Barnard Distinguished Lecture in Computer Science: Lydia E. Kavraki (Rice University)
Speaker: Lydia E. Kavraki (Rice University)
Title: Robotics, AI, and the Quest for Human-Centered Autonomous Systems
The seminar will be available for in-person and Zoom participation. For those attending in-person, a reception will precede the talk starting at 6:00pm. If you would like to attend via Zoom or in-person and you do not have an active BC/CU ID, you would need to register. A registration link will be posted soon.
Spurred by advances over the last sixty years, robots are no longer confined to factories; they are increasingly integrated into human environments, collaborating closely with people on a diverse range of tasks. As these systems evolve to tackle even more complex roles, a multitude of theoretical and practical challenges arise to ensure their reliability and performance. This talk will delve into the intricacies of developing human-centered robotic systems, placing particular emphasis on the computational underpinnings of motion planning. The first part of the talk will highlight recent advances in motion planning algorithms and explore how they enable robots to execute a wide variety of tasks across diverse settings. Building on this foundation, the second part will address deriving motion from high-level specifications, which define what the robot must achieve rather than how. Finally, the talk will discuss how the concepts and techniques refined in motion planning and robotics extend beyond traditional uses - reaching into areas such as computational structural biology and the design of new therapeutics – and highlight the transformative potential of interdisciplinary research.
Lydia E. Kavraki is the Kenneth and Audrey Kennedy Professor of Computing and professor of Computer Science and Bioengineering at Rice University. She is also the Director of the Ken Kennedy Institute for AI and Computing. Kavraki’s research develops the AI and the algorithmics needed to connect the digital to the physical world. She has two main areas of application for her research. In robotics, she develops methodologies for motion planning, machine learning methods for reasoning under uncertainty, and multi-modal frameworks to instruct robots and collaborate with them. In computational biomedicine, she develops AI methods for understanding biomolecular interactions and aiding the design of new therapeutics. Kavraki is a member of the American Academy of Arts and Sciences and the National Academy of Medicine. She is the recipient of the IEEE Robotics and Automation Society Pioneer Award and the IEEE Frances E. Allen Medal. More information about her work can be found at https://profiles.rice.edu/faculty/lydia-e-kavraki
