About Me
I am Roberto Gheda, PhD student at TU Delft. My research interest spans across graph theory, security and fairness in machine learning, and bayesian networks. I have been working along companies such as ASML and KPN. Feel free to reach out to me for any collaboration opportunity!
Publications
First author publications:
- “Checkmate! Watermarking Graph Diffusion Models in Polynomial Time”.
Roberto Gheda, Abele Malan, Robert Birke, Maksim Kitsak, Lydia Chen.
TL;DR First to apply watermark on graph data in polynomial time by using graph diffusion models and spectra of random matrices.
ICLR 2026. [Paper] - “Collaborative and Confidential Junction Trees for Hybrid Bayesian Networks”.
Roberto Gheda, Abele Malan, Thiago Guzella, Carlo Lancia, Robert Birke, Lydia Chen.
TL;DR Multi-party root-cause analysis framework for Bayesian Networks, with improved scalability and precision.
NeurIPS 2025. [Paper] [Poster]
Other publications:
- “Test-time Graph Extrapolation via Progressive Anchor-Guided Expansion”
Abele Malan, Roberto Gheda, Robert Birke, Lydia Chen.
TL;DR Sampling conditioning to preserve validity of graphs generated by diffusion models at scale.
ICLR (TTU Workshop) 2026. [Paper] - “SuperHype: Hypergraph Generation via Graph-Superposition Decomposition”.
Lucas Gantes, Abele Malan, Roberto Gheda, Robert Birke, Lydia Chen.
TL;DR A diffusion model for hypergraphs, with a scalable latent representation.
Under review, 2026. - “MAGiC: Attributed Graph Generation via Mixed-type Diffusion and Coarsening”.
Abele Malan, Roberto Gheda, Robert Birke, Lydia Chen.
TL;DR A diffusion model for generating graphs with rich node features.
Under review, 2026.
Education
PhD, TU Delft
03/2025 - now
PhD Student in Machine Learning and Network Science.
Advisors: Prof. Lydia Chen, Prof. Maksim Kitsak
MSc, TU Delft
09/2022 - 01/2025
MSc Machine Learning.
Thesis: Collaborative and Confidential Bayesian Networks.
Advisors: Prof. Lydia Chen, Dr. Thiago Guzella
BSc, University of Trento
09/2019 - 07/2022
BSc Computer Science.
Thesis: Integration of PlanSys2 for a fleet of AGVs.
Advisor: Prof. Marco Roveri
Industry Collaboration
KPN
03/2025 – present
Secure Data Sharing for Networks.
ASML
03/2024 – 01/2025
Collaborative and confidential root-cause analysis for semiconductor manufacturing via Bayesian Networks.
References
- Prof. Lydia Chen - PhD advisor and MSc thesis supervisor
Associate Professor, TU Delft.
y.chen-10@tudelft.nl - Prof. Maksim Kitsak - PhD advisor
Associate Professor, TU Delft.
m.a.kitsak@tudelft.nl - Prof. Piet van Mieghem - Head of research group
Full Professor, TU Delft.
p.f.a.vanmieghem@tudelft.nl - Prof. Robert Birke - Research collaborator
Associate Professor, University of Turin.
robert.birke@unito.it - Dr. Eric Smeitink - Industry advisor
Manager of Technology, KPN.
eric.smeitink@kpn.com - Dr. Thiago Guzella - Industry advisor
Senior Data Scientist, ASML.
thiago.guzella@asml.com