Daphne Koller is CEO and Founder of insitro, a machine learning-driven drug discovery and development company. Daphne was the Rajeev Motwani Professor of Computer Science at Stanford University, where she remains an Adjunct Professor. She was the co-founder, co-CEO and President of Coursera. She is the author of over 300 refereed publications, with an h-index of over 150. She was recognized as one of TIME’s 100 most influential people in 2012 and Newsweek’s 10 most important people in 2010. She is the recipient of the the ONR Young Investigator Award, the Presidential Early Career Award for Scientists and Engineers (PECASE), the IJCAI Computers and Thought Award, the MacArthur Foundation Fellowship, the ACM Prize in Computing, the ACM AAAI Allen Newell Award, the IEEE CS Women of ENIAC Computer Pioneer award and the Technical Leadership Abie Award. She is a member of the National Academy of Sciences and the National Academy of Engineering, and a fellow of the American Association for Artificial Intelligence, the American Academy of Arts and Sciences and the International Society of Computational Biology. Her teaching was recognized via the Stanford Medal for Excellence in Fostering Undergraduate Research, and as a Bass University Fellow in Undergraduate Education.

Research Interests

Daphne Koller’s core interests lie in the development of novel methods in machine learning and their use to discern patterns in complex data sets, with a particular focus on biomedical applications. She has done extensive work on probabilistic graphical models, relational learning, weakly supervised learning, active learning, and reinforcement learning. Her current focus is on the use of representation learning methods to learn the language of biology as manifested in high-content data across different biological scales, spanning from cellular systems through human clinical data. She uses these techniques to help predict the clinical impact of interventions, towards the goal of bringing better medicines to the patients who will benefit the most.

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Primary Section

Section 34: Computer and Information Sciences

Secondary Section

Section 29: Biophysics and Computational Biology