Research
I am a Professor of Computer Science at the University of British Columbia, a Canada CIFAR AI Chair and Faculty Member at the Vector Institute, and a Senior Research Advisor at DeepMind.
Previously, I was a Research Team Leader at OpenAI. Before that I was a Senior Research Manager and founding member of Uber AI Labs, which was formed after Uber acquired a startup our startup. Prior to Uber, I was the Loy and Edith Harris Associate Professor in Computer Science at the University of Wyoming.
I conduct research in deep learning and deep reinforcement learning, including open-ended and AI-generating algorithms. I have long been interested in creating open-ended algorithms wherein AI systems could learn and truly innovate without end (as natural evolution and human culture do). To make progress, I study how intelligence evolved and what fuels human innovation, and try to harness those principles to improve our ability to produce more complex, intelligent artificial intelligence. Such work has led my colleagues and I to create and/or develop quality-diversity, open-ended, and AI-generating algorithms, which, like nature and human culture, do not seek to produce a single, best solution, but instead innovate forever to create a vast diversity of high-quality entities.
I have also worked on AI safety, AI interpretability (aka AI neuroscience), robotics, AI for science and conservation, evolutionary algorithms, and studying open questions in evolutionary biology with digital simulations of evolving systems, sometimes called digital evolution or artificial life.