Ph.D. Student — Computer Science
I study diffusion models for generating structured data (tables or time series) subject to quality or privacy constraints.
| Dept. | Computer Science |
|---|---|
| Inst. | Delft University of Technology |
| Advisors | Profs. Lydia Chen, Rihan Hai, Arie van Deursen |
| Lab | Data Intensive Systems |
| Status | Final Year PhD Student |
| Location | Delft, The Netherlands |
I'm a PhD student in the Data Intensive Systems Group at TU Delft, advised by Profs. Lydia Chen, Rihan Hai, and Arie van Deursen. My research explores how generative models, especially diffusion models, can be utilised for generating structured data under constraints.
Before starting my PhD, I completed my MSc in Computer Science at TU Delft, where my thesis (at ASML) was on developing a secure distributed forecasting system for the semiconductor industry.
You can reach me via the contact tab.
A full list is also on Google Scholar.
A patent for a secure forecasting framework that allows multiple parties to collaboratively make forecasts without leaking privacy using multi-party-computation. Based on my master thesis.
Teaching assistantships
| Term | Course | Role |
|---|---|---|
| Spring 2024 | Seminar on Distributed Machine Learning Systems | Visiting TA @ Université de Neuchâtel |
| Spring 2023 | Seminar on Distributed Machine Learning Systems | TA @ TU Delft |
Supervision & Mentoring
| Year | Student | Role | Project |
|---|---|---|---|
| 2026 | Abdelrahman Faqieh & Saul Sanchez Gonzalez (@ University of Bern) | Research Supervisor | Tabular-to-Image Generation with Diffusion Models |
| 2026 | Lorenzo Sibi (@ CERN) | Master Thesis Supervisor | Diffusion Models for Source Localisation |
| 2025 | Zhi Wen Soi & Chenrui Fan (@ University of Bern) | Research Supervisor | Federated Synthetic Data Generation for Feature and Temporally Misaligned Time Series |
| 2025 | Arnob Chowdhury (@ ASML) | Master Thesis Supervisor | Multi-task, Multi-Frequency Time Series Forecasting |
| 2024 | Julio Vega Sanchez (@ ASML) | Master Thesis Supervisor | Federated Multi-task Time Series Forecasting |
| 2024 | Shivaani Hari (@ IIT Delhi) | Project Supervisor | Tabular Vertical Federated Learning |
Academic Roles & Service
| Year(s) | Role | Organisation / Event | |
|---|---|---|---|
| 2026 | Reviewer | NeurIPS | |
| 2026 | Journal Reviewer | TKDD | |
| 2026 | Volunteer | ECIR | |
| 2025, 2026 | Program Committee Member | RecSys | |
| 2025 | Publicity Chair, DBML Workshop | IEEE ICDE | |
| 2024 | Volunteer | IEEE ICDE | |
| 2024 | Reviewer | IEEE TPDS |
Best reached by email.