CV & Interests
I’m currently in the first year of my PhD at the University of Amsterdam, focusing on model correction—primarily through machine unlearning. My background includes experience in both research and industry, and I’ve had the opportunity to publish at CVPR and ICML 2025.
My current work centers on uncertainty quantification and information-theoretic approaches to machine unlearning. I’m open to internships or collaborative opportunities where I can contribute to meaningful, high-impact research.
News
- [July 2025] Our paper Unleashing Uncertainty: Efficient Machine Unlearning for Generative AI will be presented at the ICML 2025 workshop on Machine Unlearning for Generative AI.
- Reviewer for ICCV 2025, one of the top-tier conferences in Computer Vision
- [June 2025] Our paper, LoTUS: Large-Scale Machine Unlearning with a Taste of Uncertainty will be presented at the main conference of Computer Vision and Pattern Recognition (CVPR), taking place June 10-15 2025. Looking forward to seeing you there!
Short Bio
I am working at the Visual Computing Lab. My research focuses on correction methods that remove private or harmful information from pre-trained AI models. I am also pursuing a PhD at the University of Amsterdam in the same field, under the supervision of Efstratios Gavves (UvA) and Theodoros Semertzidis (CERTH). Our next milestone is to prevent Diffusion Models from generating impermisible images.