Please join us for the third talk in a special series in the UW Data Science Seminar featuring the AI@UW Seed Grant awardees. The AI@UW Seed Grant projects partner domain researchers from an applied disciplinary field with researchers specializing in AI theory and/or methodology. These projects were supported by the eScience Institute in collaboration with the Office of Research, the Paul G. Allen School of Computer Science & Engineering, the Information School, and the NSF Institute for Foundations of Data Science (IFDS). This seminar will feature John Choe, an Associate Professor at UW Industrial and Systems Engineering, and Kevin Jamieson, an Associate Professor at UW’s Allen School of Computer Science and Engineering on Thursday, February 13th from 4:30 to 5:20 p.m. PT.
The seminar will be held in Hitchcock Hall 132 – Campus Map.
“Data-Driven Optimization of Stochastic Computational Experiments: Applications in Hazard Risk Assessment”
Abstract This AI@UW seed grant project developed a domain-agnostic data-driven algorithm to optimize stochastic computational experiments under computational resource constraints. Stochastic computational experiments are ubiquitous in science, engineering, and medicine. This project focused on motivating applications in disaster management, where the proposed optimization can potentially save billions of dollars and many lives from disasters. This project’s optimal adaptive experiment design algorithm enables computationally efficient hazard risk assessment (e.g., earthquake-induced tsunamis, landslides), thereby informing decision-making for disaster risk reduction.
Biography: John Choe is an Associate Professor of Industrial and Systems Engineering at the University of Washington, Seattle. He is the Director of the Disaster Data Science Lab and the Deputy Director of the Center for Disaster Resilient Communities. He received his Ph.D. in Industrial and Operations Engineering and M.A. in Statistics from the University of Michigan, Ann Arbor. His work has been supported by the U.S. National Science Foundation, National Institute of Environmental Health Sciences, Centers for Disease Control and Prevention, and other public and private sector organizations.
Kevin Jamieson is an Associate Professor in the Paul G. Allen School of Computer Science and Engineering at the University of Washington. His research explores how to leverage already-collected data to inform what future measurements to make next, in a closed loop. His work has been recognized by an NSF CAREER award and Amazon Faculty Research award. He received his B.S. from the University of Washington, M.S. from Columbia University, and Ph.D. from the University of Wisconsin – Madison, all in electrical engineering.
The UW Data Science Seminar is an annual lecture series at the University of Washington that hosts scholars working across applied areas of data science, such as the sciences, engineering, humanities and arts along with methodological areas in data science, such as computer science, applied math and statistics. Our presenters come from all domain fields and include occasional external speakers from regional partners, governmental agencies and industry.
The 2024-2025 seminars will be held in person, and are free and open to the public.