PhD candidate Nankai University China
Shaohua Xu is a Ph.D. candidate in Statistics at Nankai University, China. With a strong foundation in statistical methodologies and robust experimental designs, he excels in advancing subsampling techniques and online control experiments. His work reflects a dedication to innovative solutions for complex statistical challenges.
Profile
Scopus
Education 🎓
- Ph.D. in Statistics (2019–2025*, Advisor: Prof. Yongdao Zhou)
- Nankai University, Tianjin, China
- B.S. in Statistics (2015–2019, Advisor: Assoc. Prof. Benchong Li)
- Xidian University, Xi’an, China
Experience 🛠️
Shaohua Xu has presented at prestigious national and international statistical conferences and collaborated with experts to address real-world challenges in statistical design and data analysis. He also contributes through teaching assistance and mentoring at Nankai University.
Research Interests 🔍
- Robust Regression Design
- Online Control Experiments
- Subsampling Techniques for Large-Scale Data
Awards & Honors 🏆
- 2024: Poster Award, International Chinese Statistical Association China Conference
- 2023: Best Paper Award, 2nd International Workshop on Statistical Theory and Related Fields
- 2023: Zhong Jiaqing Outstanding Paper Award, 24th Beijing-Tianjin-Hebei Young Scholars Symposium
- 2023: Second Prize, Academic Symposium on Uniform Design, Chinese Mathematical Society
- 2020 & 2022: Gongneng Scholarship, Nankai University
- 2018: National Scholarship & SAS China Analytics Championship Top 40
Publications Top Notes:📚
Xu, Shaohua, Liu, S., & Zhou, Y. (2024). MODE: Minimax Optimal Deterministic Experiments for Causal Inference in the Presence of Covariates. Entropy, 26(12), 1023. Link
Xu, Shaohua & Zhou, Y. (2024). Robust control experiments for multivariate tests with covariates and network information. Under review in Statistica Sinica.
Xu, Shaohua & Zhou, Y. (2024). Minimax designs for partially linear models. Under review in Journal of Statistical Planning and Inference.
Yang, J., Xu, Shaohua, Yang, Z., Zhang, A., & Zhou, Y. (2024). Stable subsampling under model misspecification and dataset shift. Under review in ACM Transactions on Knowledge Discovery from Data.
Xu, Shaohua, Zhou, Y., & Zhou, Z. (2024). Minimax designs for misspecified linear models. Submitted to Annals of Statistics.