Biomedical AI
A planned direction extending multimodal learning to imaging, behavioral, and sensor-derived evidence for interpretable and clinically meaningful decision support.
Multimodal AI · Computer Vision · Biomedical AI
Md Hasibur Rahman
PhD in Computer Science
Missouri University of Science and Technology
Open to assistant professor role
My research develops reliable multimodal AI for UAV perception, tracking, and autonomy under sparse observations, sensor uncertainty, and domain shift. I plan to apply my knowledge from this work to biomedical AI by integrating imaging, behavioral, and sensor-derived evidence for interpretable and clinically meaningful decision support. I am also interested in GeoAI.
News
- Successfully defended Ph.D. dissertation.
- TARF: A multilidar drone detection and tracking paper is accepted at ACM SIGSPATIAL 2026.
- Passed the Ph.D. comprehensive examination.
- KRAfT accepted for presentation at IEEE ICPR 2026.
- Radiogenomic MRI classification poster recognized among the top three posters at the NextGen Pathways 2026 Symposium.
- STARD-Net published in ACM Transactions on Spatial Algorithms and Systems.
- V-USDT published at IEEE MDM 2025.
Research
Current focus
Multimodal UAV tracking
Fusing visual, temporal, and LiDAR evidence to maintain reliable trajectories under sparse observations, sensor disagreement, and occlusion.
Vision Language Action (VLA) for UAVs
Developing UAV agents that connect visual perception and language-guided reasoning with safe, context-aware actions in dynamic environments.
Synthetic Aperture Radar (SAR) for disaster response
Using all-weather radar imagery to map affected areas, assess damage, and support timely analysis when optical observations are limited.