| Artificial intelligence in farming: Challenges and opportunities for building trust M Gardezi, B Joshi, DM Rizzo, M Ryan, E Prutzer, S Brugler, A Dadkhah Agronomy Journal 116 (3), 1217-1228, 2024 | 47 | 2024 |
| The role of living labs in cultivating inclusive and responsible innovation in precision agriculture M Gardezi, H Abuayyash, PR Adler, JP Alvez, R Anjum, AR Badireddy, ... Agricultural Systems 216, 103908, 2024 | 20 | 2024 |
| Rethinking ‘responsibility’in precision agriculture innovation: lessons from an interdisciplinary research team E Prutzer, M Gardezi, DM Rizzo, M Emery, S Merrill, BEK Ryan, ... Journal of Responsible Innovation 10 (1), 2202093, 2023 | 7 | 2023 |
| Improving decision support systems with machine learning: Identifying barriers to adoption S Brugler, M Gardezi, A Dadkhah, DM Rizzo, A Zia, SA Clay Agronomy Journal 116 (3), 1229-1236, 2024 | 5 | 2024 |
| Microbiome assembly and stability during start-up of a full-scale, two-phase anaerobic digester fed cow manure and mixed organic feedstocks AC DeCola, LC Toppen, KP Brown, A Dadkhah, DM Rizzo, RM Ziels, ... Bioresource Technology 394, 130247, 2024 | 4 | 2024 |
| Variable Drought Threshold Method for Low-Flow Behavior Reveals Distinct Clustering Across the Continental United States R van der Heijden, A Dadkhah, A Aghababaei, X Li, E Webster-Esho, ... EGU24, 2024 | | 2024 |
| Crop yield prediction: leveraging high-resolution daily cloud-free sentinel-2 imagery A Dadkhah, S Musayev, D Rizzo, P Adler, A Zia, L Garcia, P Oikonomou, ... Chapman Conference on Remote Sensing of the Water Cycle, 2024 | | 2024 |
| High resolution corn yield prediction using daily, cloud-free sentinel imagery A Dadkhah, S Musayev, P Adler, D Rizzo, A Zia, G Pinder, P Oikonomou, ... AGU23, 2023 | | 2023 |
| Spatiotemporal analysis of model errors in regional hydrological predictions of drought: A study in the Colorado River Basin A Dadkhah, D Rizzo, S Hamshaw STAHY23, 2023 | | 2023 |
| Watershed analysis and feature selection based on performance of deep learning streamflow drought models in the Colorado River Basin A Dadkhah, D Rizzo, K Underwood SEDHYD23, 2023 | | 2023 |
| Employing random forest, support vector machine learning models, and Planet Scope satellite data to predict crop yield on the farm J Rathore, D Joshi, A Dadkhah, S Kumari, M Gardezi, O Walsh, DM Rizzo, ... AGU24, 0 | | |
| Using Interpretable Machine Learning to Reveal Processes Driving Baseflow Regimes Across CONUS R van der Heijden, A Dadkhah, A Aghababaei, X Li, E Webster-Esho, ... AGU24, 0 | | |
| A Machine Learning Framework for Interpreting Spatiotemporal Model Errors in Regional Hydrological Predictions of Drought A Dadkhah, SD Hamshaw, R van der Heijden, DM Rizzo AGU24, 0 | | |
| A Framework for Spatiotemporal Improvement of Actual Evapotranspiration Estimates Using Neural Networks and Remote Sensing Data A Dadkhah, DM Rizzo, LA Garcia, PR Adler, GF Pinder, PJ Clemins, ... AGU24, 0 | | |
| Promoting Responsible Innovation in Precision Agriculture through Living Labs M Gardezi, PR Adler, H Abuayyash, J Alvez, AR Badireddy, R Anjum, ... AGU24, 0 | | |
Maaz GardeziAssociate Professor, Virginia TechBestätigte E-Mail-Adresse bei vt.edu