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 is 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. He completed his DPhil at the University of Oxford. Chris previously held a senior research scientist position at Google DeepMind and a membership at the Institute for Advanced Study in Princeton, NJ. He received the Corcoran Memorial Prize for his Oxford thesis, and has received a number of paper awards at the top machine learning conferences. Chris works on the methodology of machine learning with the goal of designing algorithms that can learn to make good predictions in stubbornly complex settings like medicine or drug discovery. Chris is internationally recognized for his gradient estimation techniques, which are now standard tools in the deep learning toolbox, and for his role as a founding member of the AlphaGo project, which was the first computer program to defeat a world champion in the game of Go.

AI2050 Project

AI has revolutionized how computers process language and images, but it has yet to deliver on its promise in drug discovery — where developing a single drug costs billions and takes over a decade. The fundamental problem is signal scarcity: the most valuable scientific data is scarce and expensive to verify. Maddison’s project develops new AI methods to begin addressing this: tools to represent diverse scientific measurements in a common format, simpler architectures that scientists can adapt, and a molecular structure predictor that trains jointly on all available data. Together, these advances can help accelerate the discovery of new medicines.