Rohan Paleja - Purdue University
Students: Spring 2026, unless noted otherwise, sessions will be virtual on Zoom.
Join us live on Zoom >
( Register to receive a reminder )
Wednesday, Jan 14, 2026 04:30pm - 05:30pm ET
( Register to receive a reminder )
Wednesday, Jan 14, 2026 04:30pm - 05:30pm ET
Building Interpretability into Human-Aware Robots through Neural Tree-Based Models
Jan 14, 2026
Abstract
Collaborative robots and machine-learning-based virtual agents are increasingly entering the human workspace with the aim of increasing productivity, enhancing safety, and improving the quality of our lives. These agents will dynamically interact with a wide variety of people in dynamic and novel contexts, increasing the prevalence of human-machine teams in applications spanning from healthcare and manufacturing to household assistance. My research aims to create transparent embodied systems that can support users and interact with humans, pushing the frontier of real-world robotics systems towards those that understand human behavior, maintain interpretability, and coordinate with high performance. In this talk, I will cover a set of works that enable robots to 1) understand and learn from diverse human users, 2) learn interpretable, human-readable tree-based control policies directly via reinforcement learning, and 3) provide users with information online to improve situational awareness and facilitate effective human-robot collaboration.About the Speaker
Dr. Rohan Paleja is an Assistant Professor in the Department of Computer Science at Purdue University. He directs the Strategies for Collaboration, Autonomy, Learning, and Exploration in Robotics Lab. The SCALE Robotics Lab focuses on advancing machine learning and artificial intelligence to improve robot learning, human-robot interaction, and multi-agent collaboration. Their goal is to equip autonomous agents with the ability to operate in the diverse, unstructured, and human-rich environments these agents will encounter in the real world.
Dr. Paleja's research interests cover a broad range of topics, namely Explainable AI (xAI), Interactive Robot Learning, and Multi-Agent Collaboration. Prior to Purdue, Dr. Paleja was a Technical Staff Researcher in the Artificial Intelligence Technology group at MIT Lincoln Laboratory, where he collaborated with the Air Force Experimental Operations Unit and the Army Research Lab. Prior to that, he earned his Ph.D. in Robotics at the Georgia Institute of Technology in 2023.
His work has received multiple awards, including a Best Paper Finalist Award at the Conference of Robot Learning (CoRL) and a Best Workshop Paper Award at the International Conference of Computer Vision (ICCV) Multi-Agent Relational Reasoning Workshop.
Ways to Watch
