Efi Foufoula-Georgiou is a University of Minnesota McKnight Distinguished Professor in the Department of Civil Engineering and the Joseph T. and Rose S. Ling Chair in Environmental Engineering. She is Director of the NSF Science and Technology Center “National Center for Earth-surface Dynamics” (NCED), and has served as Director of St. Anthony Falls Laboratory at the University of Minnesota. She received a diploma in Civil Engineering from the National Technical University of Athens, Greece, and an M.S. and Ph.D. (1985) in Environmental Engineering from the University of Florida. Her area of research is hydrology and geomorphology, with special interest on scaling theories, multiscale dynamics and space-time modeling of precipitation and landforms. She has served as associate editor of Water Resources Research, J. of Geophysical Research, Advances in Water Resources, Hydrologic and Earth System Sciences, and as editor of J. Hydrometeorology . She has also served in many national and international advisory boards including the Water Science and Technology Board, NSF, NASA and EU proposal review panels, and in several NRC studies. She is currently the chair of the Board of Directors for CUAHSI (Consortium of Universities for the Advancement of Hydrologic Sciences), a member of the Board of Trustees of UCAR (University forporation for Atmospheric Research), and a member of the Advisory Council of the GEO directorate of NSF. Professor Foufoula has been the recipient of the John Dalton Medal of the European Geophysical Society and the AGU Hydrologic Sciences Award. She is a fellow of the American Geophysical Union and American Meteorological Society, and a member of the European Academy of Sciences.

Major research interests are in the area of stochastic modeling of surface hydrologic and geomorphologic processes. Current areas of research include modeling and estimation of space-time rainfall from multiple sensors, stochastic theories of transport on the Earth's surface, river network dynamics, channel morphology, and hydrologic response. All these research topics have the common thread of exploring space-time statistical signatures over a range of scales and relating them to the underlying physical processes. Modeling is pursued using minimal complexity models that explore re-normalization and patterns.