Lydia Kavraki

ACM has named Lydia E. Kavraki of Rice University and Daphne Koller of Stanford University and Insitro recipients of the ACM - AAAI Allen Newell Award.

Lydia Kavraki is recognized for pioneering contributions to robotic motion planning, including the invention of randomized motion planning algorithms and probabilistic roadmaps, with applications to bioinformatics and biomedicine.

Kavraki conducted foundational work on physical algorithms and developed efficient high-dimensional search frameworks that impacted robotics (motion planning, hybrid systems, formal methods in robotics, assembly planning, and micro- and flexible manipulation), as well as computational structural biology, translational bioinformatics, and biomedical informatics.

Kavraki has authored more than 240 peer-reviewed publications and is a co-author of the widely used robotics textbook, Principles of Robot Motion. Her seminal paper, “Probabilistic Roadmaps for Path Planning in High Dimensional Configuration Spaces,” (with Svestka, Latombe and Overmars) was the first to establish a probabilistic approach to developing roadmaps for high-dimensional spaces, which has become one of the key techniques for motion planning for complex physical systems.

Kavraki’s contributions go beyond robotics to address problems underlying the functional annotation of proteins, the understanding of metabolic networks, and the investigation of molecular conformations and protein flexibility. She has contributed to problems that involve reasoning about the three-dimensional structure of biomolecules and their ability to interact with other biomolecules primarily for drug design and, more recently, for personalized cancer immunotherapy.

Daphne Koller is recognized for seminal contributions to machine learning and probabilistic models, the application of these techniques to biology and human health, and for contributions to democratizing education.

Koller was a leader in the development and use of graphical models, including learning the model structure as well as its parameters, and pioneered the unification of statistical learning and relational modelling languages. She also developed foundational methods for inference and learning in temporal models. Her textbook (with Nir Friedman), Probabilistic Graphical Models, is the definitive text in this area.

As an early leader in bringing machine learning methods to the life sciences, she developed Module Networks, wherein she and her colleagues harnessed modularity in gene regulatory programs to build an effective model of gene activity. She has developed groundbreaking applications of machine learning to pathology, work that not only demonstrated the ability of machine learning to outperform human pathologists, but also was one of the first to highlight the importance of the stromal tissue in cancer prognosis (now well-recognized).

Koller is also the co-founder and former co-CEO of Coursera, a platform offering free education from top universities to people worldwide. Coursera, now in its eighth year, has touched the lives of over 50 million learners in every country in the world. Koller is currently the founder and CEO of Insitro, a biotech startup that works to discover better medicines through the integration of machine learning and biology at scale.

ACM named Lydia E. Kavraki of Rice University as the 2017-2018 Athena Lecturer. Kavraki was cited for the invention of randomized motion-planning algorithms in robotics and the development of robotics-inspired methods for bioinformatics and biomedicine. Kavraki is an internationally recognized leader in developing physical algorithms, an area that addresses the computational challenges of objects moving in space while subject to physical constraints. She has made significant contributions in an impressively wide range of areas, from how a robot might move through a course of obstacles, to how a drug molecule might change its shape to interact with a target protein, to her current work with planning the motions of Robonaut 2, NASA’s robotic assistant at the International Space Station.

Initiated in 2006 by the ACM Council on Women in Computing (ACM-W), the Athena Lecturer Award celebrates women researchers who have made fundamental contributions to computer science. The award carries a cash prize of $25,000, with financial support provided by Google. The Athena Lecturer is invited to present a lecture at an ACM event. The award is named after Athena, the Greek goddess of wisdom. With her knowledge and sense of purpose, Athena epitomizes the strength, determination, and intelligence of the "Athena Lecturers." 

“Planning the motion of objects in a three-dimensional space has been a central challenge in the robotics field for a long time,” said ACM President Vicki L. Hanson. “Lydia Kavraki’s Probabilistic Roadmap Method has had a tremendous impact. It is now widely used in robotics applications in industry and is a foundational idea for numerous researchers in the field. She was then able to transfer the insights she discovered in robotics to bioinformatics and biomedicine, where she has also made important advances. Although Kavraki is being recognized with the Athena Lecturer Award for her research contributions, she has also been a generous mentor and strong role model for younger colleagues, especially women. In this way, her career exemplifies the award’s overarching goal of celebrating and supporting women in computing.”

Kavraki’s 1996 doctoral dissertation proposed the Probabilistic Roadmap Method (PRM), a technique to plan the motion of robots, which had been an enduring challenge in the field. The Probabilistic Roadmap Method was immediately hailed for its simple implementation and its ability to scale (that is, return reliable results when applied to increasingly large datasets). PRM and the subsequent advances on the original approach are now included as a fundamental tenet of motion planning in most robotics textbooks. Additionally, to aid in the dissemination of her research, Kavraki spearheaded an open source Open Motion Planning Library. The library has been used in more than 30 different robotics systems, and continues to receive new contributions from around the world.

Kavraki was also the first to recognize that the motion-planning techniques she was developing in robotics could be applied to great effect in biology and medicine. She wrote new algorithms for the analysis of the motion, shape and flexibility of molecules that had a major impact on computational biology, as well as many subareas, including drug discovery and design. Recently, she has been developing structural methods to identify cross-reactivity hot spots in T-cells. The project has the potential to introduce safer immunotherapy treatments for cancer patients.

In another exciting project that takes her research to new heights, Kavraki has been working with NASA on Robonaut 2 (R2), a humanoid robot with formidable mechanical capability and capacity to work in human-occupied environments. It is anticipated that R2s will help humans in spaceship inspection and maintenance, caretaking tasks in future long missions, and space exploration. The variety of ways in which the robot will need to move, as well as NASA’s hopes that R2 will perform dexterous manipulation—that is, complete delicate tasks with its hands—will require leading-edge motion-planning technology. R2 was expected to be deployed at the International Space Station later in 2017.

Lydia Kavraki will formally receive the 2017-2018 ACM Athena Lecturer Award at ACM's annual Awards Banquet on June 24, 2017 in San Francisco, California.