Graduate student specialized in training, evaluating, and deploying complex neural network architectures. Proficient in engineering end-to-end data pipelines, developing advanced computer vision models, and building intelligent software solutions.
Python, C++, SQL
PyTorch, TensorFlow, OpenCV, Scikit-Learn, NumPy, Pandas
Linux (Ubuntu), Git, React Native, ROS 2
Lahore University of Management Sciences (LUMS)
Advanced coursework focusing on Deep Learning architectures, Computer Vision frameworks, and probabilistic data systems.
University of Central Punjab
Core foundations in computer science, software engineering principles, algorithm design, data structures, and intelligent computing systems.
Transitioned to a full-time engineering role to collaborate on system implementation, write scalable code foundations, and contribute to software optimization cycles within active sprint environments.
Gained hands-on industry experience building application logic, debugging software systems, and working across technical stacks alongside cross-functional development teams.
3D Deep Learning & Medical Image Analysis
Designed and optimized 3D U-Net and Attention U-Net architectures to isolate complex tumor structures in multi-modal MRI datasets. Focused on spatial feature extraction and addressing class imbalance in volumetric medical scans.
Computer Vision & Intelligent Systems Deployment
Deployed a lightweight BiSeNet segmentation framework engineered for low-latency inference on hardware. Integrated the real-time visual perception outputs into a feedback control system for predictive orientation steering.