<aside> 👋 Hello world!
I am a PhD student in AMLab, at University of Amsterdam, supervised by Prof. Erik Bekkers and Prof. Rita Fioresi. I am working on Geometric Deep Learning topics as part of the CaLIForNIA Marie Skłodowska-Curie Doctoral Network.
Previously, I was a research intern at EPFL in the Signal Processing Laboratory 4, supervised by Prof. Pascal Frossard and Prof. Laura Toni, working on discrete diffusion models for graph generation. Before EPFL, I was a research intern at KAIST in the Vision and Learning Laboratory, supervised by Prof. Seunghoon Hong and Jinwoo Kim, working on deep learning models for graph data based on random walks.
****I wrote my MSc Thesis on Sheaf Neural Networks in the Computer Laboratory at the University of Cambridge under the supervision of Prof. Pietro Liò and Prof. Andrea Passerini.
I got my MSc in Artificial Intelligence Systems from University of Trento and my BSc in Mathematics from University of Milan.
If you want to chat, feel free to contact me via email! ☺️
</aside>
Full list on my Google Scholar
Towards Variational Flow Matching on General Geometries Olga Zaghen, Floor Eijkelboom, Alison Pouplin, Erik J. Bekkers *ICLR 2025 DeLTa Workshop* (Oral Presentation) **(2025)
Graph Discrete Diffusion: a Spectral Study Olga Zaghen, Manuel Madeira, Laura Toni, Pascal Frossard *ICLR 2025 DeLTa Workshop & XAI4Science Workshop* (2025)
Revisiting Random Walks for Learning on Graphs Jinwoo Kim, Olga Zaghen, Ayhan Suleymanzade, Youngmin Ryou, Seunghoon Hong *ICLR 2025* (Spotlight Presentation)(2024)
Sheaf Diffusion Goes Nonlinear: Enhancing GNNs with Adaptive Sheaf Laplacians Olga Zaghen, Antonio Longa, Steve Azzolin, Lev Telyatnikov, Andrea Passerini, Pietro Liò ICML 2024 GRaM Workshop (2024)
TopoX: A Suite of Python Packages for Machine Learning on Topological Domains Mustafa Hajij et al. JMLR (2024)