Mate Gerencser

Mate Gerencser is an Associate Professor at Vienna University of Technology (TU Wien) within the Institute for Analysis and Scientific Computing (E 101). Since March 2024, he has been supported by an ERC Starting Grant. His research focuses on stochastic partial differential equations (SPDEs), regularization by noise, regularity structures, and numerical methods for stochastic equations. He leads projects such as the ERC StG Project on 'Stochastic PDEs and Renormalization' and the FWF START Project.

His research interests span stochastic PDEs, including their theoretical foundations and numerical approximations. Key areas include the analysis of rough paths, KPZ-type equations, and the interplay between noise and equation regularity. Recent work emphasizes high-order approximation schemes and boundary renormalization techniques.

Gerencser has received prestigious grants, including the ERC Starting Grant (2024), and has contributed to leading journals in probability and stochastic analysis. He teaches courses such as 'Stochastic PDEs' and 'Applied Mathematics Foundations' at TU Wien.

His research group actively collaborates on projects addressing stochastic dynamics in continuous and discrete systems, with a focus on theoretical rigor and computational methods.