent such as risk level, asset, frequency, and strategy type the system generates tailored logic, backtests it, and connects to real broker accounts (e.g., Binance or Alpaca) for deployment. Users can monitor live trades via a dashboard and receive alerts. Optional modules include news-based trading logic and AI self-tuning of strategies. | Syed Qasim Hasan Shah (22FA-071-CS), Abdul Ahad (22FA-002-CS), Hanzala Khan (22FA-009-CS), Talha Naseem (22FA-046-CS) | |
| 56 | Computer Science | BS Computer Science | CS02 | Classroom & Shopping Cart Trash/Safety Monitoring | Ms. Shiza Hassan | SDG 11 (Sustainable Cities & Communities) / SDG 3 | Python, OpenCV, YOLOv8/YOLOv11, AI, Computer Vision | E-commerce, Business | Fall 2022 | This project is an AI and computer vision–based smart surveillance system designed to enhance safety in classrooms and public areas like malls. It detects threats and unsafe activities such as trash disposal, smoking, eating, violence, and weapon presence in real time using deep learning models. | Syed Muhammad Shahzim (22FA-038-CS), Fashi Yar Khan (22FA-053-CS), Ali Asad (22FA-070-CS), Ayesha Asghar (22SP-053-CS) | |
| 57 | Computer Science | BS Computer Science | CS03 | AI Grading for Handwritten Exams with OBE Rubric | Dr. Farhan Ahmed Karim | SDG 4 (Quality Education) | Python, PyTorch, OCR Model, Flutter, Cloud Storage, AI, CV, NLP | Education | Fall 2022 | This project aims to automate the grading of handwritten examination papers using AI. Students’ answer sheets are scanned and uploaded to cloud, where the system extracts handwritten text through OCR models and evaluates it using transformer-based NLP models. Instead of keyword matching, it understands the meaning of answers, ensuring fair and consistent grading. The system then generates scores and reports through a simple web dashboard. | Zaeem Syed (22FA-066-CS), M. Asim Amir (22FA-062-CS), M. Azeem (22FA-044-CS), M. Salar (22SP-011-CS) | |
| 58 | Computer Science | BS Computer Science | CS04 | NEUROSPARK (Early Dementia Detection & Therapy) | Ms Rabia Zuberi | SDG 3 (Good Health & Well-being) | React / Next.js, Python (FastAPI / Flask), MongoDB / PostgreSQL, Librosa, PyTorch, Transformers (BERT), SHAP, NumPy, Pandas, Chart.js, Artificial Intelligence (AI) — Speech Processing, Natural Language Processing (NLP), and Healthcare Informatics | Medical Health | Fall 2022 | NeuroSpark is an AI-powered web platform designed for early dementia detection and cognitive enhancement using speech and language analysis. The system analyzes users’ voice recordings to identify cognitive decline markers, provides explainable AI-based results, and offers personalized therapy through speech exercises, quizzes, and family-based interactions. It includes weekly progress tracking, medication reminders, and a clinician dashboard for monitoring and stage assessment — combining detection, treatment, and cognitive support in one accessible platform. | Aqsa Khan (22FA-031-CS), Muhammad Zain Ul Abdin (22FA-060-CS), Asma Asim (22FA-069-CS), Mahrukh Qazi (22FA-047-CS) | |
| 59 | Computer Science | BS Computer Science | CS05 | 3D Model Generator Using VR Simulverse | Ms. Shiza Hassan | SDG 9 (Industry, Innovation & Infrastructure) | Python, OpenCV, Cameras, PyTorch, AI and Computer Vision | Business | Fall 2022 | This project is about creating a smart system that can generate 3D models of real-world objects using image processing techniques. The main goal is to make 3D model creation easier, faster, and more accurate by capturing images from multiple angles and automatically converting them into realistic 3D models. The setup includes a controlled box with multiple cameras and proper lighting to capture clear images of an object placed inside. These 2D images are processed using computer vision and AI algorithms to reconstruct the object’s 3D shape, texture, and dimensions. In short, this project provides an efficient and automated solution for generating 3D models, combining the power of AI, and computer vision to make 3D visualization and simulation more accessible. | Fahad Ahmed Khan (22FA-014-CS), Faraz Ismail (22FA-039-CS), Hamna Waseem (22FA-032-CS), Maria Saleem (22FA-068-CS) | |
| 60 | Computer Science | BS Computer Science | CS06 | PriceXpert (Grocery Price Comparison Advisor) | Dr Adnan Ahmed Siddique | SDG 1 (No Poverty) / SDG 12 (Responsible Consumption) | Frontend: Flutter; Backend: Flask / FastAPI; Database: SQLite / Firebase; Web Scraping: BeautifulSoup, Selenium, Requests; AI & NLP: Hugging Face Transformers, Scikit-learn; Artificial Intelligence, E-commerce, Data Analytics | E-commerce | Fall 2022 | A smart, AI-powered grocery advisory system that collects product data from multiple supermarket websites, compares prices and offers based on user budget and location, and recommends the most cost-effective shopping option. The system features a chatbot-style interface with Roman Urdu and English support, providing users with an intelligent, data-driven shopping experience. | Muhammad Saif Shakil (22FA-065-CS), Maham Shahzad (22FA-025-CS), Syed Azam Ali (22FA-059-CS), Muhammad Saad (22FA-052-CS) | |
| 61 | Computer Science | BS Computer Science | CS07 | SOCA – Secure OS Command Agent | Zeeshan Saleem Khan | SDG 9 (Industry, Innovation & Infrastructure) | Python, Bash/Shell Scripting, FastAPI, SQLite / JSON / YAML, Deepseek-7B-Chat-4Bit, Electron.js / Tauri, Artificial Intelligence & System Administration | Software Industry | Fall 2022 | SOCA aims to build an AI Assistant for Linux which will allow for intuitive, secure, and automated system management through natural language interaction. It simplifies complex administrative tasks such as user management, file operations, environment configuration, and log analysis by translating plain English commands into safe, validated system actions. The system also extends its capabilities to containerization and orchestration, enabling automated Docker and Kubernetes deployments. Designed with a focus on explainability and safety, SOCA acts as both a management tool and a learning companion for system administrators. | Umar Ayaz Bader Shahabi (22FA-008-CS), Sania Tehseen (22FA-018-CS), Anuf Jabeen (22FA-019-CS), Zeeshan Ali Khan (22FA-026-CS) | |
| 62 | Computer Science | BS Computer Science | CS09 | Crypto/Commodities/Forex Portfolio Suggestor | Mirza Farrukh Waheed Baig | SDG 8 (Decent Work & Economic Growth) | Python, Flask/Django, React.js/Next.js, Firebase (optional) | Finance | Fall 2022 | This project builds a unified platform for tracking and analyzing investments across multiple asset classes, cryptocurrencies, forex, and commodities. It enables users to manage portfolios, monitor real-time values, and receive AI-based suggestions for improving asset allocation. The system uses free financial APIs to fetch live market data and update performance automatically. Key modules include portfolio tracking, profit/loss analysis, risk assessment, and diversification recommendations. With interactive charts and a clean web interface, the platform simplifies multi-asset management and provides actionable insights through a FinTech-driven approach. | Yasir Jamal (22FA-015-CS), Muhammad Abdullah (22FA-021-CS), Veesha Fatima (22FA-055-CS), Zaid Qamar (22FA-033-CS) | |
| 63 | Computer Science | BS Computer Science | CS10 | Mindsteps (ADHD Focus App for Children) | Mirza Farrukh Waheed Baig | SDG 3 (Good Health & Well-being) / SDG 4 | Flutter, Firebase, Unity, Python, Figma, AI/Health | Medical, Health, Education | Fall 2022 | MindSteps is a bilingual (Urdu and English) mobile application designed to help children with ADHD enhance their focus and attention span through engaging, research-backed cognitive games. The app integrates adaptive AI logic that personalizes difficulty based on the player’s performance — analyzing response time, accuracy, and consistency to adjust game levels in real time. Unlike existing tools, MindSteps is culturally tailored and accessible, aiming to raise ADHD awareness in Pakistan while providing a non-prescriptive, gamified support platform. The project aligns with SDG 3 (Good Health and Well-being) and SDG 4 (Quality Education) by promoting inclusive digital mental health solutions for children. | Syeda Zuha Sajjad (22FA-051-CS), Maarij Khan (22FA-056-CS), Atika Tufail (22FA-064-CS) | |
| 64 | Computer Science | BS Computer Science | CS11 | StrategaAI (AI E-commerce Pricing Platform) | Dr. Lubaid Ahmed | SDG 8 (Decent Work & Economic Growth) / SDG 9 | Frontend: Next.js (TypeScript) + TailwindCSS + Recharts; Visualization: Power BI & Streamlit; Backend/API: FastAPI; Web Scraping: Playwright + BeautifulSoup; Model Training: Python (scikit-learn + XGBoost); NLP Processing: spaCy + Transformers; Agent Framework: LangGraph + CrewAI; Data Pipeline: Prefect; Storage/Database: Supabase (PostgreSQL + Realtime + Auth) + Redis; Hosting/Deployment: Vercel + Render + Supabase Cloud; business intelligence, AI, Data analytics | Finance, E-commerce | Fall 2022 | This project introduces an AI-powered, Model and Control-Based (MCB) platform that automates e-commerce pricing and strategic decision-making through synchronized intelligent agents. The system scrapes and analyzes real-time product data from multiple supplier and retail sources to identify wholesale ranges, profit margins, and market trends. It leverages Natural Language Processing (NLP) to interpret unstructured data such as product descriptions, customer reviews, and competitor marketing content, enhancing analytical depth and decision accuracy. Specialized agents — including Scraper, Competitor, Finance & Budgeting, Marketing & Strategy, and Decision Control Agents — collaborate to generate optimized buying, selling, and marketing strategies. All insights are visualized through interactive dashboards enabling businesses to make data-driven, intelligent, and adaptive e-commerce decisions. | Mohummad Yousha (22FA-013-CS), Ayesha Iftikhar (22FA-010-CS), Syed Salik (22FA-027-CS), Noor-ul-huda Siddiqui (22FA-001-CS) | |
| 65 | Computer Science | BS Computer Science | CS12 | Photo-Realistic Virtual Tourism Platform (UE4-Nerf) | Dr. Muhammad Wasim | SDG 4 (Quality Education) / SDG 9 | Python, Colmap, Unreal Engine, Github, AI / Neural Radiance Field | Education | Fall 2022 | Despite global advances in neural rendering, universities in Pakistan, including UIT, lack a real-time, immersive visualization system using AI. Current virtual campus tools are limited and do not provide interactive, photorealistic experiences for students or visitors. This project addresses this gap by using UE4-NeRF, an advanced real-time NeRF-based rendering system. The platform will support loading of drone or phone-captured images of UIT University, reconstructing them into a photorealistic, explorable 3D environment. | Muhammad Taha (22FA-050-CS), Muhammad Yahya (22FA-041-CS), Syed Daniyal Rizvi (22FA-048-CS), Syed Ali Zaidi (22FA-035-CS) | |
| 66 | Computer Science | BS Computer Science | CS13 | ForestEdge (Forest Risk Monitoring) | Dr. Farhan Ahmed Karim | SDG 15 (Life on Land) / SDG 13 (Climate Action) | Embedded C/C++, RISC-V based edge processor (with AI acceleration), TinyML (TensorFlow Lite Micro), Environmental Sensors (Temp, RH, CO, Acoustic), System Simulation Tools, Edge AI, Internet of Things (IoT), Environmental Monitoring, Embedded System | Environmental Science | Fall 2022 | This project develops a decentralized forest monitoring system using edge AI and IoT to detect critical environmental risks such as wildfires, illegal logging, and disease outbreaks in real-time. By deploying intelligent sensor-equipped edge devices with quantized LLMs on RISC-V processor, the system performs local analysis and decision-making, transmitting only urgent alerts to a central server. This minimizes latency, reduces bandwidth, and ensures autonomous forest health monitoring, even in remote areas with poor connectivity. | Furqan Ahmed (22FA-006-CS), Muhammad Shahzaib (22FA-003-CS), Rahim Azhar (22FA-007-CS), Muhammad Romaan (22FA-034-CS) | |
| 67 | Computer Science | BS Computer Science | CS01 | BUSINESS MANAGEMENT TOOL MAKER | Engr. Fauzan Saeed | Assistant Profesor | Fall 2021 | The Business Management Tool Maker is a platform designed to help small and medium-sized businesses (SMBs) streamline their operations without needing technical expertise. The platform supports features like barcode scanning through the camera, CSV import, Excel file generation, PDF file generation, and a dashboard that visualizes key metrics such as sales and revenue trends through interactive graphs.By leveraging real-time analytics and automated reporting, the platform enables SMBs to optimize workflows and make data-driven decisions and ensures accessibility and reliability. The major conclusion drawn from this work is that the project successfully delivers an accessible, cost-effective solution for SMBs, offering them the flexibility and functionality necessary to streamline their operations and compete more effectively with larger enterprises. The platform’s success lies in its ability to democratize access to sophisticated business tools, making them intuitive and affordable for smaller businesses. | Muhammad Umer Farooq 21B-055-CS Muneer Ahmed Quadri 21B-011-CS Imad Nadeem 21B-080-CS Mahnoor 21B-151-SE Faiza Bibi 21B-164-CS | |||
| 68 | Computer Science | BS Computer Science | CS02 | Secure SNN Based Fraud Detection with Homomorphic Encryption | Dr. Farhan Ahmed Karim | Assistant Profesor | Fall 2021 | This project focuses on developing a secure and efficient fraud detection system for online transactions by combining Spiking Neural Networks (SNNs) with Homomorphic Encryption (HE). SNNs are a type of artificial neural network known for their energy efficiency and ability to process data in a way that mimics the human brain, using electrical pulses or spikes. HE allows data to remain encrypted while being processed, ensuring privacy and security throughout the detection process.With the increasing reliance on online payments, there has been a rise in cybercrime, making fraud detection systems a vital part of online transactions. This project seeks to address the challenge of identifying fraudulent transactions in real time while minimizing the number of legitimate transactions incorrectly flagged as fraud. The system was developed using a dataset of online transaction records, and machine learning techniques were applied to classify transactions as either fraudulent or legitimate.The primary goal of the project was to explore the development of a fraud detection system that balances both accuracy and security. By integrating SNNs with HE, the system aims to process encrypted transaction data in a more efficient way, with a focus on maintaining privacy while seeking to achieve reasonable precision and recall in fraud detection. Preliminary results suggest that this approach could potentially help reduce fraud while allowing legitimate transactions to be processed smoothly. | Ahsan Toufiq 21B-043-CS Laiba Khan 21B-077-CS Muhammad Omer 21B-092-CS | |||
| 69 | Computer Science | BS Computer Science | CS03 | RESIDENTIAL RECORD MANAGEMENT SYSTEM | Engr. Naveed ul Haq | Senior Lecturer | Fall 2021 | The Residential Record Management System (RRMS) is a web-based application designed to enhance the efficiency and transparency of residential colony management. This project aims to automate essential tasks such as record-keeping, financial tracking, and fund collection, addressing the limitations of existing manual and basic software solutions. The development process involves comprehensive requirement analysis, followed by the design and implementation of modules that facilitate user authentication, financial management, and reporting. By utilizing modern web technologies, including React.js and Node.js, the RRMS provides a user-friendly interface for both administrators and residents. Major conclusions drawn from this work indicate that the RRMS significantly improves operational efficiency, reduces errors in financial management, and fosters transparency in fund allocation and usage. The successful deployment of the RRMS can lead to enhanced user satisfaction and better management of residential communities. | Faryal Aslam 21B-222-SE Bushra Sultan 21B-186-SE Abdul Rafay 21B-037-CS Aneeq Ahmed Khan 21B-112-CS Rabia Khan Meerkhani 21B-199-CS | |||
| 70 | Computer Science | BS Computer Science | CS04 | DECENTRALIZED BLOCKCHAIN WITH SMART CONTRACTS | Farhat Hasnain Naqvi | Junior Lecturer | Fall 2021 | This project involves the design of a blockchain system that is decentralized,drawing inspiration from Ethereum. However, it has a particular emphasis on enabling secure and transparent transactions through smart contracts. The main objective of this project is the implementation of a Distributed Ledger System that can support cryptocurrency transactions, wallet management, and perform smart contracts at its premises in a decentralized network. Accomplishing this required the use of cryptographic techniques together with distributed consensus mechanisms that ensured the security and immutability of transaction data. It employed a PubSub system that could facilitate real-time node synchronization on transaction propagation and mining. It used a combination of JavaScript frameworks and libraries for development, such as Node.js combined with express for the backend, and React for the frontend interface. It was seeded with several wallets and transactions, and then several tests were run to see the integrity and security features of the blockchain. Ultimately, the successful implementation proved that decentralized systems have great potential for peer-to-peer transactions without intermediaries. The major conclusion drawn from the project is that blockchain technology can provide a highly secure, transparent, and efficient way to manage digital assets. | Sami Ullah 21B-016-CS Hamza Shahab 21B-214-CS Vivek Kumar 21B-179-CS M. Zarrar 20B-067-CS | |||
| 71 | Computer Science | BS Computer Science | CS06 | Predicting Climate Extremes — A Data Driven Approach | Dr. Lubaid Ahmed | Fall 2021 | The project “Predicting Climate Extremes — A Data-Driven Approach” aims to meet the immediate need for accurate, short-term weather forecasts tailored to the unique climatic conditions of Pakistan.Incorporating international models like Global Forecast System, Icosahedral Nonhydrostatic Model and local data sources like Pakistan Meteorological Department, the system integrates advanced machine-learning techniques to improve the precision of regional climate predictions. The primary objectives include enhancing the accuracy of rainfall, heatwave, flood, and drought event predictions while offering clear, actionable insights through a user-friendly visualization platform. This dual approach bridges gaps in real-time localized forecasting and data interpretation, empowering authorities and the public to make informed decisions. Bridging the gap between localized forecasting and data interpretation will allow decision-makers in public planning, agriculture, and emergency management to make well-informed decisions.The outcomes demonstrate the potential of combining physical-based weather models with machine my learning to significantly improve regional forecasting, addressing a critical gap in Pakistan’s weather prediction landscape. | Rana Muhammad Ebrahim 21B-022-CS Muhammad Taha Pasha 21B-039-CS Hanzallah Ahmed Khan 21B-148-CS Muhammad Faraz Khan 21B-053-CS Muhammad Umer 21B-120-CS |