Kate Larson is an acclaimed AI (Artificial Intelligence) researcher whose work focuses on multi-agent systems and brings together computer science, mathematics, and economics.

As the daughter of a biology professor at Memorial University in Newfoundland, Kate thought she might like to study biology. “The trouble was that everyone in the department knew me as Katie, my father’s daughter,” she says. A very good course in first-year mathematics sparked her interest and led her to major in the subject as an undergraduate at Memorial.

Kate received an NSERC Undergraduate Research Award, and it was Sherry Mantyka, her supervisor for the research project that she conducted related to the award, who encouraged Kate to attend graduate school. She explains, “Sherry was very supportive and an important mentor. She submitted my project, which was on math and cognitive science, to a research conference. That was a really big deal!”

When looking at options for graduate school, Kate initially considered math programs in Canada, but was intrigued by the advice given by a researcher she met at a conference to study computer science in the United States. “I chose to focus on a field I knew nothing about in a place that was unfamiliar to me,” says Kate.

Kate earned a Masters’ degree in Computer Science at Washington University in St. Louis and went on to complete her PhD in Computer Science at Carnegie Mellon University in Pittsburgh. Committee members for her thesis dissertation, Mechanism Design for Computationally Limited Agents, included computer scientists and a microeconomic theorist, exemplifying the multi-disciplinary nature of her research.

Kate’s research focuses on multiagent systems and reinforcement learning and applications of AI to support sustainable development and climate-related initiatives. She is especially interested in research challenges that emerge when cooperation is made the heart of AI systems. Issues associated with cooperation are pervasive and important and can be found at scales ranging from daily routines like driving on highways, scheduling meetings and working collaboratively, to global challenges like peace, commerce, and pandemic preparedness. With AI-powered machines playing an increasingly greater role in our lives, it will be important to equip them with the capabilities necessary to cooperate and foster cooperation.

Kate’s work has earned her a Province of Ontario Early Researcher Award, the Canadian Association of Computer Science/Association d’informatique canadienne (CACS/AIC) Outstanding Young Researcher Prize, a University of Waterloo Research Chair and the Pasupalak AI Fellowship. She currently splits her research time as a Professor in the Cheriton School of Computer Science at the University of Waterloo, and as a Research Scientist at DeepMind in Montreal.

Kate’s role as a researcher and professor has included serving as graduate student supervisor and PhD thesis examiner and committee member for many students during the 20 years she has been on faculty at the University of Waterloo. She is also an active member of the university community, acting as Director of Undergraduate Studies for the Cheriton School of Computer Science during the COVID pandemic and as a member of the University Senate representing the Faculty of Mathematics. Kate has also been active in outreach activities to female high school students and in events for university students to promote Computer Science as a career option for women. 

The international scientific community has benefitted from Kate’s expertise in her roles as a member of the International Joint Conferences on Artificial Intelligence (IJCAI) Board of Trustees Board, program chair for the IJCAI 2024 conference, and member of the Computing Research Association (CRA) and CS-Can|Info-Can Boards of Directors. She is Co-Editor-in-Chief of the Journal of Autonomous Agents and Multiagent Systems, and has served as Associate Editor and member of the editorial board for a range of AI scientific journals.

Kate strongly believes that the advancement of AI will benefit greatly from collaborative research that incorporates a diversity of ideas and backgrounds, leading to the consideration of a range of interesting questions. “Issues affecting those with lower incomes, women, and minority populations need to be addressed in AI research. A homogenous group of researchers will develop tools to solve a narrow set of problems,” notes Kate. Kate Larson’s research on cooperation in AI, her emphasis on diversity and interdisciplinary research teams, and her work in both academia and industry are leading the way to machines learning to find common ground to address a wide range of global challenges.