Dr. Lydia E. Kavraki ’s list of accomplishments , accolades , and titles is almost too much to serve — the computer scientist is currently the Noah Harding Professor of Computer Science and Bioengineering at Rice University , but she also hold an assignment at the Department of Structural and Computational Biology and Molecular Biophysics at the Baylor College of Medicine in Houston , in addition to sit down on a number of advisory boards for various publications , holding fellowships and memberships at a whole mess of connection and institutions , and running her own lab at Rice . It may sound a bit dry , until you actualise what Kavraki ’s employment lie in of : She makes robot work . It ’s not spoiled oeuvre if you may get it ( or , alternately , you ’re splendid enough to do it ) .
Kavraki ’s work is incredibly complex ( to put it gently ) , but her robotics work essentially boils down to path planning for automaton — have sure they have a collision - spare course to stick with . Her method acting , the Probabilistic Roadmap Method ( PRM ) , is hailed for providing a paradigm slip across the robotics community , as it utilizes randomizing and sample - based motion planners to path program , a simpler technique than had been antecedently used ( one that meant that all applicable track outer space had to be search and taken into account statement ) . Kavraki also helped write the volume on the matter — literally : HerPrinciples of Robot Motionis the preeminent textbook on the subject . She also spring up the Open Motion Planning Library , part of the Robot Operating System , which is cite to as “ the Unix of robotics”—it ’s that all-important to modern robotic movement . Kavraki ’s research is highly applicable across all sorts of robotics , let in previously unsolvable problems like how to dock an airspace shuttle to an orbiting space station and “ teach ” robot how to tie knots when suturing in a surgical environment .
Kavraki ’s expertise also widen to the cosmos of bioinformatics , and her work there go for to the structure and tractableness of corpuscle , just in case she did n’t have enough to do already .
In 2000 , Kavraki won the Association for Computing Machinery ( ACM ) Grace Murray Hopper Award for her expert contributions , an incredibly special awarding that only goes to a estimator professional person who make a unmarried , significant technical or service share at or before age 35 . ( How special ? On five social occasion , the award was n’t given out ; their criterion are just that in high spirits . ) She ’s also make a Sloan Fellowship , an NSF CAREER laurels , realization as a top youthful detective from the MITTechnology Reviewmagazine , a “ Brilliant 10 ” designation fromPopular Science , and a 2002 inclusion fromTechnology Reviewon one-year list of 35 innovators under the age of 35 , just to keep things interesting ( and lauded ) .
For now , Kavraki carry on to teach at Rice University , with her own Kavraki Lab bent on research the two prongs of her scientific interests : robotics andbioinformatics and biomedicine . By all accounts , Kavraki ’s brilliance in the lab translates to the classroom , as she is a receiver of Rice ’s own Duncan Award for excellency in research and instruction . Kavraki ’s commitment to the advance of not only her research , but her students and skill in general , is vindicated enough already , though attractively minimized with one personal line of credit on her Rice website linking out to still more accomplishment and awards , those of others dear to her , reading simply , “ I am most proud of the accomplishments and awards of my student . ”
