Guest Professor, IIT Gandhinagar
Professor, Northeastern University, Boston, MA
(Joint) Chief Scientist, Pacific Northwest National Laboratory, Richland, WA
BTech (Hons.): IIT Kharagpur, 1993
MS: University of Toledo, Ohio, 1997
PhD: Massachusetts Institute of Technology, 2002
Email: a.ganguly@northeastern.edu
Research Interests: Climate Risks, Infrastructure Resilience, Machine Learning, Nonlinear Dynamics
Prof Ganguly’s research intersects weather and hydrologic extremes under climate change, lifeline infrastructures resilience under compound extremes, as well as machine learning and nonlinear physics. Ganguly’s research domains include urban sustainability (e.g., initial ~25 min of this National Academies presentation) and climate change (e.g., this NSF news and this Nature highlight), as well as spatiotemporal machine learning (e.g., see Fig 2b of this Nature Perspective and this Nature commentary) and network science for lifeline infrastructure (e.g., this DoD SERDP video).
Lab
Sustainability and Data Sciences Laboratory: https://sdslab.io/
Startup Company: https://www.risq.io/
Research Publications
Ganguly, A.R. and colleagues, 2021. Science-integrated Artificial-intelligence for Flooding and precipitation Extremes (SAFE) (No. AI4ESP1047). AI4ESP: White Paper, US DOE BER Call. AI4ESP and US DOE.
Kodra, E., Bhatia, U., Chatterjee, S., Chen, S. and Ganguly, A.R., 2020. Physics-guided probabilistic modelling of extreme precipitation under climate change. Scientific Reports, 10, 10299.
Yadav, N., Chatterjee, S. and Ganguly, A.R., 2020. Resilience of urban transport network-of-networks under intense flood hazards exacerbated by targeted attacks. Scientific Reports, 10, 10350.
Konduri, V.S., Kumar, J., Hargrove, W.W., Hoffman, F.M. and Ganguly, A.R., 2020. Mapping crops within the growing season across the United States. Remote Sensing of Environment, 251, 112048.
Bhatia, U., Sela, L. and Ganguly, A.R., 2020. Hybrid method of recovery: combining topology and optimization for transportation systems. Journal of Infrastructure Systems, 26(3), 04020024.
Bhatia, U. and Ganguly, A.R., 2019. Precipitation extremes and depth-duration-frequency under internal climate variability. Scientific Reports, 9, 9112.
Duffy, K., Vandal, T., Li, S., Ganguly, S., Nemani, R. and Ganguly, A.R., 2019. DeepEmSat: Deep Emulation for Satellite Data Mining. Frontiers in Big Data, 2, 42.