| Using atmospheric inputs for Artificial Neural Networks to improve wind turbine power prediction J Nielson, K Bhaganagar, R Meka, A Alaeddini Energy 190, 116273, 2020 | 85 | 2020 |
| A robust deep learning framework for short-term wind power forecast of a full-scale wind farm using atmospheric variables R Meka, A Alaeddini, K Bhaganagar Energy 221, 119759, 2021 | 80 | 2021 |
| Development of a deep learning model for dynamic forecasting of blood glucose level for type 2 diabetes mellitus: secondary analysis of a randomized controlled trial SHA Faruqui, Y Du, R Meka, A Alaeddini, C Li, S Shirinkam, J Wang JMIR mHealth and uHealth 7 (11), e14452, 2019 | 65 | 2019 |
| Sequential Laplacian regularized V-optimal design of experiments for response surface modeling of expensive tests: An application in wind tunnel testing A Alaeddini, E Craft, R Meka, S Martinez IISE Transactions 51 (5), 559-576, 2019 | 10 | 2019 |
| An active learning methodology for efficient estimation of expensive noisy black-box functions using Gaussian process regression R Meka, A Alaeddini, S Oyama, K Langer IEEE Access 8, 111460-111474, 2020 | 9 | 2020 |
| Multi-armed bandit regularized expected improvement for efficient global optimization of expensive computer experiments with low noise R Meka, A Alaeddini, C Ovuegbe, PA Bhounsule, P Najafirad, K Yang IEEE Access 9, 100125-100140, 2021 | 2 | 2021 |
| Corrections to “An Active Learning Methodology for Efficient Estimation of Expensive Noisy Black-Box Functions Using Gaussian Process Regression” R Meka, A Alaeddini, S Oyama, K Langer IEEE Access 8, 128239-128239, 2020 | | 2020 |
| A Deep Learning Framework for Forecasting Power in a Full-Scale Wind Farm R Meka, K Bhaganagar, A Alaeddini 100th American Meteorological Society Annual Meeting, 2020 | | 2020 |
| Efficient Estimation and Optimization of Expensive to Evaluate Black-Box Functions R Meka The University of Texas at San Antonio, 2020 | | 2020 |
| Selected publications J Nielson, K Bhaganagar, R Meka, A Alaeddini | | 1934 |
| CREDIT AUTHOR STATEMENT S Mehan | | |
