| Homogeneous chaos basis adaptation for design optimization under uncertainty: Application to the oil well placement problem C Thimmisetty, P Tsilifis, R Ghanem Ai Edam 31 (3), 265-276, 2017 | 28 | 2017 |
| Optimal well-placement using probabilistic learning R Ghanem, C Soize, C Thimmisetty Data-Enabled Discovery and Applications 2, 1-16, 2018 | 23 | 2018 |
| Boosted embeddings for time-series forecasting SR Karingula, N Ramanan, R Tahmasbi, M Amjadi, D Jung, R Si, ... International Conference on Machine Learning, Optimization, and Data Science …, 2021 | 22 | 2021 |
| Power distribution system synchrophasor measurements with non-Gaussian noises: Real-world data testing and analysis C Huang, C Thimmisetty, X Chen, E Stewart, P Top, M Korkali, V Donde, ... IEEE Open Access Journal of Power and Energy 8, 223-228, 2021 | 20 | 2021 |
| High-dimensional intrinsic interpolation using Gaussian process regression and diffusion maps CA Thimmisetty, RG Ghanem, JA White, X Chen Mathematical Geosciences 50, 77-96, 2018 | 17 | 2018 |
| Multiscale stochastic representation in high-dimensional data using Gaussian processes with implicit diffusion metrics C Thimmisetty, A Khodabakhshnejad, N Jabbari, F Aminzadeh, ... Dynamic Data-Driven Environmental Systems Science: First International …, 2015 | 16 | 2015 |
| A Probabilistic Approach to the NASA Langley Multidisciplinary Uncertainty Quantification Challenge Problem R Ghanem, C Thimmisetty, I Yadegaran, V Keshavarzzadeh, S Masri, ... | 15* | 2014 |
| Multiscale stochastic representations using polynomial chaos expansions with gaussian process coefficients C Thimmisetty, F Aminzadeh, K Rose, R Ghanem Data-Enabled Discovery and Applications 2, 1-16, 2018 | 7 | 2018 |
| Risks and impact assessment for deepwater and ultra-deepwater Gulf of Mexico resources K Rose, F Aminzadeh, R Ghanem, C Thimmisetty, N Jabbari, ... Offshore Technology Conference, D021S025R003, 2014 | 4 | 2014 |
| Combined machine learning and formal techniques for network traffic analysis C Thimmisetty, P Tiwari, V Ananthakrishnan, CJN Coelho US Patent App. 17/447,471, 2022 | 2 | 2022 |
| Adapting the national energy technology laboratory’s offshore integrated assessment modeling approach for the offshore arctic L Romeo, K Rose, JR Bauer, C Disenhof, L Sim, J Nelson, C Thimmisetty, ... National Energy Technology Laboratory (NETL), Pittsburgh, PA, Morgantown, WV …, 2015 | 2 | 2015 |
| Computational framework for modeling of physical process X Chen, C Huang, L Min, C Thimmisetty, C Tong US Patent 11,580,280, 2023 | 1 | 2023 |
| High-dimensional Stochastic Inversion via Adjoint Models and Machine Learning CA Thimmisetty, W Zhao, X Chen, CH Tong, JA White arXiv preprint arXiv:1803.06295, 2018 | 1 | 2018 |
| Power distribution system synchrophasors with non-gaussian errors: Real-world measurements and analysis C Huang, CA Thimmisetty, X Chen, M Korkali, V Donde, E Stewart, P Top, ... arXiv preprint arXiv:1803.06230, 2018 | 1 | 2018 |
| Homogeneous chaos basis adaptation for design optimization under uncertainty: Application to the oil well placement problem. R Ghanem, X Du, C Thimmisetty, P Tsilifis AI EDAM 31 (3), 2017 | 1 | 2017 |
| Computational framework for modeling of physical process X Chen, C Huang, L Min, C Thimmisetty, C Tong, Y Xu, L Mili US Patent 11,914,937, 2024 | | 2024 |
| Log2NS: Enhancing Deep Learning Based Analysis of Logs With Formal to Prevent Survivorship Bias C Thimmisetty, P Tiwari, DG de la Iglesia, N Ramanan, M Sayer, ... arXiv preprint arXiv:2105.14149, 2021 | | 2021 |
| Boosted Embeddings for Time Series Forecasting S Rao Karingula, N Ramanan, R Tahmasbi, M Amjadi, D Jung, R Si, ... arXiv e-prints, arXiv: 2104.04781, 2021 | | 2021 |
| Efficient Stochastic Inversion Using Adjoint Models and Kernel-PCA X Chen, CA Thimmisetty, CH Tong, JA White, C Morency, C Huang, ... Lawrence Livermore National Lab.(LLNL), Livermore, CA (United States), 2018 | | 2018 |
| Efficient Stochastic Inversion Using Adjoint Models and Kernel-PCA CA Thimmisetty, W Zhao, X Chen, CH Tong, JA White Lawrence Livermore National Lab.(LLNL), Livermore, CA (United States), 2017 | | 2017 |
Roger GhanemProfessor Civil Engineering, University of Southern CaliforniaE-mail megerősítve itt: usc.edu