Lydia E. Kavraki is the Noah Harding Professor of Computer Science and
Professor of Bioengineering at Rice University. She also holds a joint 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 working with Jean-Claude Latombe. Her research
contributions are in physical algorithms and their applications in robotics (robot
motion planning, hybrid systems, 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 100 peer-reviewed
journal and conference publications and is one of the authors of a new robotics
textbook titled `Principles of Robot Motion' published by MIT Press. She is
currently a member of the editorial advisory board of the Springer Tracts in Advanced
Robotics, an associate editor for the IEEE Transactions on Computational Biology and
Bioinformatics and for the Computing Surveys. 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
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.
She currently serves as a Distinguished Lecturer for the IEEE Robotics and
Automation Society. Current projects at Kavraki's laboratory are described in
http://www.kavrakilab.org. More information on Kavraki's work can be found
in:
http://www.cs.rice.edu/~kavraki.

SWS   Info

Expert Audience

English

60 Minutes

Saarbrücken

The field of computing is increasingly expected to solve complex geometric

problems arising in the physical world. Such problems can be found in applications
ranging from robotics planning for industrial automation to molecular
modeling for studying biological processes. This talk will first describe
the development of a set of algorithmic tools for robot motion planning which
are often grouped under the name sampling-based algorithms.

Emphasis will be placed on recent results for systems with increased
physical realism and complex dynamics. The talk will then discuss how the
experience gained through sampling-based methods in robotics has led to algorithms for
characterizing the flexibility of biomolecules for drug discovery. A new trend in
Computer Science is presented in this talk. It concerns the development of algorithmic
frameworks for addressing complex high-dimensional geometric problems arising, at
different scales, in the physical world. The challenges of physical computing will
be highlighted as well as the opportunities to impact molecular biology and
medicine.

Hansen

0681-9325 691

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