Yumiaomiao

2017 - 2020, Doctor of Science, School of Statistics and Management, Shanghai University of Finance and Economics, Advised by Prof. Chunjie Wu

2015 - 2017, Master of Science, School of Statistics and Management, Shanghai University of Finance and Economics, Advised by Prof. Chunjie Wu

2011 - 2015, Bachelor of Economics, School of Statistics and Management, Shanghai University of Finance and Economics

2012 - 2015, Bachelor of Management, School of Accounting and Finance, Shanghai University of Finance and Economics

2022 - ,  Assistant Professor, East China Normal University

2020 - 2022, Postdoctor Fellow, East China Normal University, Advisor: Prof. Yong Zhou

2020, Postdoctor Fellow, Hong Kong University of Science and Technology, Advisor: Prof. Fugee Tsung  

2019 - 2020, Research Assistant, Hong Kong University of Science and Technology, Advisor: Prof. Fugee Tsung

2017, Research Assistant, Hong Kong University of Science and Technology, Advisor: Prof. Fugee Tsung

Miaomiao Yu is an assistant professor at Academy of Statistics and Interdisciplinary Sciences, Faculty of Economics and Management, East China Normal University. She was a postdoctoral research fellow of Hong Kong University of Science and Technology and East China Normal University. She is honored with Pujiang Talent, Super Postdoctor, Outstanding Graduate, etc.

Her research interests include statistical methods for big data analysis, data privacy, statistical process control. She has more than 10 papers in top international journals, including Journal of Quality and Technolog, IISE Transactions, Computers &Industrial Engineering, Statistica Sinica and so on.

The Anonymous reviewer of Journal of Quality Technology, IISE Transactions, Journal of Applied Statistics, Journal of Applied Statistics and Management, Journal of Systems Science and  Mathematical Sciences, Chinese Journal of Applied Probability and Statistics, etc.

Big data analysis, Data privacy, Statistical process control

Introduction to Statistics, Autumn 2023

7. State Key Program of National Natural Science Foundation of China, Statistical analysis methods, theories and applications of incomplete data of big data (72331005), 2024.01 - 2028.12.

6. Shanghai Science and Technology Innovation Funds,  General statistical learning theory, algorithm and application of big data in precision medicine (23JS1400501), 2023.12 - 2026.11.

5. Shanghai Pujiang Program,  Research on statistical fusion distributed algorithm and privacy protection of oil and gas pipe network transportation (23PJC040), 2023.11-2026.10.

4. National Natural Science Foundation of China, Online monitoring and its privacy protection of multi-modal networks in the oil and gas pipeline (72301108), 2024.01 - 2026.12.

3. China Postdoctoral Science Foundation, Distributed statistical theory and online monitoring based on differential privacy constraints (2021M691036), 2021.03 - 2022.10.

2. State Key Program of National Natural Science Foundation of China, Statistical theory and method of distributed algorithm and its privacy protection for big data (92046005), 2021.01 - 2021.12.

1. National Key R&D Program of China, Big data analysis theory, algorithm and application of oil and gas pipeline network security operation and maintenance (2021YFA1000100), 2021.12 - 2026.11.

（* corresponding author）

[15] Yu M., Jiang Z., Li J., Zhou Y. (2024). Incorporating auxiliary information for improved statistical inference and its extensions to distributed algorithms with an application to personal credit. The Annals of Applied Statistics, 18(4), 2863-2886.

[14] Yu M., Wang Z., Wu C. (2024). Online detection of the incidence via transfer learning. Naval Research Logistics(NRL), 71(7), 1035-1054. 

[13] Yu M., Zhou Y., Tsung F. (2023). Robust online detection in serially correlated directed network. Naval Research Logistics (NRL), 70(7), 735-752.

[11] Yu M., Zhao W., Zhou Y., Wu C. (2022+). Robust online detection on highly censored data using a semi-parametric EWMA chart. Journal of Statistical Computation and Simulation, 93(9), 1403-1419.

[11] Yu M., Li Z., Zhou Y. (2023). Privacy-preserving parameter estimation  in distributed cases . ACTA Mathematicae Applicatae Sinica, 46(2), 145-165.  (in Chinese)

[10] Wang Z., Wu C., Yu M.*, Tsung F. (2022). Self-starting process monitoring based on transfer learning. Journal of Quality Technology, 54, 589-604.

[9] Yu M., Wu C., Tsung F. (2022). Change detection in parametric multivariate dynamic data streams using the ARMAX-GARCH model. Journal of Quality Technology, 54, 303-323.

[8] Han D., Tsung F., Xian J., Yu M. (2022). Optimal sequential tests for monitoring changes in the distribution of finite observation sequences. Statistica Sinica, 32, 1317-1342. 

[7]  Yu M., Wu C., Tsung F. (2019). Monitoring the data quality of data streams using a two-step control scheme. IISE Transactions, 51, 985-998. 

[6] Yu M., Wu C., Wang Z., Tsung F. (2018). A robust CUSUM scheme with a weighted likelihood ratio to monitor an overdispersed counting process. Computer & Industrial Engineering, 126, 165-175.

[5] Zhuang F., Yu M., Wu C. (2018). Robustness study on EWMA variance control chart with estimated parameters. Journal of Systems Science and  Mathematical Sciences,  38, 101-118. (in Chinese)

[4] Wu C., Yu M., Zhuang F. (2017). Properties and enhancements of robust likelihood CUSUM control chart. Computer & Industrial Engineering, 114, 80-100. 

[3] Wu C., Wei Y., Yu M. (2017). Improved robust-likelihood cumulative sum chart for the contaminated normal distributions. Scientia Sinica Mathematica, 47, 853-868. (in Chinese)

[2] Wu C., Yu M. (2017). Improved design on  nonparametric quantile-based control charts. Journal of Applied Statistics and Management, 36, 103-112. (in Chinese)

[1] Wu C., Yu M. (2017). The robust-likelihood cumulative sum control chart cut off by diagonal when observations followed contaminated normal distribution.  Journal of Systems Science and  Mathematical Sciences, 37. 1138-1155. (in Chinese)

Super postdoctor in Shanghai (2020) 

Outstanding graduate in Shanghai (2020, 2017)

The first place winner of the best presentation award in the 2019 Quality and Data Science Doctoral Forum (2019)

• Academic star of SUFE (2019)

• Second Prize in "Huawei Cup" National Mathematical  Contest in Modeling for Graduate Students (2018)

• • Third Prize in  National Statistical  Contest in Modeling for College Students (2017)

  • Third Prize in Golden Idea Charity Competition (2012)

  
  

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