معرفی
Onkar Jadhav is a Research Fellow at the University of Western Australia's School of Earth and Oceans, specializing in developing machine learning frameworks for oceanography and computational science. His work focuses on statistical downscaling techniques for ocean temperature predictions and reduced-order modeling for financial risk analysis. Previously, he was a postdoctoral researcher at the University of Luxembourg, where he applied machine learning to wind engineering and computational fluid dynamics.
Education: He holds a Doctorate in Applied Mathematics from the Technical University of Berlin (2018–2022), with a thesis on physics-assisted machine learning for high-dimensional partial differential equations. His academic background bridges mathematics, engineering, and computational science.
Research Interests: Jadhav’s expertise spans machine learning, computational science, and applied mathematics, with applications in oceanography, wind engineering, and financial risk analysis. He emphasizes interdisciplinary approaches to solve complex, high-dimensional problems.
Publications: His research includes advancements in model order reduction for parametric systems in finance, wind load assessments using machine learning, and thermoelectric generator design for biomedical implants.
Labs/Teams: Affiliated with the Oceans Graduate School and previously with the University of Luxembourg’s wind engineering team.
