Md Hasibur Rahman

About

I am a Postdoctoral Fellow in the Department of Electrical and Computer Engineering at Clemson University, where I work with Prof. Adam Hoover. I received my Ph.D. in Computer Science from Missouri University of Science and Technology in 2026 under the supervision of Prof. Sanjay Madria. My dissertation focused on UAV detection and tracking in challenging aerial environments.

My research focuses on computer vision, tracking, spatiotemporal learning, and multimodal sensing. During my Ph.D., I worked on tiny airborne object detection, UAV swarm tracking, and multi-LiDAR 3D localization. At Clemson, I am applying this background to biomedical AI, wearable sensing, and egocentric vision.

Current Work at Clemson

Biomedical AI and osteoarthritis. I am working with the hand-OA research team on transfer learning using OAI data and newly collected data.

Egocentric vision for off-road environments. I am working on persistent traversable-route estimation from egocentric video, with a focus on maintaining a continuous route when the path is weak, occluded, or temporarily missing.

Wearable sensing. I am also exploring multimodal time-series learning for human activity and event detection in biomedical applications.

Recent

Selected Research

ACM TSAS · 2026

STARD-Net

Spatiotemporal attention for detecting tiny airborne targets from moving drones under clutter, motion, and weak visual evidence.

paper / code

ICPR · 2026

KRAfT

UAV swarm tracking using Kalman residual modeling, formation-aware association, and recovery when detections are missing or ambiguous.

paper / code + dataset

ACM SIGSPATIAL · 2026

TARF

Track-aware reliability fusion for 3D drone localization and trajectory estimation from sparse heterogeneous LiDAR observations.

conference listing

Research Interests

Computer Vision: small-object detection, multi-object tracking, temporal association, motion modeling, and state estimation.

Multimodal Sensing: sensor fusion, LiDAR-based 3D localization, sparse sensing, and temporal reasoning.

Biomedical AI: wearable sensing, multimodal time series, human activity and event detection, and transfer learning for biomedical data.

Datasets

MVAAOD. An augmented dataset for vision-based UAV detection and tracking, introduced in our IEEE AIPR 2023 paper. Dataset

UAVSwarm-W2C. A multi-UAV dataset developed for UAV swarm tracking and evaluation of temporal association, identity preservation, and formation-aware tracking. Dataset / KRAfT repository

Teaching

Before my Ph.D., I was a Lecturer in Computer Science and Engineering at Bangladesh University of Business and Technology (2018–2022), where I was instructor of record for Data Structures, Operating Systems, Data Mining, Internet of Things, and Computer Architecture. I also supervised undergraduate thesis and capstone projects and helped establish the department's IoT laboratory.

At Missouri S&T, I served as a Graduate Teaching Assistant (2023–2026), supporting Big Data and MATLAB courses through laboratory instruction, grading, office hours, debugging, and student mentoring.

Selected Honors & Research Support

• Top 3 Best Poster, Pathways 2026 Symposium, NextGen Precision Health, 2026.
• NAIRR Pilot Resource Allocation for A100/H100-class GPU resources.
• First Runner-Up, IEEE Robo-droid Championship, 2015.