Scott Niekum

Professor Niekum is an Associate Professor in the College of Information and Computer Sciences at UMass Amherst, where he directs the Safe, Confident, and Aligned Learning + Robotics Lab (SCALAR). Previously, he was an Assistant (2015-2021) and Associate (2021-2022) Professor at The University of Texas at Austin in the Department of Computer Science. Prof. Niekum received his PhD in 2013 from UMass Amherst (supervised by Andrew Barto) and was a postdoctoral research fellow at the Carnegie Mellon University Robotics Institute from 2013-2015.

The goal of Professor Niekum's research is to enable robots and other learning agents to be deployed in the real world with minimal expert intervention. Toward this goal, his lab develops efficient learning algorithms that enforce safety constraints, provide performance guarantees, and align human and agent objectives. Thus, this work draws from both machine learning and robotics, including topics such as imitation learning, reinforcement learning, manipulation, and human-robot interaction.

Professor Niekum is a recipient of the National Science Foundation CAREER Award and the AFOSR Young Investigator Award. While in his position as an Assistant Professor at The University of Texas at Austin, he also received the College of Natural Sciences Teaching Excellence Award. Prof. Niekum regularly serves as an area chair, associate editor, or reviewer for machine learning and robotics conferences and journals including NeurIPS, ICML, ICLR, RSS, CoRL, ICRA, IROS, HRI, AAAI, IJCAI, JMLR, IJRR, and TRO.