| Using a deep convolutional neural network to predict 2017 ozone concentrations, 24 hours in advance A Sayeed, Y Choi, E Eslami, Y Lops, A Roy, J Jung Neural Networks 121, 396-408, 2020 | 114 | 2020 |
| A real-time hourly ozone prediction system using deep convolutional neural network E Eslami, Y Choi, Y Lops, A Sayeed Neural Computing and Applications 32, 8783-8797, 2020 | 86 | 2020 |
| A data ensemble approach for real-time air quality forecasting using extremely randomized trees and deep neural networks E Eslami, AK Salman, Y Choi, A Sayeed, Y Lops Neural Computing and Applications 32, 7563-7579, 2020 | 63 | 2020 |
| Potential impacts of electric vehicles on air quality and health endpoints in the Greater Houston Area in 2040 S Pan, A Roy, Y Choi, E Eslami, S Thomas, X Jiang, HO Gao Atmospheric Environment 207, 38-51, 2019 | 59 | 2019 |
| A novel CMAQ-CNN hybrid model to forecast hourly surface-ozone concentrations 14 days in advance A Sayeed, Y Choi, E Eslami, J Jung, Y Lops, AK Salman, JB Lee, HJ Park, ... Scientific reports 11 (1), 10891, 2021 | 44 | 2021 |
| Effects of expanded perlite aggregate (EPA) on the mechanical behavior of lightweight concrete V Khonsari, E Eslami, A Anvari Proceedings of the 7th international conference on fracture and mechanics of …, 2010 | 35 | 2010 |
| Real-time 7-day forecast of pollen counts using a deep convolutional neural network Y Lops, Y Choi, E Eslami, A Sayeed Neural Computing and Applications 32, 11827-11836, 2020 | 34 | 2020 |
| A deep convolutional neural network model for improving WRF simulations A Sayeed, Y Choi, J Jung, Y Lops, E Eslami, AK Salman IEEE Transactions on Neural Networks and Learning Systems 34 (2), 750-760, 2021 | 25 | 2021 |
| Using wavelet transform and dynamic time warping to identify the limitations of the CNN model as an air quality forecasting system E Eslami, Y Choi, Y Lops, A Sayeed, AK Salman Geoscientific Model Development 13 (12), 6237-6251, 2020 | 16 | 2020 |
| Bioremediation of oil and heavy metal contaminated soil in construction sites: a case study of using bioventing-biosparging and phytoextraction techniques E Eslami, SHS Joodat arXiv preprint arXiv:1806.03717, 2018 | 14 | 2018 |
| CMAQ-CNN: A new-generation of post-processing techniques for chemical transport models using deep neural networks A Sayeed, E Eslami, Y Lops, Y Choi Atmospheric Environment 273, 118961, 2022 | 13 | 2022 |
| A Fuzzy Analytic Network Process Approach to Evaluate Concrete Waste Management Options K Khodaverdi, A Faghih, E Eslami ISAHP July, 2009 | 12 | 2009 |
| A deep convolutional neural network model for improving WRF forecasts A Sayeed, Y Choi, J Jung, Y Lops, E Eslami, AK Salman arXiv preprint arXiv:2008.06489, 2020 | 10 | 2020 |
| Fibrous and non-fibrous Perlite concretes–experimental and SEM studies SV Khonsari, E Eslami, A Anvari European Journal of Environmental and Civil Engineering 22 (2), 138-164, 2018 | 7 | 2018 |
| A novel CMAQ-CNN hybrid model to forecast hourly surface-ozone concentrations 14 days in advance, Sci. Rep., 11, 10891 A Sayeed, Y Choi, E Eslami, J Jung, Y Lops, AK Salman, JB Lee, HJ Park, ... | 6 | 2021 |
| A Deep Learning Driven Improved Ensemble Approach for Hurricane Forecasting E Eslami, Y Choi, Y Lops, A Sayeed 2019 ESIP Winter Meeting, 2019 | 5 | 2019 |
| CMAQ Modeling Archive for Exceptional Events Analysis, Final report to the Texas Commission on Environmental Quality (TCEQ) Y Choi, W Jeon, A Roy, AH Souri, L Diao, S Pan, E Eslami | 4 | 2016 |
| Applications of Deep Learning in Atmospheric Sciences: Air Quality Forecasting, Post-Processing, and Hurricane Tracking E Eslami University of Houston, PhD Thesis, 2019 | 1 | 2019 |
| CAMQ-AI: A computationally efficient deep learning model to improve CMAQ performance over the United States Y Choi, E Eslami, A Sayeed, Y Lops AGU Fall Meeting Abstracts 2019, A33M-2961, 2019 | 1 | 2019 |
| Health and cost impact of air pollution from biomass burning over the United States E Eslami, B Pan, Shuai, Sadeghi, Y Choi AGU Fall Meeting, New Orleans, LA, USA, 2017 | 1 | 2017 |
