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SHAHID

Mr. Shahid Ali

Lab Instructor
Department of Artificial Intelligence

Profile Summary

Shahid Ali is an AI Researcher and Computer Vision Engineer with a strong foundation in machine learning, deep learning, and image processing. My interests lie at the intersection of Computer Vision and Natural Language Processing, with a focus on developing reliable, human-centered AI solutions. Developing and deploying AI systems that are scalable, high-performance while contributing to collaborative, innovation-driven projects.

Qualification

Degree Institution Duration
Master of Science in Artificial Intelligence [MS-AI] COMSATS University Islamabad 02/09/2024 – 02/09/2026
Bachelor of Science in Computer Science [BS-CS] COMSATS University Islamabad 04/03/2019 – 15/03/2023

Thesis & CGPA

  • MS Thesis: NeuroXSeg: An Uncertainty-Aware Explainable Hybrid Deep Learning Model for Trustworthy Brain Tumor Segmentation in MRI. (CGPA: 4.0 / 4.0)
  • BS Thesis: Application for blind people to help them search for nearby objects. (CGPA: 3.49/4.0)

Teaching Experience

Position Institution Duration
Teaching Associate COMSATS University Islamabad 01/09/2025 – 31/08/2026
Lab Instructor Shifa Tameer-e-Millat University, Islamabad 13/04/2026 – Continue

Professional Experience

Position Organization Duration
Junior Oracle Developer & Data Analyst Ghani Glass Limited 03/03/2023 – 06/11/2023
Artificial Intelligence Intern KaRiz Cyber Technologies (SMC-Private) Limited 23/06/2024 – 23/07/2024

Honors & Awards

No. Award / Scholarship
1. Recipient of Fully Funded Scholarship in entire bachelor’s degree at COMSATS University Islamabad (2019-2023)
2. Recipient of Fully Funded Scholarship in entire master’s degree at COMSATS University Islamabad (2024-2026)

Research Areas / Interests

No. Research Area / Interest
1. Computer Vision (CV)
2. Medical Imaging
3. Brain Tumor Detection and Segmentation
4. Deep Fake Detection
5. Natural Language Processing (NLP)
6. Large Language Models (LLMs)
7. Retrieval-Augmented Generation (RAG)
8. Agentic AI Systems
9. Generative AI
10. Diffusion Models
11. Real-Time Object Detection
12. Healthcare AI Applications
13. Explainable AI (XAI)
14. AI-powered Diagnostic Systems
15. Transformer-based Architectures
16. Data Science and Predictive Analytics

Projects

No. Project Title
1. Application for blind people to help them search for nearby objects (Final Year Project) – Android-based real-time object detection app using YOLOv4-Tiny, SSD MobileNetV2, and ResNet50.
2. Lung Tumor Segmentation Using U-Net – Deep learning-based medical image segmentation system using U-Net architecture.
3. Posture Tracking using MediaPipe – Real-time posture monitoring system using MediaPipe and Computer Vision.
4. AI-Based Waste Recycling Plant – Real-time waste classification using YOLOv8.
5. Parkinson’s Disease Detection Using Machine Learning – ML model using biomedical data and feature selection.
6. Crop Disease Detection Application (CropX) – Mobile app for crop disease detection using image processing and ML.

Certifications

No. Certification
1. Data Science with Python – Microsoft
2. Introduction to Data Science – Microsoft
3. Machine Learning – Microsoft
4. Machine Learning, AI & Data Science – Microsoft
5. Fundamentals of AI – Microsoft Azure