Regular biography
Professor Jeya Jeyakumar is an applied mathematician affiliated with the School of Mathematics & Statistics at The University of New South Wales. His research focuses on mathematical optimization, with an emphasis on nonlinear and robust optimization, as well as machine learning-inspired mathematical models. His work integrates rigorous mathematical analysis with innovative computational methods to develop solutions that address uncertainty and enhance decision-making across science and engineering. Professor Jeyakumar's research has led to significant contributions in areas such as uncertainty quantification, risk-aware optimization, and robust optimization frameworks. He has received several awards, including the Marguerite Frank Award for the Best Paper of EURO Journal on Computational Optimization in 2024, and has led multiple ARC Discovery Project Grants. His research has also been applied in medical contexts, such as Alzheimer’s disease detection and HIV-associated neurological disorders.
Scholar-generated biography
Vaithilingam (Jeya) Jeyakumar is a Professor of Applied Mathematics at UNSW Australia, specializing in Optimization and Applications, and Operations Research. His research focuses on mathematical programming, convex and non-convex optimization, and robust optimization techniques. He has contributed significantly to the development of duality theory, constraint qualifications, and optimality conditions for convex and non-convex problems. His work often involves the analysis of generalized convexity, subdifferentials, and the application of nonsmooth optimization methods to real-world problems. Jeyakumar's research has been published in numerous high-impact journals, reflecting his expertise in theoretical and applied optimization.