Chen Xu

Chen Xu is an Associate Professor in the Department of Mathematics and Statistics at the University of Ottawa. He holds an M.A. from York University and a PhD from the University of British Columbia. His research focuses on sparse modeling, statistical learning, and big data processing, with an emphasis on both theoretical and computational advancements. Dr. Xu is affiliated with the Faculty of Science and contributes to editorial roles for journals such as the Journal of the American Statistical Association and Electronic Journal of Statistics.

Education:

• M.A., York University
• PhD, University of British Columbia

Research interests include feature selection, regularization methods, kernel methods, and high-dimensional regression. His work addresses computational challenges in big data, proposing efficient algorithms for tasks like singular value decomposition, clustering, and distributed feature screening. Recent publications highlight advancements in multiview PCA, low-tubal-rank tensor recovery, and model-free regression techniques.

Publications span prestigious journals like the Journal of the American Statistical Association and IEEE Transactions series, focusing on statistical methodology, machine learning applications, and scalable computational solutions for complex data problems.

Editorial Service:

• Associate Editor, Journal of American Statistical Association-T&M (2023–present)
• Associate Editor, Electronic Journal of Statistics (2023–present)
• Former Associate Editor, The Canadian Journal of Statistics (2019–2021)

His research groups are Statistics and Biostatistics, and Data Science, Machine Learning, and Artificial Intelligence. He has no listed awards but maintains active editorial and academic collaborations in computational statistics and machine learning.