Kris K Hauser
Kris K Hauser
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- Ph.D., Computer Science, Stanford University, 2008
- B.A., Mathematics, University of California at Berkeley, 2003
- B.A., Computer Science, University of California at Berkeley, 2003
Kris Hauser is an Associate Professor in the Department of Computer Science and the Department of Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign. His research interests lie in robot planning and control, a field devoted to providing the decision-making capabilities needed for robots and other intelligent agents to perform complex physical tasks. His research builds upon the theoretical foundations of state space dynamics and optimality, but attempts to overcome the shortcomings of classical theory when faced the complexities of real-world systems, such as high dimensionality, uncertain dynamics, bounded computation, and integration with perception and learning. The methodologies at the foundation of this work include optimization, probabilistic methods, AI, control theory, and physics simulation, and theory is bridged with practice on real-world physical robots in the context of a diverse range of applications with social impact, including robot locomotion and manipulation, medical robots, human-operated robots, warehouse automation, and intelligent vehicles.
Prof. Hauser received his PhD in Computer Science from Stanford University in 2008, bachelor's degrees in Computer Science and Mathematics from UC Berkeley in 2003, and worked as a postdoctoral fellow at UC Berkeley. He then joined the faculty at Indiana University from 2009-2014, where he started the Intelligent Motion Lab, and then joined the faculty of Duke University from 2014-2019. Prof. Hauser is a recipient of a Stanford Graduate Fellowship, Siebel Scholar Fellowship, Best Paper Award at IEEE International Conference on Humanoid Robots 2015, the NSF CAREER award, and two Amazon Research Awards. He also works as a consultant for Google's autonomous driving company, Waymo.
- Associate Professor, Department of Computer Science, Department of Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, 2019-
- Associate Professor, Department of Electrical and Computer Engineering, Department of Mechanical Engineering and Materials Science, Duke University, 2014-2019
- Assistant Professor, Department of Computer Science and Informatics, Indiana University, 2009-2014
- Robot motion planning and control, semiautonomous robots, and integrating perception and planning, as well as applications to intelligent vehicles, robotic manipulation, robot-assisted medicine, and legged locomotion.
Selected Articles in Journals
- K. Hauser, T. Bretl, J.-C Latombe, K. Harada, and B. Wilcox, Motion Planning for Legged Robots in Varied Terrain. International Journal of Robotics Research (IJRR), Vol. 27(11-12), pp. 1325-1349, 2008. (Impact factor: 4.095)
- C. Bennett and K. Hauser. Artificial Intelligence Framework for Simulating Clinical Decision-Making: A Markov Decision Process Approach. Artificial Intelligence in Medicine, 57(1):9-19, January 2013. doi: 10.1016/j.artmed.2012.12.003. (Impact factor: 1.345)
- K. Hauser. The Minimum Constraint Removal Problem with Three Robotics Applications. International Journal of Robotics Research (IJRR), 33(1):5-17, January, 2014. doi: 10.1177/0278364913507795 (Impact factor: 2.863)
- K. Hauser and Y. Zhou. Asymptotically Optimal Planning by Feasible Kinodynamic Planning in State-Cost Space. IEEE Transactions on Robotics, 32(6): 1431-1443, 2016. (Impact factor 2.432)
- K. Hauser. Learning the Problem-Optimum Map: Analysis and Application to Global Optimization in Robotics. IEEE Transaction on Robotics, 33(1):141-152, 2017. (Impact factor 2.432)
- K. Hauser, S. Wang, and M. Cutkosky. Efﬁcient Equilibrium Testing under Adhesion and Anisotropy using Empirical Contact Force Models. IEEE Transactions on Robotics, 34(5):1157-1169, 2018. doi: 10.1109/TRO.2018.2831722
- M. Draelos, G. Tang, B. Keller, A. Kuo, K. Hauser, J. A. Izatt. Optical Coherence Tomography Guided Robotic Needle Insertion for Deep Anterior Lamellar Keratoplasty. IEEE Transactions on Biomedical Engineering, Nov. 20, 2019. doi:10.1109/TBME.2019.2954505
Articles in Conference Proceedings
- S. Wang and K. Hauser. Unified Multi-Contact Fall Mitigation Planning for Humanoids via Contact Transition Tree Optimization. IEEE Int’l. Conf. on Humanoid Robots (Humanoids), November, 2018. Best paper award nominee.
- K. Hauser. Semi-Infinite Programming for Trajectory Optimization with Nonconvex Obstacles. Workshop on Algorithmic Foundations of Robotics (WAFR), December, 2018.
- F. Wang and K. Hauser. Stable Bin Packing of Non-convex 3D Objects with a Robot Manipulator. IEEE International Conference on Robotics and Automation, May, 2019.
- G. Tang and K. Hauser. Discontinuity-Sensitive Optimal Control Learning by Mixture of Experts. IEEE International Conference on Robotics and Automation, May, 2019.
- F. Wang and K. Hauser. Robot Packing with Known Items and Nondeterministic Arrival Order. Robotics: Science and Systems (RSS), June 2019. Best paper award nominee.
- G. Tang, W. Sun, and K. Hauser. Time-Optimal Trajectory Generation for Dynamic Vehicles: A Bilevel Optimization Approach. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), October, 2019.
- Indiana University Women in Computing Inspirational Teacher Award (2011)
- Amazon Research Award (2019)
- Amazon Research Award (2018)
- Best paper award, IEEE Conference on Humanoid Robots (Humanoids) (2015)
- NSF CAREER Award (2013)
- CS 498 - Intelligent Robots