Random Graphs Professors and Supervisors in Hungary

Márton Pósfaiمشاهده پروفایل

استادیار

Central European UniversityHungary

Márton Pósfai is an Assistant Professor at the Central European University (CEU), specializing in network science and statistical physics. His research focuses on the structural and dynamic properties of complex networks, particularly physical networks, their controllability, and interdependencies. He holds a PhD and MSc in Physics from Eötvös Loránd University, Budapest. His work explores interdisciplinary topics including the impact of physical constraints on network topology, resilience under damage, and social behavior in non-human primates. Notable projects include the DYNASNET initiative to understand and utilize network structures. Pósfai’s publications span theoretical models of network dismantling, multiplex centrality metrics, and algorithmic instabilities in ranking systems. Key research trends in his articles include analyzing physical network structures (e.g., 3D shape, bundling effects), controllability strategies (input node placement, longest control chains), and social dynamics influenced by resource access. His studies often bridge abstract network theory with empirical systems like primate societies and Bitcoin transaction networks. Advising and grants are not explicitly detailed in the provided materials. Pósfai maintains a lab or team focused on network science applications, though specific lab names are unspecified.

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Backhausz Ágnesمشاهده پروفایل

استادیار

Eötvös Loránd UniversityHungary

Ágnes Backhausz is a habilitated assistant professor at Eötvös Loránd University's Faculty of Science, Institute of Mathematics, Department of Probability Theory and Statistics, with a part-time research position at the Alfréd Rényi Institute of Mathematics. Her academic career spans theoretical probability and practical applications in network science. Dr. Backhausz's research focuses on probability theory with specializations in random graphs, matrices and their limits, spectral theory of random graphs, and factor of iid processes. Her work bridges pure mathematics with real-world applications, particularly in epidemiological modeling on complex networks. She has made significant contributions to understanding the eigenvectors of random regular graphs and the behavior of processes on infinite trees. Her recent publications demonstrate a growing emphasis on applying probabilistic methods to epidemic modeling on multilayer networks with overlapping communities. This research has important implications for public health policy and disease control strategies. The trend in her work shows increasing interdisciplinary collaboration, combining mathematical rigor with practical healthcare applications. Dr. Backhausz holds significant academic responsibilities including serving as Supervisor and training lead for the Beyond The Edge Marie Curie Doctoral Network (2024-2027) and as a researcher at the National Laboratory for Health Security, Hungary (2023-2026). She is an editor for Acta Mathematica Hungarica since March 2021 and has been organizing the Departmental seminar of the Department of Probability Theory and Statistics since 2010. She actively contributes to the mathematical community through program committee memberships for major conferences like Eurocomb and by organizing workshops on graph limits, groups, and stochastic processes. Her editorial work further demonstrates her standing in the mathematical research community. As an educator, Dr. Backhausz teaches mathematical statistics, probability theory, and related subjects across multiple programs at ELTE, including courses for mathematics students, earth science students, and informatics programs, showcasing the interdisciplinary nature of her expertise.

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Csaba Noszályمشاهده پروفایل

استادیار

University of DebrecenHungary

Csaba Noszály is an Assistant Professor at the University of Debrecen , affiliated with the Faculty of Informatics and the Department of Applied Mathematics and Probability Theory . His work focuses on probability theory, stochastic processes, network modeling, and random graphs, with applications in numerical methods and statistical analysis. Research Areas : Probability theory, random graphs, network evolution models, stochastic optimization, and mathematical statistics. His publications explore continuous-time network evolution, triangle-based models, Taylor’s power law in networks, and algorithms for global minimization of conic functions. Publications : Csaba has contributed to studies on 3-interaction networks, random graph cliques, distance metrics in 2D samples, and strong laws of large numbers for random fields. Academic Role : He is a full-time faculty member with a primary focus on teaching and research in applied mathematics and probability.

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Sándor Pecsoraمشاهده پروفایل

استادیار

University of DebrecenHungary

Dr. Sándor Pecsora serves as an Assistant Professor at the Department of Applied Mathematics and Probability within the Faculty of Informatics, University of Debrecen. He maintains an active teaching role for core undergraduate courses including Discrete Mathematics, Probability Theory and Statistics, and Mathematics for Business and Economics, with office location in the Faculty of Informatics building (Kassai út 26, room E210/I210). His research specialization focuses on: Network modeling Random graphs These interests directly contribute to the department's broader research initiatives in probability theory, stochastic processes, and mathematical statistics. Educational materials for his courses are publicly accessible through his institutional profile. No scientific awards, grants, or student advisees are documented in the available institutional records. Dr. Pecsora remains a current, full-time faculty member actively engaged in the department's academic mission without indications of retirement or former status.

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Kristóf Bércziمشاهده پروفایل

پژوهشگر

Eötvös Loránd UniversityHungary

Kristóf Bérczi is a researcher at the Department of Operations Research, Eötvös Loránd University, Hungary. His work intersects computer science, mathematics, and operations research, focusing on theoretical and applied optimization problems. MSc and PhD in Operations Research, ELTE Postdoc at Hungarian Academy of Sciences Research Interests: Approximation algorithms Combinatorial optimization Matroid theory Submodular functions Algorithmic game theory Graph theory Recent Publication Trends: His 2024-2025 work explores matroid-constrained partitioning, inverse optimization algorithms, rainbow subgraph problems, and envy-free pricing models, often combining matroid theory with practical algorithm design. Scientific Contributions: Active in program committees (APPROX 2019, IPCO 2024, WALCOM 2025) Organized workshops on matroid optimization and matching theory Editorial board member of SIAM Journal on Discrete Mathematics Mentorship: Supervises PhD students Áron Jánosik, András Imolay, and others, with graduates now in postdoc/lecturer positions at institutions like CMM Chile and LSE UK.

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