Biography
I am a PhD researcher specializing in image-to-graph models for medical image analysis. My work focuses on developing geometry-aware deep learning methods for vascular centerline tracking and related tasks in segmentation, object detection, and tracking. My research has been published in top-tier venues, including MICCAI and AAAI. I am proficient in Python and PyTorch, with expertise in designing scalable models for complex medical imaging datasets.
Education
PhD Electrical Engineering
Chalmers University of Technology (Gothenburg, Sweden)
Jan 2021 - Present
MSc. Complex Adaptive Systems
Chalmers University of Technology (Gothenburg, Sweden)
Sep 2018 - Jun 2020
BE Electrical Engineering
National University of Sciences and Technology (Islamabad, Pakistan)
Sep 2012 - Jun 2016
Interests
Experience
Research Assistant
Chalmers University of Technology (Gothenburg, Sweden)Developed an Android app for real-time on-device book detection and OCR (~250 ms) using EfficientDet and Google ML Kit, with a custom text-matching module for fast, private inventory management.Master Thesis Project
Whywaste AB (Gothenburg, Sweden)Developed an automated food inventory model using object detection and a novel object similarity network for visual clustering, leveraging synthetic data to reduce reliance on real samples and streamline training.Assitant Business Manager
Pakistan Telecommunication Company Limited (Karachi, Pakistan)Managed telecommunication infrastructure and 6,000 subscribers, leading a 24-member team to maintain and expand networks while implementing retention strategies that grew the customer base.Process Engineering Intern
Procter & Gamble (Karachi, Pakistan)Conducted PR analysis on a new packing line to enhance troubleshooting, developed a logistics tracker for cost monitoring, and streamlined processes to reduce time and improve efficiency.Sales and Design Intern
Avanceon Middle East & South Asia (Karachi, Pakistan)Applied CRM tools to improve sales at Avanceon. Gained expertise in Rockwell Automation systems and IAB software, while researching industrial applications and safety standards to strengthen technical knowledge.
Extensive experience building custom Transformer, CNN, RNN, and GNN models for vessel centerline detection, image segmentation, object detection, registration, and diverse ML tasks including semi/self-supervised, reinforcement learning, and NLP.
Experience with Python, PyTorch, TensorFlow, CUDA, C++, and MATLAB.
Skilled in creating custom datasets for image segmentation and spatial graphs, handling large-scale multimodal data (CT, MRI, endoscopy, images, text) for model training and validation using extensive evaluation criteria.
Git, Bash, Conda, Docker, Linux, Cloud GPUs (SLURM, Google Cloud), Experiment tracking (Neptune, Weights & Biases), Android software development.