"From Robots to Biomolecules: Computing for the Physical World"
2013 / 2014 George Bekey Lecture
Department of Computer Science

Lydia E. Kavraki

Noah Harding Professor of Computer Science and Bioengineering Rice University

Professor, Graduate Program in Structural and Computational Biology and Molecular Biophysics (Joint Appointment) Baylor College of Medicine


Over the last decade, the development of fast and reliable motion planning algorithms has deeply influenced many domains in robotics, such as industrial automation and autonomous exploration. Motion planning has also contributed to great advances in an array of unlikely fields, including graphics animation and computational structural biology.

This talk will first describe how sampling-based methods revolutionized motion planning in robotics. The presentation will quickly focus on recent algorithms that are particularly suitable for systems with complex dynamics. The talk will then introduce an integrative framework that allows the synthesis of motion plans from high-level specifications. The framework uses temporal logic and formal methods and establishes a tight link between classical motion planning in robotics and task planning in artificial intelligence. Although research initially began in the realm of robotics, the experience gained has led to algorithmic advances for analyzing the motion and function of proteins, the worker molecules of all cells. This talk will conclude by discussing robotics-inspired methods for computing the flexibility of proteins and large macromolecular complexes with the ultimate goals of deciphering molecular function and aiding the discovery of new therapeutics.


Lydia E. Kavraki is the Noah Harding Professor of Computer Science and Bioengineering at Rice University. She also holds an appointment at the Department of Structural and Computational Biology and Molecular Biophysics at the Baylor College of Medicine in Houston. Kavraki received her B.A. in Computer Science from the University of Crete in Greece and her Ph.D. in Computer Science from Stanford University. Her research contributions are in physical algorithms and their applications in robotics (robot motion planning, hybrid systems, formal methods in robotics, assembly planning, micromanipulation, and flexible object manipulation), as well as in computational structural biology, translational bioinformatics, and biomedical informatics (modeling of proteins and biomolecular interactions, large-scale functional annotation of proteins, computer-assisted drug design, and systems biology).

Kavraki has authored more than 180 peer-reviewed journal and conference publications and a co-author of the popular robotics textbook "Principles of Robot Motion" published by MIT Press. She is heavily involved in the development of The Open Motion Planning Library (OMPL), which is used in industry and in academic research in robotics and biomedicine. Kavraki is currently on the editorial board of the International Journal of Robotics Research, the ACM/IEEE Transactions on Computational Biology and Bioinformatics, the Computer Science Review, and Big Data. She is also a member of the editorial advisory board of the Springer Tracts in Advanced Robotics. 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), a Fellow of the American Association for the Advancement of Science (AAAS), and a Fellow of the World Technology Network (WTN). Kavraki was elected a member of the Institute of Medicine (IOM) of the National Academies in 2012. She is also a member of the Academy of Medicine, Engineering and Science of Texas (TAMEST) since 2012.

Published on August 15th, 2017

Last updated on January 23rd, 2020