Dong Xiaowen

Dong Xiaowen is an Associate Professor of Engineering Science at the University of Oxford, affiliated with the Department of Engineering Science. He is an academic member of the Machine Learning Research Group and the Oxford-Man Institute, and also serves as a Tutorial Fellow at Lady Margaret Hall. His research focuses on signal processing and machine learning techniques for analysing network data, with applications in social and economic sciences. Prior to joining Oxford, he was a postdoctoral associate at the MIT Media Lab and received his PhD from the Swiss Federal Institute of Technology (EPFL).

Xiaowen Dong is a researcher at the University of Oxford, focusing on signal processing, machine learning, network science, and computational social science. His work explores graph signal processing, learning Laplacian matrices, and the application of machine learning to financial and social systems. Dong's research includes analyzing mobility patterns, sentiment correlation in financial news, and segregation in urban areas. He also investigates neural architectures for graph-based learning and interpretable methods for social media analysis. His publications highlight the intersection of graph theory, signal processing, and machine learning in understanding complex systems.