معرفی
Yura Malitsky is a postdoctoral researcher at Graz University of Technology's Institute of Computer Graphics and Vision, working under the supervision of Prof. Thomas Pock. He earned his Master's in Applied Mathematics from Kyiv National University in 2012 and completed his PhD in 2015 on projection methods for variational inequalities and composite optimization problems.
- Education: MS in Applied Mathematics (Kyiv National University, 2012), PhD in Optimization (2015)
- Affiliation: Graz University of Technology, Institute of Computer Graphics and Vision
- Academic Rank: Researcher
His research focuses on convex optimization, variational inequalities, and nonlinear analysis, with applications to machine learning and signal processing. His work includes developing adaptive gradient methods, distributed optimization algorithms for ring networks, and novel approaches to stochastic variance reduction.
Recent publications explore entropic mirror descent, Riemannian optimization, over-the-air computation for distributed systems, and improvements to primal-dual methods. He has contributed to advancements in resolvent splitting techniques and forward-reflected-backward methods for monotone operators.
Malitsky's research bridges theoretical optimization frameworks with practical implementations in decentralized systems and high-dimensional learning problems. His work demonstrates significant technical contributions to algorithm design and convergence analysis.
