Ganguly leads Artificial Intelligence section for US Climate Assessment
CEE Professor Auroop Ganguly, the PI of the Sustainability and Data Science Laboratory (SDS Lab), is the lead author of the Artificial Intelligence section in the Climate Adaptation chapter of the upcoming Sustained National Climate Assessment report for the United States. Ganguly has published extensively on climate extremes, machine learning in climate, and climate adaptation. His students and research associates who have co-published with him in these areas include (in alphabetical order) Udit Bhatia, Kevin Clark, Debasish Das, Babak Fard, Poulomi Ganguli, Hanieh Hassanzadeh, Shih-Chieh Kao, Evan Kodra, Devashish Kumar, Esther Parish, Karsten Stenhaeuser, Thomas Vandal, and Daiwei Wang, while others including Lindsey Bressler, Kate Duffy, Shashank Konduri, Amina Ly, Rachindra Mawalagedara, Omitaomu Omitaomu, Bharat Sharma, and Lizzy Warner have contributed in various ways. Ganguly’s collaborators over the years in these areas have included colleagues from across colleges at Northeastern University and across divisions at the Oak Ridge National Laboratory, as well as the University of Minnesota, the University of Notre Dame, NASA Ames, the Indian Institutes of Technology (Bombay, Gandhinagar, and Kharagpur campuses), Temple University, US DOE’s ARPA-E, risQ Inc., the City of Boston and the Town of Brookline, while collaborative support and/or funding in these areas have been provided by (besides Northeastern and Oak Ridge), among others, the National Science Foundation, NASA Ames, the Department of Energy, the Massachusetts Port Authority, the City of Boston, the Department of Homeland Security, and the Department of Defense. Recently, one Nature commentary highlighted an award winning paper on Deep Learning for statistical downscaling led by the SDS Lab, which was developed in collaboration with NASA Ames and risQ Inc., while one Nature news article highlighted a joint work on climate networks led by the University of Minnesota. Ganguly was the lead editor a few years back of a journal special issue dedicated to physics-driven data mining in climate and weather.