Scott Niekum
Adjunct Assistant Professor
Dr. Niekum is an Adjunct Professor at The University of Texas at Austin as well as an Associate Professor and the director of the Safe, Confident, and Aligned Learning + Robotics Lab (SCALAR) in the College of Information and Computer Sciences at The University of Massachusetts Amherst. In addition, he is also a core member of the interdepartmental UMass robotics group.
Research
Research Areas:
Research Interests:
- Enabling personal robots to be deployed with minimal intervention by robotics experts
- Machine learning and robotics
- learning from demonstration, manipulation, time-series analysis, control theory, and reinforcement learning.
Select Publications
P.S. Thomas, S. Niekum, G. Theocharous, and G.D. Konidaris. December 2015. Policy Evaluation Using the Omega-Return. Advances in Neural Information Processing Systems.
S. Niekum, S. Osentoski, C.G. Atkeson, and A.G. Barto. May 2015. Online Bayesian Changepoint Detection for Articulated Motion Models. IEEE International Conference on Robotics and Automation.
K. Hausman, S. Niekum, S. Osentoski, and G. Sukhatme. May 2015. Active Articulation Model Estimation through Interactive Perception. IEEE International Conference on Robotics and Automation.
S. Niekum, S. Osentoski, G.D. Konidaris, S. Chitta, B. Marthi, and A.G. Barto. February 2015. Learning Grounded Finite-State Representations from Unstructured Demonstrations. International Journal of Robotics Research.
S. Niekum, S. Osentoski, S. Chitta, B. Marthi, and Andrew G. Barto. June 2013. Incremental Semantically Grounded Learning from Demonstration. Robotics: Science and Systems.
Awards & Honors
2018 -
National Science Foundation CAREER Award
2018 -
PI: NSF CAREER Award
2017 -
PI: NSF - Smart and Autonomous Systems
2017 -
Co-PI: Office of Naval Research
2016 -
PI: NSF - National Robotics Initiative
2016 -
PI: NSF - Robust Intelligence
2012 -
PI: NSF - National Robotics Initiative
