Jeya Jeyakumar

Professor Jeya Jeyakumar is a leading applied mathematician at the School of Mathematics and Statistics of the University of New South Wales (UNSW), internationally recognized for pioneering contributions to mathematical optimization. His work bridges rigorous theoretical analysis with practical computational methods, advancing fields like global optimization, robust decision-making, and machine learning-inspired models.

• PhD in Optimization, University of Melbourne

His research focuses on transforming complex mathematical concepts into robust optimization frameworks for uncertainty quantification, risk minimization, and multi-stage decision-making. Key applications include medical decision support tools (e.g., Alzheimer’s detection via handwriting analysis), radiation therapy planning, and Huntington’s disease characterization.

Recent work spans distributionally robust optimization, polynomial optimization, and convexifiable systems. His 15 most recent publications address topics like data-driven optimization over measure spaces, adjustable robustness in medical contexts, and algebraic approaches to fuzzy sets.

• 2025: Marguerite Frank Award for EURO Journal on Computational Optimization
• 2019: Joint winner of Journal of Global Optimization Best Paper Prize
• 2017: Optimization Letters Best Paper Prize

Professor Jeyakumar has secured multiple ARC Discovery Project grants (e.g., $471,300 in 2025 for risk-aware optimization) and industry collaborations. He supervises HDR students in areas like two-stage robust optimization and feature selection under uncertainty.