Dr. Mohammed Ombadi is a water data science postdoctoral research fellow in the Climate and Ecosystem Sciences Division at Lawrence Berkeley National Laboratory. He received his B.S. degree in Civil Engineering from University of Khartoum in 2014, and M.S. and Ph.D. in Civil & Environmental Engineering, in 2017 and 2021, respectively. His PhD thesis focused on the use of causal inference, information-theoretic techniques, and other data-driven approaches to the analysis of environmental systems.
At Berkeley lab, his research is concerned with investigating the impacts of streamflow disturbances on water quality using data-driven approaches. He is also a part of the Calibrated & Systematic Characterization, Attribution, and Detection of Extremes (CASCADE).