Avi Pfeffer

Avi leads Charles River’s research in a variety of computational intelligence techniques, such as probabilistic reasoning, machine learning, and computational game theory. With over 20 years of experience, Avi has led the research and development of probabilistic representation and reasoning frameworks. He developed both IBAL, the first general-purpose probabilistic programming language, and Figaro™, Charles River’s probabilistic programming language. Avi has produced systems for representing, reasoning about, and learning the beliefs, preferences, and decision-making strategies of people in strategic situations. He also invented object-oriented Bayesian networks and probabilistic relational models, which form the foundation for the statistical relational learning field. Avi serves as Action Editor of the Journal of Machine Learning Research and served as Associate Editor of Artificial Intelligence Journal and as Program Chair of the Conference on Uncertainty in Artificial Intelligence. He received his PhD in computer science from Stanford University and his BA in computer science from University of California, Berkeley.