Lydia E. Kavraki, Ph.D.

AIMBE College of Fellows Class of 2004
For the development of pioneering robotics-engineered methods for the study of biomolecular motion, biomolecular interactions, protein folding and drug discovery.

NSF RAPID grant supports COVID-19 ‘computational pipeline’

Via Rice University | June 16, 2020

Lydia Kavraki, the Noah Harding Professor of Computer Science at Rice, has received a National Science Foundation (NSF) Rapid Response Research grant to implement a computational pipeline to help identify fragments of SARS-CoV-2 viral proteins that could be used as targets for vaccine development.

“Efforts are already underway to produce new drug inhibitors, repurpose existing drugs and devise combination treatments for COVID-19,” said Kavraki, who is also a professor of bioengineering, electrical and computer engineering and mechanical engineering… Continue reading.

Kavraki Wins Technical Leadership Award

Via Rice | September 1, 2015

Lydia Kavraki, Rice’s Noah Harding Professor of Computer Science and a professor of bioengineering, has been named the winner of the 2015 Award for Technical Leadership by the Anita Borg Institute.

The institute, which promotes the progress of women in technology, will present the award to Kavraki at the 2015 Grace Hopper Celebration of Women in Computing. Rice is a gold academic sponsor of the Oct. 14-16 event, which will bring 12,000 women technologists to Houston’s George R. Brown Convention Center.

The award recognizes women who demonstrate leadership through contributions and achievements that raise the impact of women on technology.

Kavraki, who joined Rice in 1996, continues to push the boundaries of fundamental computer science, but with her own agenda. While she and her Rice students tackle specific problems in both robotics and biomedical sciences, she wants each solution to address a bigger picture.

“We try to connect our work with current applications,” she said. “My students enjoy working on applications, but they also gain a lot by understanding that we need to develop fundamental computational methodologies for us to be able to tackle larger problems.