| Machine learning assisted high-throughput screening of transition metal single atom based superb hydrogen evolution electrocatalysts M Umer, S Umer, M Zafari, M Ha, R Anand, A Hajibabaei, A Abbas, G Lee, ... Journal of Materials Chemistry A 10 (12), 6679-6689, 2022 | 109 | 2022 |
| Machine learning approaches to predict the photocatalytic performance of bismuth ferrite-based materials in the removal of malachite green ZH Jaffari, A Abbas, SM Lam, S Park, K Chon, ES Kim, KH Cho Journal of hazardous materials 442, 130031, 2023 | 93 | 2023 |
| Prediction of biogas production in anaerobic co-digestion of organic wastes using deep learning models K Jeong, A Abbas, J Shin, M Son, YM Kim, KH Cho Water research 205, 117697, 2021 | 71 | 2021 |
| Deep learning for pH prediction in water desalination using membrane capacitive deionization M Son, N Yoon, K Jeong, A Abass, BE Logan, KH Cho Desalination 516, 115233, 2021 | 45 | 2021 |
| Dual-stage attention-based LSTM for simulating performance of brackish water treatment plant N Yoon, J Kim, JL Lim, A Abbas, K Jeong, KH Cho Desalination 512, 115107, 2021 | 45 | 2021 |
| Prediction of antibiotic-resistance genes occurrence at a recreational beach with deep learning models J Jang, A Abbas, M Kim, J Shin, YM Kim, KH Cho Water research 196, 117001, 2021 | 40 | 2021 |
| Transformer-based deep learning models for adsorption capacity prediction of heavy metal ions toward biochar-based adsorbents ZH Jaffari, A Abbas, CM Kim, J Shin, J Kwak, C Son, YG Lee, S Kim, ... Journal of Hazardous Materials 462, 132773, 2024 | 37 | 2024 |
| Machine learning analysis to interpret the effect of the photocatalytic reaction rate constant (k) of semiconductor-based photocatalysts on dye removal CM Kim, ZH Jaffari, A Abbas, MF Chowdhury, KH Cho Journal of Hazardous Materials 465, 132995, 2024 | 33 | 2024 |
| Developing a deep learning model for the simulation of micro-pollutants in a watershed D Yun, A Abbas, J Jeon, M Ligaray, SS Baek, KH Cho Journal of Cleaner Production 300, 126858, 2021 | 26 | 2021 |
| AI4Water v1. 0: an open-source python package for modeling hydrological time series using data-driven methods A Abbas, L Boithias, Y Pachepsky, K Kim, JA Chun, KH Cho Geoscientific Model Development 15 (7), 3021-3039, 2022 | 25 | 2022 |
| Long short-term memory models of water quality in inland water environments JC Pyo, Y Pachepsky, S Kim, A Abbas, M Kim, YS Kwon, M Ligaray, ... Water research X 21, 100207, 2023 | 24 | 2023 |
| Deep learning-based algorithms for long-term prediction of chlorophyll-a in catchment streams A Abbas, M Park, SS Baek, KH Cho Journal of Hydrology 626, 130240, 2023 | 22 | 2023 |
| An open-source deep learning model for predicting effluent concentration in capacitive deionization M Son, N Yoon, S Park, A Abbas, KH Cho Science of The Total Environment 856, 159158, 2023 | 21 | 2023 |
| Surface and sub-surface flow estimation at high temporal resolution using deep neural networks A Abbas, S Baek, M Kim, M Ligaray, O Ribolzi, N Silvera, JH Min, ... Journal of Hydrology 590, 125370, 2020 | 20 | 2020 |
| Artificial neural networks for insights into adsorption capacity of industrial dyes using carbon-based materials S Iftikhar, N Zahra, F Rubab, RA Sumra, MB Khan, A Abbas, ZH Jaffari Separation and Purification Technology 326, 124891, 2023 | 18 | 2023 |
| In-stream Escherichia coli modeling using high-temporal-resolution data with deep learning and process-based models A Abbas, S Baek, N Silvera, B Soulileuth, Y Pachepsky, O Ribolzi, ... Hydrology and Earth System Sciences 25 (12), 6185-6202, 2021 | 18 | 2021 |
| Estimation of base and surface flow using deep neural networks and a hydrologic model in two watersheds of the Chesapeake Bay J Lee, A Abbas, GW McCarty, X Zhang, S Lee, KH Cho Journal of Hydrology 617, 128916, 2023 | 16 | 2023 |
| Autonomous calibration of EFDC for predicting chlorophyll-a using reinforcement learning and a real-time monitoring system SM Hong, A Abbas, S Kim, DH Kwon, N Yoon, D Yun, S Lee, ... Environmental Modelling & Software 168, 105805, 2023 | 13 | 2023 |
| Crystal graph convolution neural networks for fast and accurate prediction of adsorption ability of Nb 2 CT x towards Pb (ii) and Cd (ii) ions ZH Jaffari, A Abbas, M Umer, ES Kim, KH Cho Journal of Materials Chemistry A 11 (16), 9009-9018, 2023 | 13 | 2023 |
| Digital imaging-in-flow (FlowCAM) and probabilistic machine learning to assess the sonolytic disinfection of cyanobacteria in sewage wastewater ZH Jaffari, S Na, A Abbas, KY Park, KH Cho Journal of Hazardous Materials 468, 133762, 2024 | 12 | 2024 |
Pachepsky YUSDA-ARSZweryfikowany adres z ars.usda.gov