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I am  interested in graph theory, probability, numerical methods for dynamical systems, partial differential equations, stochastic analysis, and randomized algorithms. I am especially fascinated by the synergy of these fields, which often reveals fundamental connections between discrete and continuous mathematical objects. I place significant emphasis on ensuring that my work has societal relevance and generates tangible, practical impact. To date, the most notable contributions of my research have been in the fields of chemistry and materials science. I am also trying to broaden this scope to address challenges within complex societal systems.

Some of my past, current, and future research interests include (in arbitrary order):

• Mathematical foundation for network science
• Random matrices and spectral properties of sparse graphs
• Randomised approximation algorithms
• Random graph representation of nonlinear PDEs
• Percolation problems in random environments
• Parameter inference problems for stochastic differential equations
• Automata and graph grammars
• Dynamical systems that approximately solve NP problems
• Random graph theory for coalescence, gelation, and phase 
• Mathematical aspects of complex systems, including statistical physics view on epidemiology

— Eager to discuss these or similar topics? Please don’t hesitate to contact me. Email usually works best.

Student projects: I’m happy to advise motivated students, preferably on matters I can pretend to be an expert myself. Several suggestions for projects can be found . If you like interacting with industry, I usually have internship projects that involve the aforementioned topics.

See also: , feel free to enquire.

— a broad research theme at the Mathematical Institute.

an outrech venue for students and by students.

Postdocs

• Rik Versendaal, now faculty at TU Delft

PhD Students

• Ruben Hendriks
• Mike de Vries
• Verena Schamboeck (, ), now a modeller at Austrian Power Grid 
• Yuliia Orlova (, ), now a postdoc at ľ¹Ï¸£ÀûÓ°ÊÓ of Amsterdam

Master Students

• Myrthe van Leewen ()
• Willem Kalkman ( 2025)
• Yeyang Hu ( 2024)
• Josanne Verheule ( 2024, collaboration with RIVM)
• Hannah Onverwagt ( 2023)
• Niels Scholte ( 2023, collaboration with CBS)
• Fleur Slegers ( 2023, now PhD at UU)
• Mike de Vries (thesis 2023, now PhD at UU)
• Niek Mooij (, now PhD at UU)
• Camillo Schenone (, )
• Andi Lin ( 2022, now PhD at Nijmegen)
• Thomas Bakx (thesis 2022, , with Elisa Chisari, now PhD student at the physics department UU)
• Nynke Brouwer ( 2021, data scientist at Moraves)
• Yaïr Hein (, now PhD at UU)
• Frits Verhagen  ( 2020, joint supervision with Umut Gürsoy), 
  now PhD Student at ľ¹Ï¸£ÀûÓ°ÊÓ of Singapore
• Femke Ieperen ( 2020, , ), now developer at Scientific Volume Imaging

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