Hyperbolic Random Graphs Professors and Supervisors in Netherlands

Tobias Müllerمشاهده پروفایل

استاد

University of GroningenNetherlands

Prof. Tobias Müller is a Professor at the Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence at the University of Groningen. His academic journey includes previous positions at Utrecht University, CWI (Centrum Wiskunde & Informatica), Tel Aviv University, and Eindhoven University of Technology, with a doctorate from the University of Oxford under Colin McDiarmid. His research focuses on combinatorics, probability theory, random graphs, percolation, discrete and stochastic geometry, and combinatorial game theory. He has contributed extensively to understanding complex networks, hyperbolic models, and geometric random structures. Research Interests: Random Graphs and Percolation Theory Discrete and Stochastic Geometry Hyperbolic Network Models Probabilistic Combinatorics Geometric Probability Graph Algorithms and Connectivity Notable Contributions: Analysis of Voronoi and Poisson-Voronoi percolation in hyperbolic planes. Studies on Mallows random permutations and their cycle structures. Research on component games and logical limit laws in graph theory. Investigations into the geometry and properties of random geometric graphs. Grants & Collaborations: Active in organizing workshops and conferences on random graphs and geometric networks, including the BIRS Workshop on Random Geometric Graphs and the STAR Workshops series. Labs/Teams: Member of the Bernoulli Institute’s research groups, focusing on stochastic studies, combinatorics, and algorithmic methods.

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Clara Stegehuisمشاهده پروفایل

دانشیار

University of TwenteNetherlands

Clara Stegehuis serves as Associate Professor in Mathematics of Operations Research, specializing in the mathematical foundations of complex networks. Her research establishes critical connections between theoretical graph models and real-world applications in wireless communications and chemical reaction systems, with 68 research outputs including 34 articles and 16 preprints. Her primary research domains include: Random Graph Theory and Scale-Free Networks Hypergraph Modeling and Sampling Algorithms Geometric Network Analysis Stochastic Processes on Networks Combinatorial Optimization for Network Structures Network Applications in Wireless Systems Recent publications (2023-2025) demonstrate methodological innovation in hypergraph sampling (Hypercurveball algorithm) and geometric network detection, while addressing practical challenges in mmWave networks, cellular resilience, and reaction network analysis. Her work consistently bridges abstract mathematical frameworks with engineering applications through rigorous probabilistic modeling. Dr. Stegehuis has supervised two graduate students and contributed two significant datasets to the research community. Though no specific awards are documented in the provided materials, her h-index of 9 and consistent publication output (10 papers in 2025) reflect substantial scholarly impact. Current research initiatives focus on multi-connectivity optimization for wireless networks, geometric structure detection in scale-free graphs, and applying random graph theory to model out-of-equilibrium chemical systems, often through interdisciplinary collaboration with domain experts.

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Julia Komjathyمشاهده پروفایل

دانشیار

Delft University of TechnologyNetherlands

Julia Komjathy is an Associate Professor at Delft University of Technology's Faculty of Electrical Engineering, Mathematics and Computer Science (EWI), within the Delft Institute of Applied Mathematics (DIAM). She leads the Applied Probability Group and focuses on probabilistic network models, including random graphs, spatial networks, and epidemic processes. Her research explores structural properties like 'explosion' in weighted graphs and phase transitions in contact processes. Education: Ph.D. in Mathematics from TU Budapest under Professors Márton Balázs and Károly Simon (2012). Thesis: Topics in Markov chains: Mixing and escape rate . Research Interests: Random graph models of complex networks Spatial random graphs and hyperbolic geometry Weighted random graphs and distance evolution Epidemic spread dynamics on networks Branching processes and percolation theory Phase transitions in scale-free systems Professional Activities: Organizer of TU Delft's Probability & Statistics Seminar Keynote speaker at WAW 2024 (Warsaw) and Discrete Probability Days 2023 (Barcelona) Supervised 4 PhD students, including Enrico Baroni (2017), Viktoria Vadon (2020), and Joost Jorritsma (2023) Awards: None explicitly listed, but her work has been published in top journals like PNAS, Annals of Applied Probability, and Random Structures & Algorithms. Current Projects: Investigating degree-dependent contact processes, first-passage percolation growth regimes, and cluster-size decay in spatial networks.

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Pim van der Hoornمشاهده پروفایل

استادیار

Eindhoven University of TechnologyNetherlands

Pim van der Hoorn is an Assistant Professor in Probability at the Department of Mathematics and Computer Science at Eindhoven University of Technology. He is also a member of the Eindhoven Young Academy of Engineers and serves as a board member of the Dutch Network Science Society. His primary research affiliation is with the Institute for Complex Molecular Systems (ICMS), where he is part of the ICMS Core research group. Dr. van der Hoorn's research focuses on developing mathematical foundations of network science using probability theory, statistics, random graphs and graph limits. His work centers around two main pillars: the design of mathematical frameworks for statistical analysis of networks and understanding emerging geometry in networks. He also applies network science to solve problems in computational biology and materials science, particularly in studying cell-cell interactions in cancer and molecular charge transport in organic semiconductors. His recent publications demonstrate a strong trend toward unifying theoretical frameworks for network analysis while simultaneously applying these frameworks to solve complex problems across disciplines. His work bridges pure mathematical theory with practical applications, showing how network science can provide insights into diverse fields from cancer biology to materials engineering. Dr. van der Hoorn is actively involved in teaching with courses including Extreme values and other catastrophes, Network Statistics for Data Science, and Measure, Integration and Probability Theory. His educational activities reflect his research interests, providing students with both theoretical foundations and practical applications of probability and network science. He collaborates extensively across disciplinary boundaries, working with researchers in computational biology, cancer research, and materials science. His research has received support from organizations including the Netherlands Organization for Scientific Research (NWO) and the Immunoengineering Program of the Institute for Complex Molecular System.

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