| Optimizing multiple-pollutant waste load allocation in rivers: an interval parameter game theoretic model MR Nikoo, PHB Beiglou, N Mahjouri Water Resources Management 30 (12), 4201-4220, 2016 | 43 | 2016 |
| A novel Bayesian maximum entropy-based approach for optimal design of water quality monitoring networks in rivers R Salman, MR Nikoo, SA Shojaeezadeh, PHB Beiglou, M Sadegh, ... Journal of Hydrology 603, 126822, 2021 | 21 | 2021 |
| Will land use land cover change drive atmospheric conditions to become more conducive to wildfires in the United States? S Zhong, T Wang, P Sciusco, M Shen, L Pei, J Nikolic, K McKeehan, ... International Journal of Climatology 41 (6), 3578-3597, 2021 | 19 | 2021 |
| MUSCAT: Multi-Scale Spatio-Temporal Learning with Application to Climate Modeling. J Xu, X Liu, T Wilson, PN Tan, P Hatami, L Luo IJCAI, 2912-2918, 2018 | 17 | 2018 |
| A game theoretic model for trading pollution discharge permits in river systems MR Nikoo, R Kerachian, MH Niksokhan, PHB Beiglou International Journal of Environmental Science and Development 2 (2), 162-166, 2011 | 17 | 2011 |
| Applicability of Benford’s Law to compliance assessment of self-reported wastewater treatment plant discharge data PHB Beiglou, C Gibbs, L Rivers, U Adhikari, J Mitchell Journal of Environmental Assessment Policy and Management 19 (04), 1750017, 2017 | 10 | 2017 |
| Automated analysis of the US drought monitor maps with machine learning and multiple drought indicators P Hatami Bahman Beiglou, L Luo, PN Tan, L Pei Frontiers in big Data 4, 750536, 2021 | 9 | 2021 |
| Distribution preserving multi-task regression for spatio-temporal data X Liu, PN Tan, Z Abraham, L Luo, P Hatami 2018 IEEE International Conference on Data Mining (ICDM), 1134-1139, 2018 | 6 | 2018 |
| A Multiple Pollutants Trading-Ratio System for River Water Quality Trading PHB Beiglou, R Kerachian, MR Nikoo, STO Naeeni | 3 | 2012 |
| Predicting US Drought Monitor Drought Categories with multiple land surface models and machine learning P Hatami, L Luo, L Pei, X Liu, T Wilson, PN Tan AGU Fall Meeting Abstracts 2018, H21J-1770, 2018 | 2 | 2018 |
| A deep learning architecture for long-range forecasting of sea surface temperature anomalies T Wilson, X Liu, PN Tan, P Hatami, L Luo AGU Fall Meeting Abstracts 2018, IN21D-0734, 2018 | 1 | 2018 |
| Stronger Soot Standards would Protect more Chicagoans P Hatami https://elpc.org/wp-content/uploads/2023/09/ELPC-Comments-Reconsideration-of …, 2023 | | 2023 |
| From Fixed Points to Fluid Measurements: Strategizing Mobile Air Quality Monitoring With Stationary Data In Chicago P Hatami Environmental Law & Policy Center, 2023 | | 2023 |
| Downscaling SMAP Satellite-Retrieved Soil Moisture Using Machine Learning Approaches with an Uncertainty Perspective P Hatami, L Luo, PN Tan American Meteorological Society Meeting Abstracts 102, J15B. 6, 2022 | | 2022 |
| Analysis of Phosphorus Concentrations in the Maumee River P Hatami https://elpc.org/wp-content/uploads/2022/05/Analysis-of-Phosphorus-Maumee …, 2022 | | 2022 |
| Rising Waters: Climate Change Impacts and Toxic Risks to Lake Michigan’s Shoreline Communities LS Pouyan Hatami, Kiana Courtney, Jill Geiger, Joshua Gonzalez, Maya Peña ... https://elpc.org/wp-content/uploads/2022/08/ELPCRisingWatersReport_2022.pdf, 2022 | | 2022 |
| Geographic Applications of Knowledge-Rich Machine Learning Approaches in Spatiotemporal Data Analysis PHB Beiglou Michigan State University, 2021 | | 2021 |
| Acknowledgement of reviewers 2018 A Ab Ghani, M Abahi, A Abbas, GM Abraha, S Abhilash, OA Adewuyi, ... Natural Hazards 95, 437-444, 2019 | | 2019 |
| A Deep Learning Architecture for Long-Range Forecasting of Sea Surface Temperature Anomalies X Liu, PN Tan, T Wilson, P Hatami, L Luo AGU Fall Meeting 2018, 2018 | | 2018 |
| Deep Graph Convolution for Weather Prediction T Wilson, X Liu, PN Tan, P Hatami, L Luo AGU Fall Meeting Abstracts 2018, IN21D-0737, 2018 | | 2018 |
Lifeng LuoProfessor, Michigan State UniversityVerified email at msu.edu
