Current Phenomenon

Interactive field. Move your cursor through the background. Reload the page to cycle to a different dynamical system.

Learning Dynamics / AI for Science / Generative AI

Antonis Vozikis

PhD researcher at the University of Amsterdam, developing deep-learning models of dynamical systems. I study how immune and cancer cells interact using data-driven and physics-inspired methods, and also work on generative AI. I am supervised by Prof. Efstratios Gavves and Dr. Andrii Zadaianchuk.

  • Learning dynamics
  • Generative AI
  • 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
View Publications Contact GitHub LinkedIn
Current focus Learning dynamics
MSc in AI Vrije Universiteit Amsterdam and Universiteit van Amsterdam
Background Electrical and Computer Engineering
Portrait of Antonis Vozikis
Current application T-cell and cancer-cell interaction modeling
38-second sequence

Live imaging and segmented trajectories

Cellular Dynamics

A cellular encounter in motion

BEHAV3D live imaging of T cells interacting with cancer organoids. The left panel shows microscopy data; the right panel shows a segmented view. These interactions motivate my research on learning cellular dynamics.

Imaging: BEHAV3D

  • Cellular dynamics
  • Learning dynamics

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.

01

Learning Dynamics

My main research focus is learning dynamics with deep learning in the context of AI for Science.

  • Supervised by Prof. Efstratios Gavves and Dr. Andrii Zadaianchuk
  • Universiteit van Amsterdam
02

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
  • Learning and modeling cellular interaction dynamics
03

Generative AI

I also work on generative AI, including autoregressive models for structured graphs and the physical behavior of video generative models.

  • Autoregressive knowledge graph generation
  • Video generative models and physical reasoning

Podcast

AI in the Physical World

AI in the Physical World cover artwork

Conversations with researchers about how AI helps us understand, design, and control the physical world — from robotics and embodied intelligence to physics, biology, and materials.

All episodes Listen on Spotify Apple Podcasts

News

Recent updates

Recent milestones, talks, teaching, and research updates.

Recent news

All news

Oct 14, 2026

The first episode of AI in the Physical World is out! I started this podcast to share our research and open questions through conversations with people who might never read our papers.