Xiaowen Dong

Xiaowen Dong is an Associate Professor in the Department of Engineering Science at the University of Oxford, affiliated with the Machine Learning Research Group and the Oxford-Man Institute. He is also a Tutorial Fellow at Lady Margaret Hall. Prior to Oxford, he was a postdoctoral researcher at MIT Media Lab and earned his PhD from EPFL. His research focuses on signal processing and machine learning for analyzing network data, with applications in social, urban, and financial systems.

• Education: PhD from École Polytechnique Fédérale de Lausanne (EPFL), Switzerland.
• Research Interests: Graph signal processing, geometric deep learning, network topology inference, computational social science, and urban computing.

He has received awards including the Turing Fellowship and outstanding paper recognitions. His work spans theoretical advancements and practical applications in network analysis, with collaborations extending to institutions like MIT, EPFL, and the Alan Turing Institute.

Notable achievements include contributions to understanding urban segregation, pandemic impacts on mobility, and financial network dynamics. He advises multiple doctoral and master's students across disciplines and actively organizes workshops and conferences in graph-based learning and network science.