Prof. Praveen Kumar holds a B.Tech. (Indian Institute of Technology, Bombay, India 1987), M.S. (Iowa State University 1989), and Ph.D. (University of Minnesota 1993), all in civil engineering, and has been on the Univ. of Illinois faculty since 1995. He is also an Affiliate Faculty in the Department of Atmospheric Science; Institute of Sustainability, Energy, and Environment; National Center for Supercomputing Applications; Carle Woese Institute for Genomics Biology; and Center for Digital Agriculture. His research focus is on complex hydrologic systems bridging across theory, modeling, and informatics. He presently serves as the Director of the NSF funded Critical Zone Observatory for Intensively Managed Landscapes, which is part of a national and international network. He is an AGU Fellow and AMS Fellow; a recipient of the Mahatma Gandhi Pravasi Samman (Non-Resident Honor) Award 2017 given by the NRI Welfare Society of India; and Distinguished Alumnus Award, Indian Institute of Technology, Bombay, India. From 2002-2008, he served as a founding Board member for CUAHSI, a consortium of over 110 universities for the advancement of hydrologic science. From 2009-2013 he served as the Editor-in-Chief of Water Resources Research and presently serves as the founding Chief Editor for Frontiers in Water. Prior to that he also served as the Editor of Geophysical Research Letters, a leading journal for inter-disciplinary research.
Geophysical systems, such as climate, weather, and critical zone, exhibit a complex network of interactions among a variety of earth system components. These interactions occur across spatial scales and distances and involve a range of time scales. They arise from forcing and feedback that cause fluctuations in a single or a group of components to propagate through the entire network. We propose that this propagation of fluctuations and their attenuation or amplification can also be characterized as a flow of information between the interacting network components. The flow of information across the network structures large-scale behaviors, such as responses to drought or climate change. They also enable new ways for thinking about cause-effect relationships. We will discuss the development of novel emerging framework(s), and associated formulations, for characterizing multivariate system dynamics with information flow as the currency of exchange between interacting components. They will be illustrated using problems in geophysical settings. This research draws upon and contributes to the convergence of advances using information theory from diverse fields such as complex systems, communication, statistical physics, mathematics, geophysics, machine learning, and artificial intelligence.