Curriculum Vitae
Snawar Hussain
PhD researcher working at the intersection of AI, computational imaging, numerical simulation, and physics. I build physics-aware and data-driven methods for modeling complex systems, with broader interests in scientific reinforcement learning, simulation, generative modeling, and computer vision.
Selected Projects
Selected research and engineering projects across computational MRI, AI-assisted imaging, computer vision, representation learning, and biomedical image analysis.
KIMBI: AI-Supported Intelligent Magnetic Resonance Imaging
Contributed to the KIMBI project in the context of Fraunhofer MEVIS and the U Bremen Research Alliance. My work focused on MRI simulation components compatible with gammaSTAR, a vendor-agnostic MR sequence development framework, supporting the connection between executable sequence descriptions, simulation, and AI-assisted imaging workflows.
ROBUST: Rodent Observable Behavior Understanding and Study Toolkit
A toolkit for unsupervised behavior analysis of rats using self-supervised representation learning with variational autoencoders and Hidden Markov Model based behavioral state clustering.
2D/3D Pose Estimation
Developed a multi-view pose estimation workflow that reconstructs 3D pose from multiple 2D camera views using geometric triangulation and camera-view correspondence.
Retinal Blood Vessel Segmentation
Implemented a U-Net based segmentation pipeline for retinal blood vessel extraction, including model training, evaluation, and qualitative visualization of segmentation results.
Education & Research Experience
PhD Candidate in Physics
Fraunhofer MEVIS / University of Bremen
Working on physics-based simulation, AI-assisted computational imaging, MRI sequence modeling, and efficient numerical methods for scientific computing.
Research Scholar in Computer Science
Zhejiang University
Research experience in machine learning, computer vision, representation learning.
M.Sc. in Control Science and Engineering
Central South University
Focused on intelligent systems, pattern recognition, machine learning, and computational methods for biomedical imaging and image processing.
B.Sc. in Mechatronics Engineering
National University of Sciences and Technology
Foundation in robotics, embedded systems, control, electronics, and engineering computation.
Publications
My research contributions span across simulation, computational imaging, scientific machine learning, and computer vision.
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