Hello!
I’m a DDSA Postdoctoral Fellow at Aarhus University 🇩🇰, working on Robust Graph Unlearning.
My research focuses on Privacy-Preserving Machine Learning and Machine Unlearning. I have published papers at NeurIPS, EMNLP, and Springer’s Machine Learning, among others.
My research focuses on Privacy-Preserving Machine Learning and Machine Unlearning. I have published papers at NeurIPS, EMNLP, and Springer’s Machine Learning, among others.
Selected Highlights
| Year | Achievement |
|---|---|
| 2026 | 📘 Accepted at NeurIPS 2026 |
| 2026 | 📘 Accepted at EMNLP 2026 Findings |
| 2026 | 🏅 Selected as a DAAD AInet Fellow — Postdoc-NeT-AI on Reliable AI |
| 2026 | 🏅 Awarded a DDSA Postdoctoral Fellowship on Robust Graph Unlearning (Danish Data Science Academy) |
| 2026 | 📘 Published in Springer’s Machine Learning Journal, ECML-PKDD 2026 Journal track |
| 2026 | 🏅 Won a Postdoc position at Aarhus University |
| 2026 | 🎓 Defended my Ph.D. cum laude with Doctor Europaeus distinction! |
| 2025 | 📘 Published in Springer’s Machine Learning Journal |
| 2025 | 👥 Hosted WIPE-OUT, a Workshop on Machine Unlearning at ECML-PKDD 2025 |
| 2025 | 📘 Published at IJCAI 2025 Demo, CIKM 2025 |
| 2025 | 🌍 Visiting Ph.D. — Aarhus University, Denmark |
Projects
Lethe Benchmark for Edge Unlearning in Graph Neural Networks Link inference attacks for evaluating edge unlearning methods. Accepted at NeurIPS 2026. View on GitHub
WIPE-OUT 2 Workshop on Machine Unlearning and Privacy Preservation Held at ECML-PKDD 2026, Naples. Workshop website
ERASURE Extendible Machine Unlearning Framework An open-source framework for Machine Unlearning research. View on GitHub