孔新兵，必威betway西汉姆教授，博士生导师。2007年毕业于兰州大学，获得学士和硕士学位，2011年毕业于香港科技大学，获得博士学位。主要研究方向为高频、高维数据统计、经济金融计量、网络数据统计、机器学习等。在Annas of Statistics、Journal of the American Statistical Association、Journal of Econometrics、Biometrika、Journal of Business and Economic Statistics发表论文20余篇。

主要研究方向为高频、高维数据统计、经济金融计量、机器学习等。在Journal of the American Statistical Association（JASA、Journal of Econometrics、Biometrika、Journal of Business and Economic Statistics等统计学相关领域的核心期刊上发表论文20余篇。

1.第一届统计科学技术进步奖一等奖、2021、第一完成人

2.教育部高校优秀科技成果奖（人文社科）三等奖、2024、论文第一作者

1.  国家自然科学基金重点项目子课题、202501-202912、70万、在研

2. 国家自然科学基金重点专项项目、202401-202712、199万、在研

3. 国家自然科学基金面上项目、202001-202312、50万、已结题

4. 国家自然科学基金面上项目、201601-201912、39万、已结题

5. 国家自然科学基金青年项目、201301-201512、22万、已结题

1. Yong He, Xinbing Kong, Long Yu, Lorenzo Trapani. Online change-point detection for matrix-valued time series with latent two-way factor structure, Annals of Statistics, 2024, Published Online.

2. Yong He, Xinbing Kong, Long Yu, Xinsheng Zhang and Changwei Zhao. Matrix factor anlysis: from least squares to iterative projection, Journal of Business and Economic Statistics, 2024,42,322-334.

3. Xin-Bing Kong, Jin-Guan Lin, Cheng Liu, Guang-Ying Liu. Discrepancy between global and local principal component analysis on large-panel high-frequency data, Journal of the American Statistical Association, 2023, 118,1333-1344.

4. Yong He, Xinbing Kong, Lorenzo Trapani, Long Yu. One-way or two-way factor model for matrix sequences? Journal of Econometrics, 2023, 235,1981-2004.

5. Yong He, Xinbing Kong, Long Yu, Xinsheng Zhang. Large-dimensional factor analysis without moment constraints, Journal of Business and Economic Statistics, 2022, 40, 302-312.

6. Long Yu, Yong He, Xinbing Kong*, Xinsheng Zhang. Projected estimation for large-dimensional matrix factor model, Journal of Econometrics, 2022, 229, 201-217.

7. Xinbing Kong. A random-perturbation-based rank estimator of the number of factors, Biometrika, 2020, 107, 505-511.

8. Xinbing Kong, Jiangyan Wang, Jinbao Xing, Chao Xu and Chao Ying. Factor and idiosyncratic empirical processes,Journal of the American Statistical Association, 2019, 114, 1138-1146.

9. Xin-Bing Kong, Zhi Liu, Wang Zhou. A rank test of the number of factors with high-frequency data, Journal of Econometrics, 2019, 211, 439-460.

10. Xin-Bing Kong and Cheng Liu. Testing against constant factor loading matrix with large panel high-frequency data, Journal of Econometrics, 2018, 204, 301-319.

11. Xin-Bing Kong. On the systematic and idiosyncratic volatility with large panel high-frequency data, Annals of Statistics, 2018, 46, 1077-1108.

12. Zhi Liu, Xin-Bing Kong, Bing-Yi Jing. Estimating the integrated volatility using high-frequency data with zero durations，Journal of Econometrics, 2018，204, 18-32.

13. Donggyu Kim, Xinbing Kong, Cuixia Li, Yazhen Wang. Adaptive thresholding estimator for large volatility matrix estimation based on high-frequency financial data, Journal of Econometrics, 2018, 203, 69-79.

14. Xin-Bing Kong, Shao-Jun Xu, Wang Zhou. Bootstrapping volatility functionals: a local and nonparametric perspective, Biometrika, 2018, 105, 463-469.

15. Xin-Bing Kong. On the number of common factors with high-frequency data, Biometrika, 2017, 104, 397-410.

16. Xin-Bing Kong, Zhi Liu, Bing-Yi Jing. Testing for pure-jump processes for high-frequency data, Annals of Statistics, 2015, 43, 847-877.

17. Bing-Yi Jing, Zhi Liu, Xin-Bing Kong. On the estimation of integrated volatility with jumps and microstructure noise, Journal of Business and Ecoomic Statistics, 2014, 32, 457-467.

18. Bing-Yi Jing, Xin-Bing Kong, Zhi Liu. Modeling high frequency data by pure-jump processes? Annals of Statistics, 2012, 40, 759-784.

19. Bing-Yi Jing, Xin-Bing Kong, Zhi Liu, Per A Mykland. On the jump activity index for semimartingales, Journal of Econometrics, 2012, 166, 213-223.

20. Bing-Yi Jing, Xin-Bing Kong, Zhi Liu. Estimating the jump activity index under noisy observations using high frequency data, Journal of the American Statistical Association, 2011, 106, 558-568.

1.第三届紫丁香应用统计国际会议45分钟大会报告、2021

2.第十二届全国概率统计会议1小时大会报告、2023

3.中国现场统计研究会统计学术前沿研讨会50分钟大会报告、2023