On June 21st, 2025, we had the honor of welcoming Professor Dung from Tan Tao University to deliver an academic seminar on Federated Learning for students in URA research group, held at the VNPT Laboratory.
Throughout the seminar, Professor Dung provided a comprehensive overview of Federated Learning which is a decentralized machine learning approach that enables multiple clients to collaboratively train models without sharing raw data. The presentation covered several core aspects, including fundamental concepts, classification of federated learning types (e.g., horizontal, vertical, and hybrid FL), the main research problems being addressed in the field, and the practical as well as theoretical challenges that researchers often encounter when deploying FL systems.
The seminar served as a valuable knowledge-sharing session, especially for students and research fellows who are beginning to explore the frontier of privacy-preserving machine learning. Beyond foundational content, Professor Dũng also introduced an emerging research direction that drew great interest from attendees: the integration of Federated Learning with multi-agent systems. This interdisciplinary topic opens up new avenues for innovation and experimentation, particularly in scenarios involving distributed intelligent agents that learn and adapt in coordination.
The event concluded with a casual and engaging lunch between Professor Dung and members of the URA team. It was not only an opportunity to continue the academic conversation in an informal setting but also to strengthen connections and foster potential future collaborations.
We sincerely thank Professor Dung for his time, expertise, and inspiring insights. His visit has sparked many new ideas and discussions that will likely influence our ongoing research directions.