| Redefining Super-Resolution: Fine-mesh PDE predictions without classical simulations RK Sarkar, R Majumdar, V Jadhav, SS Sakhinana, V Runkana arXiv preprint arXiv:2311.09740, 2023 | 1 | 2023 |
| Hypergraph Learning based Recommender System for Anomaly Detection, Control and Optimization SS Srinivas, RK Sarkar, V Runkana 2022 IEEE International Conference on Big Data (Big Data), 1922-1929, 2022 | 1 | 2022 |
| PointSAGE: Mesh-independent superresolution approach to fluid flow predictions R Sarkar, KSS Aripirala, VS Jadhav, SS Sakhinana, V Runkana ICLR 2024 Workshop on AI4DifferentialEquations In Science, 2024 | | 2024 |
| System and method for generating mixed variable type multivariate temporal synthetic data SS Sakhinana, V Runkana, RK Sarkar US Patent App. 17/994,580, 2023 | | 2023 |
| Privacy preserving generative mechanism for industrial time-series data disclosure SS Sakhinana, V Runkana, RK Sarkar US Patent App. 17/804,682, 2023 | | 2023 |
| Congeniality-preserving generative adversarial networks for imputing low-dimensional multivariate time-series data SS Sakhinana, RK Sarkar, V Runkana US Patent App. 17/815,316, 2023 | | 2023 |
| Battery GraphNets: Relational Learning for Lithium-ion Batteries(LiBs) Life Estimation RK Sarkar, SS Sakhinana, V Runkana GLIndA2022 Workshop, NeurIPS-2022, 2022 | | 2022 |
| EMCNet: Graph-Nets for Electron Micrographs Classification S Srinivas, R Sarkar, V Runkana | | 2022 |
Venkataramana RunkanaChief Scientist, Tata Consultancy Services, Research and Innovation for Manufacturing & Engineering在 tcs.com 的电子邮件经过验证
