Biography
I’m a PhD student at the QUVA lab at the University of Amsterdam supervised by Yuki Asano and Cees Snoek. Additionally, I am enrolled in the ELLIS PhD program in collaboration with Qualcomm. My research primarily focuses on foundation models, and how they can be efficiently adapted to incorporate desirable behaviors and properties.
Previously, I completed my Master’s degree in Artificial Intelligence at the University of Amsterdam, where I mainly worked on computer vision and causal representation learning. I also hold a Bachelor’s degree in Computer Science from the University of Amsterdam.
Interests
- Foundation Models
- Computer Vision
- Self-Supervised Learning
Education
MSc in Artificial Intelligence, 2023
University of Amsterdam
BSc in Computer Science, 2021
University of Amsterdam
News
- Sep 2023: I have started my PhD on Adaptable Foundation Models at the University of Amsterdam under the supervision of Cees Snoek and Yuki Asano.
- Apr 2023: I gave a tutorial on Causal Identifiability from Temporal Intervened Sequences as a part of the Causality and Causal Representation Learning module of the Deep Learning 2 course at the University of Amsterdam.
- Jan 2023: I gave an invited guest lecture “MLRC 2021 - Our Experience” at the introductory lecture of the Fairness in AI course of the University of Amsterdam.
- Aug 2022: Our paper “C-3PO: Towards Rotation Equivariant Feature Detection and Description” has been accepted to the VIPriors workshop at ECCV 2022.
- Jul 2022: Our poster on “Quantifying CLIP’s Ability to Perform Cross-Modal Grounding using Attention-Model Explainability” received the best poster award at the XAI course of the University of Amsterdam.
- Apr 2022: Our paper on the Reproducibility Study of “Counterfactual Generative Networks” received the Best Paper Award of MLRC 2021.
- Jan 2022: Our paper “The Cost of Reinforcement Learning for Game Engines: The AZ-Hive Case-study” has been accepted to ICPE 2022.
- Jun 2021: Our presentation “The Cost of AlphaZero: the Hive Case” received the best presentation award at CompSys-2021.
Recent Publications
We reproduce the paper “Counterfactual Generative Networks” by Axel Sauer and Andreas Geiger to identify which parts of the experimental results supporting their claims can be reproduced, and at what cost in terms of resources (e.g., computational cost, development effort, and communication with the authors).
