Roman Naeem

Roman Naeem

PhD Student

Chalmers University of Technology

Biography

I am a PhD researcher specializing in deep learning for computer vision and medical image analysis. I have experience developing state-of-the-art models for tasks such as segmentation, object detection, and image-to-graph centerline tracking. My work has been published in top-tier venues, including MICCAI and AAAI. I am proficient in Python and PyTorch, with expertise in designing large-scale, geometry-aware deep learning models optimized for complex 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

Computer Vision Object Detection/Tracking and Segmentation Geometry-aware Deep Learing
Publications
Roman Naeem, David Hagerman, Jennifer Alvén, Lennart Svennson, Fredrik Kahl (2025). Trexplorer Super: Topologically Correct Centerline Tree Tracking of Tubular Objects in CT Volumes. In MICCAI 2025.
PDF Code Dataset DOI
David Hagerman, Anna Johnning, Roman Naeem, Fredrik Kahl, Erik Kristiansson, Lennart Svensson (2025). Optimizing Gene-Based Testing for Antibiotic Resistance Prediction. In AAAI 2025.
PDF Code Dataset DOI
Roman Naeem, David Hagerman, Lennart Svennson, Fredrik Kahl (2024). Trexplorer: Recurrent DETR for Topologically Correct Tree Centerline Tracking. In MICCAI 2024.
PDF Code Dataset DOI
David Hagerman, Roman Naeem, Jakob Lindqvist, Carl Lindström, Fredrik Kahl, Lennart Svennson (2024). SwInception - Local Attention Meets Convolutions. In ICPRAI 2024.
PDF Code Dataset DOI

Experience

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.
Technical Skills
Deep Learning

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.

Programming

Experience with Python, PyTorch, TensorFlow, CUDA, C++, and MATLAB.

Datasets and Validation

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.

Software Engineering

Git, Bash, Conda, Linux, Cloud GPUs (SLURM, Google Cloud), Experiment tracking (Neptune, Weights & Biases), Android software development.