| Physics-inspired integrated space–time artificial neural networks for regional groundwater flow modeling A Ghaseminejad, V Uddameri Hydrology and Earth System Sciences 24 (12), 5759-5779, 2020 | 13 | 2020 |
| A tiered stochastic framework for assessing crop yield loss risks due to water scarcity under different uncertainty levels V Uddameri, A Ghaseminejad, EA Hernandez Agricultural Water Management 238, 106226, 2020 | 11 | 2020 |
| A simulation–optimization approach for optimal design of groundwater withdrawal wells’ location and pumping rate considering desalination constraints A Ghaseminejad, M Shourian Environmental earth sciences 78, 1-11, 2019 | 11 | 2019 |
| Optimal Design of Groundwater Wells' Placement and Pumping Rates by Use of a Simulation-Optimization Approach A Ghaseminejad, M Shourian Iran-Water Resources Research 12 (2), 24-37, 2016 | 1 | 2016 |
| Assessing the contribution of discrete precipitation events to groundwater recharge in the shallow unconfined aquifers A Ghaseminejad, N Bhat, M Kumar, P Clement AGU23, 2023 | | 2023 |
| Machine Learning-Driven Temporal Downscaling of Groundwater Recharge Estimates to Obtain Event-Based Response A Ghaseminejad, N Bhat, P Raghav, M Kumar, P Clement AGU Fall Meeting Abstracts 2022, H35H-1215, 2022 | | 2022 |
| Physics-inspired Machine Learning Methods for Modeling Regional Groundwater Flow Systems A Ghaseminejad Texas Tech University, 2022 | | 2022 |
| Is the Representation of Interannual Leaf Phenology Dynamics Needed for Accurate Estimation of Evapotranspiration? M Kumar, A Ghaseminejad, P Raghav AGU23, 0 | | |
Venkatesh UddameriLamar UniversityVerified email at lamar.edu
