Ruizhi Zhang is an Assistant Professor in the Department of Statistics at University of Nebraska-Lincoln. He received his B.S. degree in Mathematics from Hua Loo-Keng Talent Program in Mathematics at University of Science and Technology of China (USTC) in 2014, graduated with honors. He received his Ph.D. degree in Statistics in the School of Industrial and Systems Engineering at Georgia Institute of Technology. His research interests include change-point detection, sequential analysis, robust statistics, high-dimensional statistical inference, functional data analysis, etc.
Refereed Journals and Transactions (published or accepted):
1. Zhang, R., Wang, J., Mei, Y., 2017, “Search for evergreens in science: a functional data analysis”, Journal of Informetrics, vol. 11, page 629-644.
2. Zhang, R., Mei, Y., Shi, J., 2018, “Wavelet-based Profile Monitoring Using Order-Thresholding Recursive CUSUM Schemes”, In Y. Zhao and D. G. Chen (ed.) New Frontiers in Biostatistics and Bioinformatics, Cham, Switzerland: Springer, pages 141-159.
3. Zhang, R., Mei, Y, 2018, “Asymptotic Statistical Properties of Communication-Efficient Quickest Detection Schemes in Sensor Networks”, Sequential Analysis, vol. 37, page 375-396.
4. Liu, K., Zhang, R., Mei, Y., 2019, “Scalable SUM-shrinkage schemes for distributed monitoring large-scale data streams”, Statistica Sinica, vol. 29, page 1-22.
Submitted Papers
5. Zhang, R., Mei, Y., Shi, J., 2019, “Robust Real-time Monitoring of High-dimensional Data Streams,” (The conference poster version won the best student poster award in the workshop on Biostatistics and Bioinformatics 2017 and the conference version received the Best Student Paper Award Finalist in Quality, Statistics, and Reliability Section of INFORMS 2018)
6. Zhang, R., Mei, Y., Shi, J., Xu, H., 2019, “Robustness and Tractability for Non-convex M-estimators”.