CV
Education
- PhD Candidate, Complexity Science Hub & TU Wien, Vienna, 2023 – present
- Machine learning for complex adaptive systems, with a focus on supply chain dynamics. Supervisor: Stefan Thurner.
- MSc Physics (9.0/10 GPA; 4.0/4.0 US), Universiteit van Amsterdam, 2020 – 2023
- Theoretical Physics track
- Thesis: Approximate Inference in Spiking Neural Networks, Max Planck Institute for Dynamics and Self-Organization, Göttingen. Supervisors: V. Priesemann, F. Mikulasch, L. Rudelt.
- BSc Physics & BSc Mathematics (cum laude), Radboud Universiteit, Nijmegen, 2017 – 2020
- Thesis: Path-Integral Control Theory Applied to Evolutionary Dynamics, Donders Institute. Supervisors: H.J. Kappen, A. Nourmohammad.
- Honours Programme: funded research at the University of Washington, Seattle.
Publications
K. van Driel, L.N. Ialongo, P.A. Astudillo-Estévez, S. Thurner. Generalized Degrees for Scalable Discrete Time Dynamic Graph Generation. Learning on Graphs Conference, 2025. Oral (extended abstract). [paper] [code]
K. van Driel, L. Rudelt, V. Priesemann, F.A. Mikulasch. Prediction Mismatch Responses Arise as Corrections of a Predictive Spiking Code. bioRxiv preprint, 2023. [paper] [code]
Talks & Conferences
- European Forum Alpbach – Complexity science in the green transition, 2025
- Learning on Graphs Conference – Oral presentation, 2025
- Summer School on Economic Networks, University of Oxford, 2024
- ICLR – Volunteer, 2024
- CSH Winter School on Complex Systems, 2024
- Summer School on Economic Complexity, Maastricht University, 2024
Experience
- Quantitative Analyst (part-time), Gimli, 2021 – 2022
- Game-theoretic models for Flashbots MEV blind auction bid optimisation.
- Intern Analyst (part-time), MindHash, 2020 – 2021
- Machine learning for object extraction and tracking in LiDAR point cloud data.
Blommers Coffee Roastery, Nijmegen, 2020 – 2021
- Undergraduate Researcher, University of Washington, Seattle, 2020
- Computational research on constrained mutations in genome space.
- Teaching Assistant / Tutor, Radboud Universiteit, 2015 – 2020
Activities
- Reading group on EU industrial and economic policy (organiser), CSH, 2024
- Honours Programme, interdisciplinary research (Radboud), 2017 – 2020
- Symposium Committee, study association Marie Curie, 2017 – 2019
- Physics Bachelor Representative at high schools & universities, 2017 – 2019
Skills
- Programming: Python (PyTorch, PyTorch Geometric, JAX), CUDA / Triton, C++, LaTeX, Git, Linux / Slurm
- Methods: Graph neural networks, Normalizing flows, Dynamic graph generation, Spiking neural networks, Variational inference, Network science, Probabilistic generative models
- Languages: Dutch (native), English (fluent), German (B2)