Experience

  1. Doctoral Researcher, Computer Vision and Machine Learning

    Chalmers University of Technology (Gothenburg, Sweden)

    Research on structured prediction and efficient architectures for 3D medical imaging, funded by MedTech West. Thesis: Centerline Extraction for Tubular Trees in Medical Images.

    • Developed a family of recurrent transformer models for centerline graph extraction from 3D CT volumes (Trexplorer, Trexplorer Super, RefTr) producing topologically valid tree output. Three consecutive first-author MICCAI papers, the latest refining whole branch trajectories jointly to improve precision while using 2.4x fewer decoder parameters than the previous state of the art.
    • Released public benchmark datasets and radius-aware evaluation metrics for centerline tracking, archived on Zenodo with a DOI.
    • Built CEVAR, a fully automatic pipeline for post-EVAR follow-up CT developed with vascular surgeons at Sahlgrenska Academy, outperforming the commercial semi-automatic workflow currently in clinical use.
    • Worked on efficient dense prediction: BATS (over 53% lower peak GPU memory, up to 30% faster at comparable accuracy) and ARTA (54.6 mIoU on ADE20K in the ~100M parameter class).
    • Ran large-scale training on Swedish national HPC (NAISS, Berzelius, Mimer) as project PI, with sensitive patient data under ethics approval and containerised pipelines for reproducibility.
    • Supervised master’s theses and taught Deep Machine Learning, Medical Imaging Systems, and Digital Health, one course in Swedish.

  2. 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.

  3. 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.

  4. Assistant 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.

  5. 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.

  6. 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.

Education

  1. PhD Electrical Engineering

    Chalmers University of Technology (Gothenburg, Sweden)

  2. MSc. Complex Adaptive Systems

    Chalmers University of Technology (Gothenburg, Sweden)

  3. BE Electrical Engineering

    National University of Sciences and Technology (Islamabad, Pakistan)
Skills & Hobbies
Deep Learning

Custom transformer, CNN, and recurrent architectures for structured prediction, image-to-graph modelling, segmentation, detection, and registration in 2D and 3D. Efficient and mixed-resolution designs, plus semi-supervised, self-supervised, and reinforcement learning.

Programming

Python, PyTorch, TensorFlow, CUDA, C++, MATLAB, SQL. NumPy, SciPy, pandas, scikit-learn, OpenCV, SimpleITK.

High-Performance Computing

Large-scale multi-GPU training on Swedish national HPC (NAISS, Berzelius, Mimer) as project PI. SLURM, containerised environments, custom CUDA kernels, GPU profiling and memory optimisation.

Datasets and Validation

Building and publicly releasing benchmark datasets for image segmentation and spatial graphs. Custom metrics, benchmark design, and failure-mode analysis. Large-scale multimodal data (CT, MRI, endoscopy, natural images, text), including sensitive patient data under ethics approval.

Software Engineering

Git, Bash, Conda, Docker, Linux, Google Cloud. Experiment tracking with Weights & Biases and Neptune. Android development.

Awards
Languages
100%
English
70%
Swedish