Experience

  1. Postdoc in Artificial Intelligence for Climate

    Vrije Universiteit Amsterdam
    Foundation models for climate

  2. PhD in Computer Science (Artificial Intelligence), expected 2025

    University of Amsterdam

    Main Publications:

    • Roto-translated Local Coordinate Frames For Interacting Dynamical Systems (NeurIPS 2021)
    • Latent Field Discovery in Interacting Dynamical Systems with Neural Fields (NeurIPS 2023)
    • Graph Neural Networks for Learning Equivariant Representations of Neural Networks (ICLR 2024, Oral)
    • From MLP to NeoMLP: Leveraging Self-Attention for Neural Fields (Preprint, 2024)

  3. Research Assistant

    University of Amsterdam

    Visual Scene Graph Generation using Graph Transformer Networks

    • Development of a novel Graph Network for visual scene graph generation that explicitly utilizes both local and global information on the graph space, using Transformer blocks to attend to global context.

  4. Computer Vision & Machine Learning Engineer

    P.A.N.D.O.R.A. Robotics
    • Development of a general-purpose image classification API using RGB-D sensor data, as well as a benchmarking API for performance evaluation of computer vision algorithms; motion detection and obstacle detection from RGB-D sensor data.
Teaching Experience

  1. Deep Learning II, Teaching Assistant

    University of Amsterdam, MSc AI

  2. Deep Learning II, Teaching Assistant

    University of Amsterdam, MSc AI

  3. Machine Learning I, Teaching Assistant

    University of Amsterdam, MSc AI

  4. Deep Learning, Teaching Assistant

    University of Amsterdam, MSc AI

  5. Machine Learning I, Teaching Assistant

    University of Amsterdam, MSc AI
PhD Supervision
  1. Eliot Walt (co-supervised with Dim Coumou)
    Deep learning for extended-range weather forecasting
    Vrije Universiteit Amsterdam, Institute for Environmental Studies (IVM)
Thesis Supervision
  1. Constantinos Dimitriou
    Regional Medium-Range Forecasting
    Vrije Universiteit Amsterdam, BSc AI
  2. Kevyn M. Smit
    Evaluating Fine-Tuning Methods for Aurora’s S2S Forecasting: A Comparison of LoRA and FourierFT
    Vrije Universiteit Amsterdam, BSc AI
  3. Danilo Rijpstra
    Latent space analysis on heatwave clustering/detection
    Vrije Universiteit Amsterdam, BSc AI
  4. Mikołaj Magiera
    Interpretation and Visualization of Medium-Range Weather Forecasts Through Attention Heatmaps
    Vrije Universiteit Amsterdam, BSc CS
  5. Mark Mitrani (co-supervised with Melinda Galfi)
    Predicting Weather-driven Crop Failures with Space-time Transformers
    Vrije Universiteit Amsterdam, MSc AI
  6. Victor Kyriakou
    Equivariant Trajectory Forecasting with Latent Orientation Graph Networks
    University of Amsterdam, MSc AI
  7. Daniel Perez Jensen
    Heterogeneous Graph Neural Networks for River Flow Prediction in the Rio Copiapó Watershed
    University of Amsterdam, MSc AI
  8. Daniël (Stijn) Hamerslag
    Driving on Data: Object Detection in Urban Driving Scenes
    University of Amsterdam, BSc AI
Extracurricular
Thinking Hour
University of Amsterdam ∙ September 2021 – August 2022
Organizing and hosting “Thinking Hour”, a reading group with invited talks and tutorials
Reviewer
ICLR (International Conference on Learning Representations)
2026 2025 2023
ICML (International Conference on Machine Learning)
2025 2021
LoG (Learning on Graphs)
2023 2022
NeurIPS (Neural Information Processing Systems)
2023
CVPR (The IEEE/CVF Conference on Computer Vision and Pattern Recognition)
2023
CDS Workshop NeurIPS (A Causal View on Dynamical Systems)
2022
CVIU (Computer Vision and Image Understanding)
2022
PAMI (IEEE Transactions on Pattern Analysis and Machine Intelligence)
2022
ECCV (European Conference on Computer Vision)
2020