Auroop R Ganguly is the Principal Investigator of the Sustainability and Data Sciences Laboratory (SDS Lab) and an Associate Professor at the department of Civil and Environmental Engineering at Northeastern University.
Selected Publications: Climate Extremes
2. Ghosh, S., Das, D., Kao, S.-C., and A.R. Ganguly, (2012):Lack of uniform trends but increasing spatial variability in observed Indian rainfall extremes. Nature Climate Change 2(2), 86-91, doi:10.1038/nclimate1327. Highlighted by the National Science Foundation (Selected) News: American Meteorological Society, Science Daily, Earth Times, Deccan Herald (India)
5.Ganguly, A.R., Steinhaeuser, K., Erickson, D.J., Branstetter, M. Parish, Singh, N., Drake, J.B., and L. Buja (2009): Higher Trends but Larger Uncertainty and Geographic Variability in 21st Century Temperature and Heat Waves. Proceedings of the National Academy of Sciences of the United States of America , 106(37), 15555-15559.
Selected Publications: Hydrological Systems
2.Khan, S., Kuhn, G., Ganguly, A.R., Erickson, D.J., and G. Ostrouchov (2007): Spatio-temporal variability of daily and weekly precipitation extremes in South America. Water Resources Research, 43, W11424.
4.Khan, S.,Ganguly, A.R.,Bandyopadhyay,S.,Saigal, S., Erickson, D.J., Protopopescu, V., and G. Ostrouchov (2006): Non-linear Statistics reveals stronger ties between ENSO and the tropical hydrological cycle. Geophysical Research Letter, 33, L24402,6 PP., DOI: 10.1029/2006GL027941.
Selected Publications: Data Sciences
1.Chatterjee, S., Steinhaeuser, K., Banerjee, A., Chatterjee, S., and A.R. Ganguly (2012): Sparse Group Lasso: Consistency and Climate Applications. 2012 SIAM International Conference on Data Mining (SDM 2012), Anaheim, CA, April 26-28, 2012. Oral Presentation and Full Paper (Acceptance Rate: 15%). Best Student Paper Award at SDM 2012
2. Kawale, J., Liess, S., Kumar, A., Steinbach, M., Ganguly, A.R., Samatova, N.F., Semazzi, F., Snyder, P., and V. Kumar (2011): Data-guided discovery of climate dipoles in observations and models. 2011 NASA Conference on Intelligent Data Understanding (NASA CIDU 2011), Mountain View, CA, October 20-21, 2011. Best Student Paper Award at NASA CIDU 2012
Selected Publications: Complex Systems
1. Omitaomu, O.A., Protopopescu, V.A., and A.R. Ganguly (2011): Empirical mode decomposition technique with conditional mutual information for denoising operational sensor data. IEEE Sensors Journal, DOI: 10.1109/JSEN.2011.2142302.
3. Ganguly, A.R., Gama, J., Omitaomu, O.A., Gaber, M.M., and R.R. Vatsavai (Editors) (2009): Knowledge Discovery from Sensor Data. CRC Press, Taylor & Francis, New York: 216 pages.
5.Reyes-Aldasoro, C.C., Ganguly, A.R., Lemus, G., and A Gupta (1999): A hybrid model based on dynamic programming, neural networks, and surrogate value for inventory optimization applications. Journal of the Operational Research Society, 50(1), 85-94.