I am an associate professor at the Department of Geophysical Sciences and Committee of Computational and Applied Mathematics. Before joining UChicago, I was a tenured associate professor at Rice University. I received my Ph.D. (geophysical turbulence) and M.A. (applied mathematics) from UC Berkeley in 2013 and was a Ziff Environmental Fellow at the Harvard University Center for the Environment and Department of Earth and Planetary Sciences from 2013 to 2016. I received a CAREER Award from NSF in 2021 and a Young Investigator Award from the Office of Naval Research in 2020.

I lead the Climate Extremes Theory and Data (CeTD) group focused on integrating theory, simulations, observations, and machine learning techniques to understand the dynamics and future changes of extreme weather events in a changing climate.

Dr. Jiwen Fan is the Deputy Division Director and Senor Earth Scientist of the Environmental Science Division. She also holds a joint appointment as a senior scientist at University of Chicago. She is a Fellow of American Meteorological Society (AMS).

Dr. Fan’s research encompasses atmospheric chemistry and aerosols, cloud physics, convective systems, severe weather, aerosol-precipitation-climate interactions, land-atmosphere interactions, and human-earth system interactions. Her primary foci in recent years include the impacts of environmental (e.g., urbanization, anthropogenic aerosols, wildfires) and climate change on convective storms and weather hazards and model developments of cloud microphysics and aerosol-cloud interactions.

Pertaining to AICE, she has been working with data scientists to develop machine learning models for predicting precipitation and hail, analyzing observational data, and building ML emulators for complex cloud microphysical processes.

Dr. Ian Foster is Senior Scientist and Distinguished Fellow, and also director of the Data Science and Learning Division, at Argonne National Laboratory, and the Arthur Holly Compton Distinguished Service Professor of Computer Science at the University of Chicago. Ian received a BSc degree from the University of Canterbury, New Zealand, and a PhD from Imperial College, United Kingdom, both in computer science. His research deals with distributed, parallel, and data-intensive computing technologies, and innovative applications of those technologies to scientific problems in such domains as materials science, climate change, and biomedicine. Foster is a fellow of the AAAS, ACM, BCS, and IEEE, and an Office of Science Distinguished Scientists Fellow.

In his research,  he seeks to develop tools and techniques that allow people to use high-performance computing technologies to do qualitatively new things. This involves investigations of parallel and distributed languages, algorithms, and communication; and also focused work on applications. He is particularly interested in using high-performance networking to incorporate remote compute and information resources into local computational environments.

Amir Jina is an Assistant Professor at Harris Public Policy. Amir’s research focuses on the role of the environment in shaping how societies develop. This research combines economics with methods from climate science and remote sensing to understand the impacts of climate, and has involved fieldwork on climate change adaptation with communities in India, Bangladesh, Kenya, and Uganda.

Amir is a founding member of the Climate Impact Lab – researching the socioeconomic impacts of climate change around the world – and scientific advisor to the Innovation Commission on Climate Change, Food Security, and Agriculture – promoting the use of weather services for climate change adaptation in low-income countries

Amir received a Ph.D. in Sustainable Development and M.A. in Climate and Society both from Columbia University, B.A.s in Mathematics and Theoretical Physics from Trinity College, Dublin, and previously worked with the Red Cross/Red Crescent in South Asia.

Prof. Shaw’s research focuses on the physics of the atmosphere and climate system past, present and future. She seeks to understand the underlying mechanisms controlling the response to climate changes so that we can have greater confidence in future projections. Her approach combines theory (primarily conservation laws), numerical modeling across a hierarchy of complexity and observational data analysis. Prof. Shaw is excited to take advantage of AI/ML tools for increasing our understanding and prediction of the impacts of climate change. She is working to ensure these methods get the right answer for the right reasons.

Robert Rosner is a theoretical physicist, on the faculty of the University of Chicago since 1987, where he is the William E. Wrather Distinguished Service Professor in the departments of Astronomy & Astrophysics and Physics, as well as in the Enrico Fermi Institute and the University of Chicago Harris School of Public Policy. He served as Argonne National Laboratory’s Chief Scientist and Associate Laboratory Director for Physical, Biological and Computational Sciences (2002–2005), and was Argonne’s Laboratory Director from 2005 to 2009; he was the founding chair of the U.S. Department of Energy’s National Laboratory Directors’ Council (2007–2009). His degrees are all in physics (BA, Brandeis University; PhD, Harvard University). He was elected to the American Academy of Arts and Sciences in 2001, and to the Norwegian Academy of Science and Letters (as a Foreign Member) in 2004; he is also a Fellow of the American Physical Society. Most of his scientific work has been related to fluid dynamics and plasma physics problems, as well as in applied mathematics and computational physics, especially in the development of modern high-performance computer simulation tools, with a particular interest in complex systems (ranging from astrophysical systems to nuclear fission reactors). Within the past few years, he has been increasingly involved in energy technologies, and in the public policy issues that relate to the development and deployment of various energy production and consumption technologies, including especially nuclear energy, the electrification of transport, and energy use in urban environments. He is the founding director of the Energy Policy Institute at the University of Chicago (EPIC), located at the University of Chicago Harris School of Public Policy and Booth School of Business.

Rick Stevens is the Associate Laboratory Director of the Computing, Environment and Life Sciences Directorate at Argonne National Laboratory, and a Professor of Computer Science at the University of Chicago, with significant responsibility in delivering on the U.S. national initiative for Exascale computing and developing the DOE initiative in Artificial Intelligence (AI) for Science.

At Argonne, he is leading the Laboratory’s AI for Science initiative and currently focusing on high-performance computing systems which includes leading a significant collaboration with Intel and Cray to launch Argonne’s first exascale computer, Aurora 21, which will pursue some of the farthest-reaching science and engineering breakthroughs ever achieved with supercomputing, as well as a partnership with Cerebras Systems to bring hardware on site to advance the massive deep learning experiments being pursued at Argonne for basic and applied science and medicine with supercompute-scale AI.

Prof. Stevens is a member of the American Association for the Advancement of Science and has received many national honors for his research, including an R&D 100 award.

Rebecca Willett is a Worah Family Professor in the Wallman Society of Fellows and the Departments of Statistics and Computer Science at the University of Chicago. She completed her PhD in Electrical and Computer Engineering at Rice University in 2005 and was an Assistant then tenured Associate Professor of Electrical and Computer Engineering at Duke University from 2005 to 2013. She was an Associate Professor of Electrical and Computer Engineering, Harvey D. Spangler Faculty Scholar, and Fellow of the Wisconsin Institutes for Discovery at the University of Wisconsin-Madison from 2013 to 2018.  Prof. Willett received the National Science Foundation CAREER Award in 2007, was a member of the DARPA Computer Science Study Group 2007-2011, and received an Air Force Office of Scientific Research Young Investigator Program award in 2010. Prof. Willett has also held visiting researcher positions at the Institute for Pure and Applied Mathematics at UCLA in 2004, the University of Wisconsin-Madison 2003-2005, the French National Institute for Research in Computer Science and Control (INRIA) in 2003, and the Applied Science Research and Development Laboratory at GE Medical Systems (now GE Healthcare) in 2002. Her research interests include network and imaging science with applications in medical imaging, wireless sensor networks, astronomy, and social networks. She is also an instructor for FEMMES (Females Excelling More in Math Engineering and Science; news article here) and a local exhibit leader for Sally Ride Festivals. She was a recipient of the National Science Foundation Graduate Research Fellowship, the Rice University Presidential Scholarship, the Society of Women Engineers Caterpillar Scholarship, and the Angier B. Duke Memorial Scholarship.

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Tiana Pyer-Pereira

Research Administrator, Willett Research Group

tianap@uchicago.edu

Bing Gong is a research scientist at the Data Science Institute of the University of Chicago. Her research focuses on developing state-of-the-art, scalable deep learning neural networks in weather prediction applications. Prior to joining the University of Chicago, Bing Gong held a position as an assistant professor at Shanghai Normal University in China and was a postdoctoral researcher at the Jülich Supercomputing Center in Germany. She obtained her Ph.D. in the field of artificial intelligence in the application of environmental science and energy from the Technical University of Madrid, Spain, in July 2017.

Research focus: Deep learning for Earth Systems,  weather prediction

Jessica Wan is a Postdoctoral Research Associate in the Climate Systems Engineering initiative at The University of Chicago. Her research aims to understand how climate engineering proposals might reduce regional climate impacts by combining interdisciplinary analysis frameworks and modeling tools ranging from global climate models to AI emulators.

Prior to joining UChicago, Jessica received her Ph.D. in Earth Sciences from Scripps Institution of Oceanography at the University of California San Diego where her work focused on modeling the effects to regional marine cloud brightening. While completing her graduate degree, Jessica was a National Defense Science and Engineering Graduate fellow and an Achievement Rewards for College Scientists scholar. She also holds a B.S. in Environment & Sustainability from Cornell University.

Katie Kowal is the Director of AI for Weather at the Data Science Institute, working closely with the Climate Extremes Theory and Data (CeTD) group led by Professor Pedram Hassanzadeh in the Geophysical Sciences Department and the Human Centered Weather Forecasts Initiative (HCWF). She manages large interdisciplinary projects, conducts research on AI forecasts at weather and subseasonal timescales, and supports strategic planning across multiple initiatives. As part of HCWF, she coordinates research and operational teams to help bridge the gap between AI advances in weather and subseasonal-to-seasonal forecasting and their practical usefulness for decision-makers in low- and middle- income countries. Previously, as the Weather Forecast Lead for the Human Centered Weather Forecasts Initiative Indian Monsoon Onset project, she managed the operational deployment of the Indian monsoon onset forecasts in 2025 and led curriculum development for AIM for Scale’s first AI weather training program. 

Prior to coming to the University of Chicago, she was a scientist at the National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center International Desk, supporting multiple national meteorological services in Latin America and the Pacific Islands with operational forecasts, training, and research on improving subseasonal to seasonal forecasts. Katie holds a DPhil in Hydrology and an MSc in Environmental Change and Management from the University of Oxford as a Rhodes Scholar and a BA in Physics and Political Science from Lewis & Clark College. Earlier in her career, she was a science policy fellow at the Science and Technology Policy Institute, supporting the White House Office of Science and Technology Policy to develop national policy on regulating nuclear space launch approvals and improving critical infrastructure resilience to extreme events including space weather.

Ozma Houck is a PhD Student at the Harris School of Public Policy. Ozma’s research focuses on understanding how innovations in weather forecasting can be used to increase climate adaptation and accelerate the transition to renewable energy. Her work leverages traditional economic methods alongside tools from climate science and machine learning to study the socioeconomic impacts of climate and weather. Ozma received B.A.s in Mathematics and Economics from Carleton College. She previously worked as a research professional at the Booth School of Business.

Rajat Masiwal is a postdoctoral scholar in the Department of Geophysical Sciences at the University of Chicago. His research focuses on improving sub-seasonal forecasts by integrating artificial intelligence with dynamical models. He earned his Ph.D. from the Indian Institute of Science, Bangalore, where he investigated the dynamics of the Indian monsoon using observations, theory, and idealized modeling.

His broader interests include understanding climate system processes through a hierarchy of models, combining physics-based approaches with emerging AI techniques. Additionally he maintains an active interest in the meteorology of renewable energy resources, such as wind and solar, and how better forecasting of these can support a transition to a decarbonized electricity grid