Current Phenomenon
Interactive field. Move your cursor through the background. Reload the page to cycle to a different dynamical system.
Dynamical Systems / AI for Science / Physical AI
Learning dynamical systems with deep learning.
I am a PhD researcher in AI for Science, with a focus on learning dynamical systems using Deep Learning, supervised by Prof. Efstratios Gavves and Dr. Andrii Zadaianchuk at Universiteit van Amsterdam.
- Physical AI
- Dynamical systems
- Equivariant learning
- Scientific machine learning
- Cellular dynamics
PhD Candidate, AI for Science Universiteit van Amsterdam Scientific Supervisor, Embodied AI MSc Research Teams Vrije Universiteit Amsterdam Former ML Researcher Centrum Wiskunde & Informatica
Current application T-cell and cancer-cell interaction modeling
Signature Result
T-cell and cancer-cell interaction dynamics
A time-resolved interaction sequence grounding my work on cellular dynamics and physical AI, capturing pursuit, contact, and response as the system evolves.
About
Research focus and background
A core application of my work lies in cellular dynamics, where I study how T cells interact with and attack cancer cells using data driven and physics inspired models.
I hold a Master's in Artificial Intelligence from Vrije Universiteit (VU), in collaboration with Universiteit van Amsterdam (UvA) (Grade 8.5/10). My thesis research focused on Generative AI Architectures for Structured Graphs and received a 9/10.
I am a graduate in Electrical and Computer Engineering with a lifelong passion for Mathematics. From a young age, I found joy in solving mathematical problems, which led me into the field of AI.
When I am not immersed in my research, I enjoy reading, good coffee, and long walks in nature.
Learning Dynamical Systems
My PhD research focuses on learning dynamical systems with deep learning in the context of AI for Science.
- Supervised by Prof. Efstratios Gavves and Dr. Andrii Zadaianchuk
- Universiteit van Amsterdam
Cellular Dynamics
A core application of my work is understanding how T cells interact with and attack cancer cells.
- Data driven and physics inspired models
- Dynamical systems and physical AI orientation
Academic Background
My academic background combines Artificial Intelligence with Electrical and Computer Engineering.
- MSc in Artificial Intelligence, Grade 8.5/10
- Thesis on Generative AI Architectures for Structured Graphs, Grade 9/10
Selected Work
Selected publications
A few selected papers and research outputs.
Morpheus
Benchmarking physical reasoning of video generative models using real physical experiments.
Read paper
Autoregressive Models for Knowledge Graph Generation
ARK and SAIL for autoregressive knowledge graph generation with strong semantic validity and controlled graph completion.
arXiv
Selected Publications
Selected papers and ongoing work, including physical reasoning and generative modeling for structured scientific domains.
View publicationsNews
Recent updates
Recent milestones, talks, teaching, and research updates.
Recent news
All newsOct 30, 2025
I had the plesure of presenting the work on Generative AI for Graphs on the ELLIS Amsterdam Research Retreat. This was a wonderful experience, and I am very happy to have been able to share the work with the community.
Oct 16, 2025
Check out this new article i co-authored in AI for Food Allergies as part of the HuggingFace Science collaboration team. It’s a great example of how AI can be used to improve the quality of life for people with food allergies.
Sep 01, 2025
I’m excited to share that I’ll be a scientific supervisor in Embodied AI, for the research projects of the master students for the course of Evolutionary Computing at VU Amsterdam!
Apr 01, 2025
I’m excited to share that I’ll be a teaching assistant for the master course Natural Language Processing at VU Amsterdam!