Event Location: NSH 1305
Bio: Lydia E. Kavraki is the Noah Harding Professor of Computer Science and Professor of Bioengineering at Rice University. Kavraki received her Ph.D. in Computer Science from Stanford University. Her research contributions are in the area of robotics (robot motion planning, hybrid systems, formal methods in robotics, assembly planning, micromanipulation, and flexible object manipulation) and computational structural biology and bioinformatics (modeling of proteins and biomolecular interactions, computer-assisted drug design and the large-scale functional annotation of proteins). Kavraki has authored more than 150 peer-reviewed journal and conference publications and is one of the authors of a robotics textbook titled “Principles of Robot Motion” published by MIT Press. She is currently on the editorial board of the International Journal of Robotics Research, the ACM/IEEE Transactions on Computational Biology and Bioinformatics, and the Computer Science Review. She is also a member of the editorial advisory board of the Springer Tracts in Advanced Robotics, while she currently serves as a Distinguished Lecturer for the IEEE Robotics and Automation Society. Kavraki is the recipient of the Association for Computing Machinery (ACM) Grace Murray Hopper Award for her technical contributions. She has also received an NSF CAREER award, a Sloan Fellowship, the Early Academic Career Award from the IEEE Society on Robotics and Automation, a recognition as a top young investigator from the MIT Technology Review Magazine, and the Duncan Award for excellence in research and teaching from Rice University. Kavraki is a Fellow of the Association of Computing Machinery (ACM), a Fellow of the Institute of Electrical and Electronics Engineers (IEEE), a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI), a Fellow of the American Institute for Medical and Biological Engineering (AIMBE), and a Fellow of the World Technology Network (WTN).

Abstract: Note: The speaker has requested that this talk NOT be webcast or captured. It will not be available on video.

Over the last decade, the development of robot motion planning algorithms to solve complex geometric problems has contributed not only to advances in industrial automation and autonomous exploration, but also to a number of diverse fields such as graphics animation and computational structural biology. This talk will start by briefly discussing the state of the art of sampling-based motion planning and the Open Motion Planning Library that implements many such algorithms.

Recent advances in planning for hybrid systems will be described, as well as the challenges of combining formal logic and planning for creating safe and reliable robotic systems.

The talk will also demonstrate how the experience gained through robotics planning has led to algorithmic tools for analyzing the flexibility and interactions of molecules for the discovery of new medicines.