Rate My Professor Yao Hu

Hu's research interests encompass socio-hydrology, agent-based modeling, model coupling and integration, water system modeling analysis and optimization, causal inference, high-performance and cloud computing, data science, and cyberinfrastructure. He has obtained funding as principal investigator, co-investigator, or sub-PI on projects including the Department of Defense's Military DEEDS Project (2022-2025, approximately $240,000 for a PhD student), NSF DISES on groundwater sustainability in changing climates (candidate's share $261,172), NOAA collaborations on runoff risk prediction ($50,000-$65,000 and $90,000), and University of Delaware Research Foundation grants. Key publications include 'Are all data useful? Inferring causality to predict flows across sewer and drainage systems using Directed Information and Boosted Regression Trees' (Water Research, 2018); 'Urban Total Phosphorus Loads to the St. Clair-Detroit River System' (Journal of Great Lakes Research, 2019); 'Edge-of-field Runoff Prediction by a Hybrid Modeling Approach Using Causal Inference' (Environmental Research Communications, 2021); 'Combining human and machine intelligence to derive agents’ behavioral rules for groundwater irrigation' (Advances in Water Resources, 2017); and several on sensitivity analysis and web-based modeling in Environmental Modelling & Software and Groundwater (2015). His scholarship has garnered over 225 citations per Google Scholar. Hu has presented at American Geophysical Union meetings, World Environment and Water Resources Congress, and European Geosciences Union on topics such as runoff risk, socio-hydrological modeling, and groundwater behaviors.