Appendix B: Planning Committee Biographies

L. Ruby Leung (Chair) is a Battelle Fellow at Pacific Northwest National Laboratory. Her research broadly cuts across multiple areas in modeling and analysis of climate and water cycle including orographic precipitation, monsoon climate, extreme events, land surface processes, land-atmosphere interactions, and aerosol-cloud interactions. Leung is the chief scientist of the U.S. Department of Energy’s (DOE’s) Energy Exascale Earth System Model, a major effort to develop state-of-the-art capabilities for modeling human-Earth system processes on DOE’s next generation high-performance computers. She has organized several workshops sponsored by DOE, the National Science Foundation, the National Oceanic and Atmospheric Administration, and the National Aeronautics and Space Administration to define gaps and priorities for climate research. She currently serves as a member of the Board on Atmospheric Sciences and Climate of the National Academies of Sciences, Engineering, and Medicine and as an editor of the American Meteorological Society (AMS) Journal of Hydrometeorology. She has published more than 425 papers in peer-reviewed journals. Leung is an elected member of the National Academy of Engineering and Washington State Academy of Sciences and a fellow of AMS, the American Association for the Advancement of Science, and the American Geophysical Union (AGU). She is the recipient of the AGU Global Environmental Change Bert Bolin Award and Lecture in 2019, the AGU Atmospheric Science Jacob Bjerknes Lecture in 2020, DOE Distinguished Scientist Fellow in 2021, and the AMS Hydrologic Sciences Medal in 2022.

Ann Bostrom is the Weyerhaeuser Endowed Professor in Environmental Policy in the Evans School of Public Policy & Governance at the University of Washington. She studies risk perception with a focus on mental models of hazardous processes, risk and science communication, and decision making under uncertainty. Dr. Bostrom is a fellow of the American Association for the Advancement of Science (AAAS) and of the Washington State Academy of Sciences (WSAS), and a fellow and former president of the Society for Risk Analysis. She is also currently serving as an elected board member for both AAAS and WSAS. She is a member of the leadership team and co-leads risk communication research in the National Science Foundation-funded AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography (AI2ES), and is a co-principal investigator of the Cascadia CoPes Hazards Research Hub. Dr. Bostrom completed postdoctoral studies in cognitive aspects of survey methodology at the Bureau of Labor Statistics, and in engineering and public policy at Carnegie Mellon University, after earning her Ph.D. there in policy analysis. She also holds an M.B.A. from Western Washington University and a B.A. in English from the University of Washington. She is currently serving as a member of the national Advisory Committee on Earthquake Hazards Reduction.

Patrick Heimbach is a computational oceanographer and W. A. “Tex” Moncrief, Jr., Chair III in Simulation-Based Engineering and Sciences at the University of Texas at Austin. His research focuses on ocean and ice dynamics and their role in the global climate system. He is an expert on the use of inverse methods applied to ocean and sea ice model parameter and state estimation, uncertainty quantification, and observing system design. Heimbach earned his Ph.D. in 1998 from the Max-Planck-Institute for Meteorology and the University of Hamburg, Germany. Among his professional activities, Heimbach serves on the National Academies of Sciences, Engineering, and Medicine’s Ocean Studies Board; the National Science Foundation’s Advisory Committee for

the Office of Polar Programs; the CLIVAR/CliC Northern Ocean Regional Panel; and the U.S. CLIVAR Ocean Uncertainty Quantification working group.

Amy McGovern is the Lloyd G. and Joyce Austin Presidential Professor in the School of Computer Science and School of Meteorology at the University of Oklahoma. She is also the director of the National Science Foundation’s AI Institute for Research on Trustworthy AI in Weather, Climate, and Coastal Oceanography. Dr. McGovern’s Ph.D. is in computer science from the University of Massachusetts (2002). She also has an M.S. in computer science from the University of Massachusetts Amherst (1998) and a B.S. (honors) in math/computer science from Carnegie Mellon University (1996). She has worked in the intersection of artificial intelligence and meteorology since 2005, when she joined the University of Oklahoma as faculty. Dr. McGovern became a fellow of the American Meteorological Society in 2021.

Diego Melgar is the Ann and Lew Williams Chair of Earth Sciences and an assistant professor of geophysics in the Department of Earth Sciences at the University of Oregon. His research focuses on large earthquakes. He works on understanding the physics of faults using many diverse kinds of on-shore and off-shore data. He researches the hazards associated with these large events, working on tsunami modeling and coastal impacts, as well as studying how strong shaking can be forecast. Dr. Melgar was awarded the 2016 Charles Richter early career award from the Seismological Society of America. He is also a member of the National Academies of Sciences, Engineering, and Medicine’s Committee on Solid Earth Geophysics. Prior to joining the University of Oregon, he spent 3 years at the University of California, Berkeley’s, Seismological Laboratory. He earned his B.Eng. in geophysics from the Universidad Nacional Autónoma de México and his M.S. and Ph.D. in geophysics from the Scripps Institution of Oceanography.

Aarti Singh is an associate professor in the Machine Learning Department at Carnegie Mellon University (CMU). Her research lies at the intersection of machine learning, statistics, and signal processing, and focuses on designing statistically and computationally efficient algorithms that can interactively leverage inherent structure in the data, and its application to scientific domains. She received a B.E. in electronics and communication engineering from the University of Delhi in 1997, and an M.S. and Ph.D. in electrical engineering from the University of Wisconsin—Madison in 2003 and 2008, respectively. Dr. Singh was a postdoctoral research associate at the Program in Applied and Computational Mathematics at Princeton University, before joining CMU in 2009. Her work is recognized by a National Science Foundation (NSF) Career Award, a U.S. Air Force Young Investigator Award, A. Nico Habermann Junior Faculty Chair Award, Harold A. Peterson Best Dissertation Award, and four best student paper awards. Her service honors include serving as program chair for the International Conference on Machine Learning 2020; program chair for Artificial Intelligence and Statistics 2017 conference; associate editor for IEEE Transactions on Information Theory and IEEE Transactions on Signal and Information Processing over Networks; expert team member for The Minerals, Metals & Materials Society’s science and technology study on artificial intelligence for materials and manufacturing innovation, sponsored by the Office of Naval Research/National Institute of Standards and Technology; steering committee for NSF innovation laboratory on data-driven chemistry; and the National Academies of Sciences, Engineering, and Medicine’s Committee on Applied and Theoretical Statistics.

Laure Zanna is a professor in mathematics and atmosphere/ocean science at the Courant Institute, New York University (NYU). Her research focuses on the dynamics of the climate

system, and the main emphasis of her work is to study the influence of the ocean on local and global scales. Prior to NYU, she was a faculty member at the University of Oxford until 2019 and obtained her Ph.D. in 2009 in climate dynamics from Harvard University. She was the recipient of the 2020 Nicholas P. Fofonoff Award from the American Meteorological Society “for exceptional creativity in the development and application of new concepts in ocean and climate dynamics.” She is the lead principal investigator of the National Science Foundation-National Oceanic and Atmospheric Administration Climate Process Team on Ocean Transport and Eddy Energy, and M2LInES—an international effort to improve climate models with scientific machine learning. She currently serves as an editor for the Journal of Climate, a member on the International CLIVAR Ocean Model Development Panel, and a member of the Community Earth System Model Advisory Board.

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