Chris Maddison

Chris Maddison is an Assistant Professor in the Department of Computer Science and the Department of Statistical Sciences at the University of Toronto. He serves as a CIFAR AI Chair at the Vector Institute, a member of the ELLIS Society, and a faculty affiliate of the Schwartz Reisman Institute for Technology and Society. His research focuses on machine learning methodology, particularly gradient estimation techniques and AI applications in natural sciences, such as drug discovery and causal inference. Maddison previously held positions at Google DeepMind and the Institute for Advanced Study in Princeton, NJ, and earned his DPhil from the University of Oxford.

• Education: DPhil in Computer Science, University of Oxford
• Affiliations: University of Toronto, Vector Institute, ELLIS Society, Schwartz Reisman Institute

Maddison’s group works on methods for AI in drug discovery, causal inference, and scaling dynamics, with publications in top machine learning conferences (NeurIPS, ICML, ICLR). He developed gradient estimation techniques now standard in deep learning and co-founded the AlphaGo project at DeepMind.

• NeurIPS Best Paper Award 2014
• Open Philanthropy AI Fellow
• CIFAR AI Chair

His lab includes PhD students Nikita Dhawan, Honghua Dong, Haonan Duan, Ayoub El Hanchi, Chuning Li, Yangjun Ruan, and Anvith Thudi. Former members include Dami Choi, Daniel Johnson, and Max Paulus. He teaches courses on large models, statistical methods for machine learning, and machine learning fundamentals.