I am an AI researcher developing trustworthy and clinically relevant machine learning methods for medical imaging. My research focuses on cardiac ultrasound, cardiac MRI, 3D/4D reconstruction, foundation models, and computational cardiology, with the goal of improving cardiovascular diagnosis and expanding global access to advanced imaging technologies.
My work combines deep learning, computer vision, geometric learning, and biomedical engineering to bridge cutting-edge AI research with real-world clinical applications.
- 🫀 Cardiac AI (Ultrasound & MRI)
- 📈 Medical Image Analysis
- 🧠 Foundation Models for Medical Imaging
- 📦 Representation Learning
- 🕸 Geometric & Mesh Learning
- 📐 3D/4D Cardiac Reconstruction
- 🔄 Motion Estimation & Image Registration
- 🧬 Computational Cardiology
📚 Citations: 3142
📈 h-index: 23
⭐ i10-index: 29
🌍 Google Scholar
https://scholar.google.com/citations?user=36WXELIAAAAJ
📄 Selected Publication Venues
- IEEE Transactions on Medical Imaging (TMI)
- Medical Image Analysis (MedIA)
- MICCAI
- 🥇 FoE EPSRC Postdoctoral Pathway Fellowship
- 🥈 Runner-up Best Presentation Award (MICCAI ASMUS)
- 🏅 Imperial College EPSRC Doctoral Training Partnership Studentship
- 🥇 Erasmus Mundus Joint Master's Scholarship
- 🏅 University Gold Medal
I welcome collaborations in
- Medical Image Analysis
- AI for Healthcare
- Cardiac Imaging
- Foundation Models
- Computer Vision
- Open-source Medical AI
Feel free to connect if you're interested in collaborating on research, open-source software, or clinical AI applications (kamruleeekuet@gmail.com, k.hasan22@imperial.ac.uk).
"Building trustworthy AI to advance cardiovascular imaging and improve global access to healthcare."