Welcome to my personal webpage
I am a researcher working at the intersection of mathematical optimization and machine learning. My work focuses on the development, theoretical analysis, and numerical implementation of algorithms for convex and nonconvex problems. I am particularly interested in designing efficient, adaptive, and scalable optimization methods for challenging problems in scientific computing and modern AI.
Current Position
Postdoctoral Researcher
Department of Mathematics and Statistics, University of Helsinki, Finland
Working with Tuomo Valkonen.
Research Interests
My research combines optimization theory, algorithm design, and computational methods. Select a topic to learn more about my work, related publications, and research projects.
Optimization Algorithms
Convex and nonconvex optimization, nonsmooth composite problems, constrained optimization, and second- and higher-order methods.
Optimization for Machine Learning
Optimization methods for machine learning and AI, with an emphasis on algorithmic efficiency, adaptivity, and theoretical guarantees.
Distributed and Federated Learning
Communication-efficient optimization, distributed algorithms, and robust learning in heterogeneous and adversarial environments.
Inverse Problems and Scientific Computing
Optimization methods for inverse problems, dynamic systems, and large-scale computational applications.
Academic Background
I received my Ph.D. in Automatic Control and Systems Engineering in May 2024, under the supervision of Ion Necoara, at the National University of Science and Technology POLITEHNICA Bucharest.
My doctoral research was conducted within the Marie Skłodowska-Curie TraDE-OPT H2020 Innovative Training Network, where I was an Early Stage Researcher (ESR10).