Katie Kowal

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.