Afsana Khan

Federated Learning | Privacy-Preserving Machine Learning | Data Fusion

I recently completed my PhD from the Department of Advanced Computing Sciences at Maastricht University, Netherlands. My doctoral research focused on federated learning and privacy-preserving data analysis, particularly on how organisations can learn from distributed data without having to share their raw data.

My broader research interests are in machine learning for distributed, heterogeneous, and privacy-sensitive data, with an emphasis on developing methods that are useful in real-world settings. More recently, I worked as a Researcher at the same department on the Interreg DigiMach project, where I worked on data-driven approaches for machine health monitoring using industrial operational data.

I obtained an M.Sc. in Computer Science with a specialization in Distributed Systems from the University of Tartu, Estonia. During my master's studies, I worked as a Research Assistant at the Mobile and Cloud Laboratory, where I contributed to the EU Horizon project RADON and the Estonian Research Council-funded project CIISIM. Before that, I obtained my B.Sc. in Computer Science and Engineering from the Bangladesh University of Professionals.

Apart from research, I also enjoy travelling and painting. I have visited over 20 countries across three continents, and I like to paint in my leisure time.

News

September 2026Latest	Our paper, HybridFL: A Federated Learning Approach for Financial Crime Detection, was accepted at FLTA 2026. 🎉
August 2026Latest	Another paper, Federated Learning for Distributed CNC Tool Wear Prediction, was accepted at SSS 2026.
June 2026	Organised a seminar, "Federated Systems for Distributed Intelligence", at the Department of Advanced Computing Sciences, Maastricht University.
June 2026	Defended my PhD dissertation, Unlocking Value of Data with Vertical Federated Learning. 🎓
April 2026	Guest lecture on "Introduction to Federated Learning" at the Master's Privacy Seminar at Tilburg University.