Current member
Shah Md Nehal Hasnaeen
PhD Student, Bredesen Center
Nehal works on machine learning across modalities — from RF fingerprinting to the multimodal fusion behind FujiView's scenic-visibility forecasts.
Shah Md Nehal Hasnaeen is a PhD student in the Bredesen Center for Interdisciplinary Research and Graduate Education at the University of Tennessee, Knoxville, working with AICIP on multimodal machine learning.
He is a co-author of FujiView (WACV 2026), the lab’s multimodal scenic-visibility forecasting system, and of the lab’s collaborative work on reinforcement learning and AI agents for adaptive robotic assistance in dementia care. His broader research interests span deep learning for electromagnetic and RF fingerprinting, bringing a signals background to the lab’s fusion problems.
Before UT, he earned an MS from Idaho State University and a BS from Bangladesh University of Engineering and Technology.
Projects
FujiView
Will you see Mount Fuji tomorrow? FujiView fuses live webcam imagery with weather data to forecast scenic visibility — published at WACV 2026.
MUSICARE-VR
Music intervention in virtual reality that adapts to a person with dementia in real time — with reinforcement learning and AI agents driving socially assistive robots.
Publications
FujiView: Multimodal Late-Fusion for Predicting Scenic Visibility
IEEE/CVF Winter Conference on Applications of Computer Vision (WACV) 2026
Integrating Reinforcement Learning and AI Agents for Adaptive Robotic Interaction and Assistance in Dementia Care
arXiv 2025