Prof. Cathy Wu

Professor Wu works at the intersection of machine learning, optimization, and large-scale societal systems. Her recent research focuses on mixed autonomy systems in mobility, which studies the complex integration of automation such as self-driving cars into existing urban systems. She is interested in developing principled computational tools to enable reliable and complex decision-making for critical societal systems.

Throughout her career, Professor Wu has collaborated and worked broadly across fields, including transportation, computer science, electrical engineering, mechanical engineering, urban planning, and public policy, and institutions, including Microsoft Research, OpenAI, the Google X Self-Driving Car Team, AT&T, Caltrans, Facebook, and Dropbox. As the founder and Chair of the Interdisciplinary Research Initiative within the ACM Future of Computing Academy, she is actively building international programs to unlock the potential of interdisciplinary research in computing.

Professor Wu studies learning for control in large-scale systems. By facilitating decision making in large-scale systems, she aims to enable more sustainable cities and infrastructure. Recent work is motivated by the emerging paradigm for managing traffic by directly controlling vehicles. This has the potential to enable roadways that are not only more efficient, but also safer, healthier, and more environmentally friendly. To understand this emerging paradigm, Wu designs flexible methods for rigorously optimizing a vast range of scenarios and sustainability metrics. Such methods must cope with complexity, diversity, and scale. Professor Wu's work draws from reinforcement learning, deep learning, control, optimization, and stochastic modeling. Broadly, she is interested in applications in large-scale multi-agent systems as well as combinatorial optimization.