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Meet Our Research Team

Laszlo Lovasz Hungarian-American mathematician
Project Leader - Rényi Institute
László Lovász (born March 9, 1948) is a Hungarian-American mathematician and professor emeritus at Eötvös Loránd University, best known for his work in combinatorics, for which he was awarded the 2021 Abel Prize jointly with Avi Wigderson.
Barabasi Albert-Laszlo
Principal Investigator - CEU
Albert-László Barabási is a network scientist, fascinated with a wide range of topics, from unveiling the structure of the brain to treating diseases using network medicine, from the emergence of success in art to how does science really works.
Jaroslav Nešetřil
Principal Investigator - CUNI
Jaroslav (Jarik) Nešetřil (born March 13, 1946 in Brno) is a Czech mathematician, working at Charles University in Prague. His research areas include combinatorics, graph theory, algebra, posets, and computer science.
Iva Bacic erc dynasnet researcher
Researcher - CEU
I am Postdoc working on physical networks under the supervision of Márton Pósfai. Currently studying growth models for linear physical networks in which edges are non-intersecting straight segments.
Martin Balko dynasnet researcher
Researcher - CUNI
I work on extremal problems for ordered graphs and hypergarphs.
Luka Blagojevic erc dynasnet researcher
Researcher - CEU
I am a PhD student, with thesis research on reference models of physical networks, ways to describe them and their robustness property.
Márton Borbényi
Researcher - Rényi
My goal is to approximate various graph parameters and graph polynomials in sparse large graphs.
Samuel Braunfeld
Researcher - CUNI

Samuel Braunfeld is a postdoctoral researcher at Charles University, working on model theory and combinatorics.

Tomas Bures dynasnet researcher
Researcher - CUNI
In DYNASNET I focus on modeling collective adaptive systems and approximating their decisions using neural networks as well as network control and assemblies.
Czifra Domonkos fiatal kutató a dynasnet projekten
Researcher - Rényi
My research focuses on the epidemic spreading on geometric and real-world metapopulation networks. I'm interested in understanding what role the different parts of the network play in an epidemic, and how the initial seed distribution influences the speed and the final size of the epidemic.