PNNL

Auroop Ratan Ganguly works in machine learning and nonlinear dynamics, as well as in extreme value theory and network science, for challenges pertaining to the sciences of water, weather, and earth systems, and the resilience of infrastructures, transportation, water systems, and cities. He has developed process knowledge integrated Artificial Intelligence (A.I.) methods across a wide range of domains. Ganguly has 27+ years of full-time experience in the U.S. spanning the private industry, government labs, and academia. With his current and former PhD students, he has launched multiple startups, one of which has been successfully sold off to a Fortune 500 company that owns the New York stock exchange. He is a Fellow of the American Society of Civil Engineers, a Distinguished Member of the Association for Computing Machinery, a PhD from the Massachusetts Institute of Technology, and a B.Tech. (Hons.) from the Indian Institute of Technology Kharagpur. He directs the Sustainability and Data Sciences Laboratory (SDS Lab) at Northeastern University in Boston, Massachusetts, and a focus area within their Institute for Experiential A.I..

Ganguly is a joint appointee as a Chief Scientist within the Advanced Computing, Mathematics, and Data Division at the Pacific Northwest National Laboratory.

• Nonlinear Dynamics and Machine Learning
• Hybrid Real-World Physics-AI Systems
• Infrastructure Resilience to Compound Extremes
• Natural Hazards Risk Assessment
• Weather Analytics for Extremes and Uncertainty
• National and Homeland Security 

• PhD in Civil and Environmental Engineering, Massachusetts Institute of Technology, 2002
• MS in Civil Engineering, University of Toledo, 1997
• BTech in Civil Engineering, Indian Institute of Technology, 1993

• Fellow, American Society of Civil Engineers
• Distinguished Member, Association for Computing Machinery
• Senior Member, IEEE

• Northeastern University College of Engineering Distinguished Professor (2023)
• Northeastern University Constantinos Mavroidis Translational Research Award (2021)
• Invited Panelist, US National Academies Workshop: Machine Learning/Artificial Intelligence for Earth System Science
• Invited Keynote, US National Academies Workshop: Data, Models, Urban Sustainability
• Invited Panelist, National Academies Workshop: Machine Learning/Artificial Intelligence for Earth System Science (2022)
• Invited Keynote, National Academies Workshop: Data, Models, Urban Sustainability (2019)
• Environmental Research Letters (ERL) Highlights of 2015, for ERL paper (2015)
• Outstanding Reviewer, ASCE (2011)
• Faculty Fellow, Northeastern University, College of Engineering (2011)
• Best Student Paper Award, SIAM Data Mining (2011)
• AGU Editor’s Pick for Geophysical Research Letters journal paper, AGU (2011)
• Outstanding Joint/Adjunct/Research Faculty Award, University of Tennessee, Knoxville (2010)
• Significant Event and Exceptional Mentoring Awards, Oak Ridge National Laboratory (2009)
• Exceptional Mentoring Award, ORNL (2009)
• Significant Event Award, ORNL (2008-2010)
• Outstanding Mentoring Award, ORNL (2006, 2008)
• Selfless Mentoring Award, ORNL (2006)

2020

• Yadav N, S Chatterjee, and A Ganguly. 2020. "Resilience of Urban Transport Network-of-Networks under Intense Flood Hazards Exacerbated by Targeted Attacks." Scientific Reports 10, no. 2020:10350. PNNL-SA-153287. doi:10.1038/s41598-020-66049-y

2019

• Visweswara Sathanur A, B Sripimonwan, M Halappanavar, S Chatterjee, A Ganguly, and K Clark. 2019. "Identification of Critical Airports from the Perspective of Delay and Disruption Propagation in Air Travel Networks." In IEEE International Symposium on Technologies for Homeland Security (HST 2019), November 5-6, 2019, Woburn, MA, 1-6. Piscataway, New Jersey:IEEE. PNNL-SA-147072. doi:10.1109/HST47167.2019.9032999

2018

• Bhatia U., S. Chatterjee, A.R. Ganguly, J. Gao, M. Halappanavar, M.R. Oster, and K. Clark, et al. 2018. "Aviation Transportation, Cyber Threats, and Network-of-Networks: Modeling Perspectives for Translating Theory to Practice." In IEEE International Symposium onTechnologies for Homeland Security (HST 2018), October 23-24, 2018, Woburn, MA, 1-7. Piscataway, New Jersey:IEEE. PNNL-SA-134574. doi:10.1109/THS.2018.8574123