尹建鑫

orien ation tation

北京大學數學科學學院博士,美國賓夕法尼亞大學博士後,現任中國人民大學統計學院副教授,主要研究興趣為圖模型、高維數據分析及統計推斷、變數選擇與罰函式方法、非參數統計、機器學習。

教育經歷

2004--2009, 北京大學數學科學學院,機率統計系,機率論與數理統計專業,理學博士;
1999--2003,北京大學力學與工程科學系,理論與套用力學專業,理學學士。
2009--2011,美國賓夕法尼亞大學(University of Pennsylvania),佩雷爾曼醫學院,生物統計系,博士後研究員;

主講課程:

機率論(本科生)、數理統計(本科生)、高等統計學(研究生)。

工作及科研經歷

2012--今,中國人民大學統計學院,副教授;
2011--2012,中國人民大學統計學院,講師;
2004--2009,北京大學數學科學學院,機率統計系,助研(助教);
2002--2003,北京大學理論生物學中心、湍流與複雜系統國家重點實驗室,本科生研究員。

研究領域

高維數據分析及統計推斷
變數選擇與罰函式方法
非參數統計

學術成果

論文與研究報告

S. He, J. Yin, H. Li and X. Wang (2012).Graphical Model Selection and Estimation for High Dimensional Tensor Data,submitted.
J. Yin and H. Li (2012).Adjusting for High-dimensional Covariates in Sparse Precision Matrix Estimation by L1-Penalization, submitted.
X. Li and J. Yin (2012). Sparse Sufficient Dimension Reduction for Markov Blanket Discovery, Communications in Statistics-Simulation and Computation, minor revision.
J. Yin and H. Li (2012). Model Selection and Estimation in Matrix Normal Graphical Model, Journal of Multivariate Analysis, 107, 119-140.
J. Yin and H. Li (2011). A Sparse Conditional Gaussian Graphical Model for Analysis of Genetical Genomics Data, Annals of Applied Statistics, Vol. 5, No. 4, 2630-2650.
J. Yin, Z. Geng, R. Li and H. Wang(2010).Nonparametric Covariance Model, Statistica Sinica, 20, 469-479.
J.Yin, Y. Zhou, C. Wang,P. He, C. Zheng and Z. Geng(2008). Partial orientation and local structure learning of causal networks for prediction, Journal of Machine Learning Research: Workshop and Conference Proceedings 3: 93-105. (prize-winning paper)
Y. Zhou, C. Wang, J. Yin and Z. Geng(2010). Discover Local Causal Network around a Target to a Given Depth, Journal of Machine Learning Research: Workshop and Conference Proceedings 6: 191-202.
佘振蘇,楊鑄,歐陽正清, 朱懷球,王超,尹建鑫(2003). SARS冠狀病毒的起源和進化初探,北京大學學報(自然科學版), Vol. 39, No. 6: 809-814.

主持的科研項目

高維數據的圖模型學習與統計推斷(No.11201479),國家自然科學基金青年科學基金項目,2013-2015.

學術交流與兼職

國際生物統計學會中國分會(IBS-China), 副秘書長 。
國際數理統計學會(IMS), 成員。
Presentation: Sparse matrix normal graphical model and its extension to tensor data. International Symposium on Statistics & Management Science (ISSMS 2012), July 2012, Huangshan, Anhui Proviance.
Presentation: Penalized estimation and selection for precision matrix and Graphical models. Mini-workshop on statistical machine learning and biosciences in 2012, May 2012, Beijing.
Presentation: Model selection and estimation in Matrix Normal Graphical Model. Joint Statistical Meetings, August 2011,Miami Beach, Florida.
Presentation: Genetic Network Learning in Genetical Genomics Experiments, East North American Region Spring Meeting(ENAR 2010), March 2010, New Orleans, L.A., U.S.
The "Significant Advance on the SIDO dataset for the LOCANET task" Award, 2008 NIPS Causality competition Workbench Team. December 12, 2008, Whistler, Canada.
The "Best Overall Contribution" Award, IEEE World Congress on Computational Intelligence(WCCI) 2008. (http://www.causality.inf.ethz.ch/challenge.php)
Presentation: Partial Orientation and Local Structure Learning of DAGs for Prediction. IEEE WCCI 2008, June 2008, Hong Kong, China.
Presentation: Nonparametric Covariance Model. The first IMS-China Conference on Statistics and Probability, June 2008, Hangzhou, China.

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