Masudur Rahman

PostDoc @PurdueEngineers (IE), Ph.D in CS@Purdue
Email: rahman64@purdue.edu
My research focuses on developing principled and adaptable intelligence for autonomous systems operating in complex, high-stakes environments. I investigate generalization, and sample efficiency in decision-making under uncertainty, with an emphasis on algorithms that enable agents to reason, adapt, and act in dynamic settings. I design novel reinforcement learning algorithms and advance the reasoning capabilities of vision-language models (VLMs and LLMs), with a focus on grounded, interactive environments. These contributions enable high-impact applications, including burn diagnosis through medical imaging, and medical and emergency robotics, where systems must perceive affordances and improvise actions in unstructured, rapidly evolving conditions.
I am currently a Postdoctoral Research Assistant in the Edwardson School of Industrial Engineering at Purdue University, working with Dr. Juan P. Wachs. I completed my Ph.D. in Computer Science at Purdue University in 2024 under the supervision of Dr. Yexiang Xue. I completed my M.S. in Computer Science at the University of Virginia in 2018. Before that, I worked as a Lecturer at BRAC University from 2013 to 2015, after earning my B.Sc. in Computer Science and Engineering from BUET in 2013.
KEY RESEARCH AREAS
Reinforcement Learning
I develop practical algorithms that empower agents to generalize under uncertainty and adapt beyond their training distribution. My work focuses on robust, sample-efficient reinforcement learning, enhanced by foundation models for complex, real-world decision-making.
Keywords: Generalization in RL · Robust RL · Robust Policy Optimization (RPO) · Foundation Model-Augmented RL · Adaptive Decision-Making
Robotics
My research builds embodied systems capable of perceiving, reasoning, and improvising in unstructured environments. I combine affordance-aware control with foundation model-guided perception to support real-time planning in both medical and field robotics.
Keywords: Embodied AI · Affordance Learning · VLM-Guided Perception · Foundation Model-Guided Perception · Teleoperation· Robotic Improvisation
AI in Healthcare
I design clinically grounded AI systems that integrate visual, linguistic, and structured data to support diagnosis and autonomous decision-making. This includes medical imaging and robotic assistance, powered by foundation models and multimodal reasoning.
Keywords: Multimodal Reasoning · VLMs · Medical Robotics · Foundation Models in Healthcare · Burn Care
news
Jun 24, 2025 | A paper got accepted to the JMIR Medical Informatics 2025. Paper title: BURN-AID: AI-Driven Integrated System for Burn Depth Prediction with Electronic Medical Records. |
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May 25, 2025 | An abstract paper has been accepted to the Plastic Surgery The Meeting (PSTM) 2025. The work will be presented at PSTM 2025 — the premier annual conference organized by the American Society of Plastic Surgeons (ASPS)— at the New Orleans, Louisiana, in October 2025. |
May 20, 2025 | An abstract paper has been accepted to the Military Health System Research Symposium (MHSRS) 2025. Paper title: A Chain-of-Thought AI Reasoning Framework for Burn Diagnosis. The work will be presented at MHSRS — the leading forum for military health research — at the Gaylord Palms Resort and Convention Center in Kissimmee, FL, in August 2025. |
May 12, 2025 | A paper has been accepted to the Annual Conference on Medical Image Understanding and Analysis (MIUA) 2025. Paper title: Knowledge-Driven Hypothesis Generation for Burn Diagnosis from Ultrasound with a Vision-Language Model. Attending MIUA in July in Leeds, UK. |
Mar 17, 2025 | A paper got accepted to the Military Medicine Journal 2025. Paper title: A Framework for Advancing Burn Assessment with Artificial Intelligence. |
Nov 27, 2024 | Completed NSF I-Corps Hub: Great Lakes Region. Digital Badge. |
Nov 04, 2024 | Started my PostDoc at Purdue Engineering (IE). |
Sep 24, 2024 | Defended my Ph.D. Thesis. |
Jul 31, 2024 | Presenting a paper on AI for burn care at the Military Health System Research Symposium (MHSRS) 2024 in August, Kissimmee, FL. |
Jul 31, 2024 | Lightning talk on AI in Burn Surgery at ADSA 2024 in October at University of Michigan, Ann Arbor |
selected publications
- BURN-AID: AI-Driven Integrated System for Burn Depth Prediction with Electronic Medical RecordsJMIR Med Inform, 2025
- MIUAKnowledge-Driven Hypothesis Generation for Burn Diagnosis from Ultrasound with Vision- Language Model.2025
- MHSRS-AbstractA Chain-of-Thought AI Reasoning Framework for Burn DiagnosisIn In Military Health System Research Symposium , 2025