| Predicting electricity consumption for commercial and residential buildings using deep recurrent neural networks A Rahman, V Srikumar, AD Smith Applied energy 212, 372-385, 2018 | 695 | 2018 |
| Predicting heating demand and sizing a stratified thermal storage tank using deep learning algorithms A Rahman, AD Smith Applied Energy 228, 108-121, 2018 | 78 | 2018 |
| Performance modeling and parametric study of a stratified water thermal storage tank A Rahman, AD Smith, N Fumo Applied Thermal Engineering 100, 668-679, 2016 | 72 | 2016 |
| A machine learning framework for predicting the shear strength of carbon nanotube-polymer interfaces based on molecular dynamics simulation data A Rahman, P Deshpande, MS Radue, GM Odegard, S Gowtham, ... Composites Science and Technology 207, 108627, 2021 | 67 | 2021 |
| Predicting microstructure-sensitive fatigue-crack path in 3D using a machine learning framework K Pierson, A Rahman, AD Spear Jom 71 (8), 2680-2694, 2019 | 55 | 2019 |
| Predicting fuel consumption for commercial buildings with machine learning algorithms A Rahman, AD Smith Energy and Buildings 152, 341-358, 2017 | 42 | 2017 |
| Multiscale effects masked the impact of the COVID-19 pandemic on electricity demand in the United States CD Burleyson, A Rahman, JS Rice, AD Smith, N Voisin Applied Energy 304, 117711, 2021 | 27 | 2021 |
| A void descriptor function to uniquely characterize pore networks and predict ductile-metal failure properties JM Erickson, A Rahman, AD Spear International Journal of Fracture 225, 47-67, 2020 | 19 | 2020 |
| Simplified modeling of thermal storage tank for distributed energy heat recovery applications A Rahman, N Fumo, AD Smith Energy Sustainability 56857, V002T13A005, 2015 | 19 | 2015 |
| Investigating the efficacy of machine learning tools in modeling the continuous stabilization and carbonization process and predicting carbon fiber properties N Shirolkar, P Patwardhan, A Rahman, A Spear, S Kumar Carbon 174, 605-616, 2021 | 18 | 2021 |
| Neural ordinary differential equations for nonlinear system identification A Rahman, J Drgoňa, A Tuor, J Strube 2022 American Control Conference (ACC), 3979-3984, 2022 | 15 | 2022 |
| Changes in electricity load profiles under COVID-19: Implications of “The new normal” for electricity demand C Burleyson, AD Smith, JS Rice, N Voisin, A Rahman engrXiv, 2020 | 7 | 2020 |
| Adversar: Adversarial search and rescue via multi-agent reinforcement learning A Rahman, A Bhattacharya, T Ramachandran, S Mukherjee, H Sharma, ... 2022 IEEE International Symposium on Technologies for Homeland Security (HST …, 2022 | 5 | 2022 |
| On-policy learning-based deep reinforcement learning assessment for building control efficiency and stability JY Lee, A Rahman, S Huang, AD Smith, S Katipamula Science and Technology for the Built Environment 28 (9), 1150-1165, 2022 | 5 | 2022 |
| Generation of thermo-acoustic waves from pulsed solar/IR radiation A Rahman The University of Utah, 2014 | 5 | 2014 |
| Flexible reinforcement learning framework for building control using EnergyPlus-modelica energy models JY Lee, S Huang, A Rahman, AD Smith, S Katipamula Proceedings of the 1st International Workshop on Reinforcement Learning for …, 2020 | 4 | 2020 |
| tell: a Python package to model future total electricity loads in the United States CR McGrath, CD Burleyson, Z Khan, A Rahman, T Thurber, CR Vernon, ... Journal of Open Source Software 7 (79), 4472, 2022 | 3 | 2022 |
| Production of acoustic waves from pulsed thermal radiation K Chen, A Rahman, Y Kim, SJ Oh, W Chun International Journal of Energy Research 40 (4), 462-472, 2016 | 3 | 2016 |
| Multi-fidelity Bayesian Optimization for Co-design of Resilient Cyber-Physical Systems S Vasisht, A Rahman, T Ramachandran, A Bhattacharya, V Adetola 2022 ACM/IEEE 13th International Conference on Cyber-Physical Systems (ICCPS …, 2022 | 2 | 2022 |
| A Computational Framework for Control Co-Design of Resilient Cyber–Physical Systems With Applications to Microgrids T Ramachandran, S Vasisht, A Rahman, A Bhattacharya, V Adetola IEEE Transactions on Control Systems Technology, 2023 | | 2023 |
Amanda D. SmithSenior Scientist, Built Environment at Project DrawdownVerified email at utah.edu
