A Journey of Wisdom and Impact: A Conversation with Dr. Xizhi Wu
Volume 23, Issue 4 (2025): Special Issue: In honor of Prof. Xizhi Wu for his transformative contributions to statistics and data science in China, pp. 695–715
Pub. online: 28 October 2025
Type: Data Science Conversation
Open Access
Received
7 October 2025
7 October 2025
Accepted
16 October 2025
16 October 2025
Published
28 October 2025
28 October 2025
Abstract
Over the past three decades, the discipline of statistics has undergone profound transformation, driven by the rapid emergence of data science and artificial intelligence. These developments have reshaped methodological paradigms and introduced new challenges and opportunities for statistical education, particularly in China. In this context, Professor Xizhi Wu from the School of Statistics at Renmin University of China has remained closely engaged with the evolving landscape, demonstrating keen insight and a forward-looking perspective. Through sustained contributions to teaching, research, and educational reform, Professor Wu has deeply influenced generations of students and educators, playing a pivotal role in the advancement of statistical education. To document and reflect on this legacy, the Capital of Statistics conducted an in-depth interview with Professor Wu, focusing on his academic trajectory, professional contributions, and perspectives on the future of the discipline. The conversation also recounts meaningful interactions with his students, offering a multidimensional portrait of a life devoted to statistics.
References
Breiman L (2001). Random forest. Machine Learning, 45: 5–32. https://doi.org/10.1023/A:1010933404324
Tsai CL, Wu X (1990). Diagnostics in transformation and weighted regression. Technometrics, 32(3): 315–322. https://doi.org/10.1080/00401706.1990.10484684
Tukey JW (1962). The future of data analysis. The Annals of Mathematical Statistics, 33(1): 1–67. https://doi.org/10.1214/aoms/1177704711
Wu X, Luo Z (1993). Second-order approach to local influence. Journal of the Royal Statistical Society Series B: Statistical Methodology, 55(4): 929–936. https://doi.org/10.1111/j.2517-6161.1993.tb01951.x