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Jingchen Liu
December 6, 2016
1255 Amsterdam Avenue
Room 1030
New York, NY 10027 USA
(212) 851-2146
[email protected]
http://stat.columbia.edu/~jcliu
Education
Harvard University, Cambridge, Massachusetts USA,
Ph.D., Statistics,
June 2008
Advisor: Xiao-Li Meng and Jose H. Blanchet
Peking University,
Beijing, China,
B.S., Mathematics,
June 2003
Employment
2013 - present
Associate Professor, Department of Statistics, Columbia University,
2008 - 2013
Assistant Professor, Department of Statistics, Columbia University,
Honors, Awards, and Plenary Talks
2014 Plenary talk, International Workshop on Applied Probability, Antalya, Turkey
2013 Tweedie New Researcher Award, Institute of Mathematical Statistics
2013 State of the Art lecturer, International Meeting of the Psychometric Society
2010 Finalist of Junior Faculty Interest Group (JFIG) paper competition, The Institute For Operations Research
and The Management Sciences (6 papers selected out of 39 submissions)
2009 Best Publication in Applied Probability Award, Applied Probability Society, The Institute For Operations
Research and The Management Sciences (awarded every two years alternated with Erlang Prize)
2007 IBM Thomas J. Watson Research Center Student Research Award, The 21st New England Statistics Symposium
2004 American Statistical Association Survey Research Methods Section Travel Awards
Grant Support
2017 - 2020 PI, (co-PI: Z. Ying), National Science Foundataion – Latent and Graphical Models for Complex
Dependent Data in Education.
2015 - 2018 PI, Army Research Office – Rare-event Analysis and Computational Methods for Stochastic Systems
Driven by Random Fields.
2014 - 2014 PI, Army Research Office – Rare-event Analysis and Computational Methods for Stochastic Systems
Driven by Random Fields.
2013 - 2017 PI (co-PI: Z. Ying), National Science Foundation – Statistical Analysis for Cognitive Diagnosis Theory and Applications.
Jingchen Liu, Page 2
2011 - 2014 PI (co-PI: J. Blanchet), National Science Foundation – Efficient Monte Carlo Methods for Gaussian
Random Fields.
2011 - 2012
PI (co-PI: Z. Ying), National Science Foundation – Statistical Analysis for Cognitive Assessment.
2010 - 2013 Co-PI (PI: A. Gelman), Institute of Education Sciences, R305D100017 – Practical Tools for
Multilevel/Hierarchical Modeling in Education.
Publications
Probability, applied probability, operations research, and applied mathematics
1. Xiaoou Li, Jingchen Liu, and Gongjun Xu. On the Tail Probabilities of Aggregated Lognormal Random
Fields with Small Noise. Mathematics of Operations Research, 41(1), 236-246, 2016.
2. Xiaoou Li and Jingchen Liu. Rare-event Simulation and Efficient Discretization for the Supremum of
Gaussian Random Fields. Advances in Applied Probability, 47(3), 787-816, 2015.
3. Jingchen Liu, Jianfeng Lu, and Xiang Zhou. Efficient Rare-event Simulation for Failure Problems in Random
Media. SIAM Journal on Scientific Computing. 37(2), A609-A624, 2015.
4. Gongjun Xu, Guang Lin, and Jingchen Liu. Rare-event Simulation for Stochastic Korteweg-de Vries Equation. SIAM/ASA Journal on Uncertainty Quantification, 2(1), 698-716, 2014.
5. Jingchen Liu and Gongjun Xu. On the Conditional Distributions and the Efficient Simulations of Exponential
Integrals of Gaussian Random Fields. The Annals of Applied Probability, 24(4), 1691-1738, 2014.
6. Jingchen Liu and Gongjun Xu. On the Efficient Simulations for the Exponential Integrals of General Hölder
Continuous Gaussian Random Fields. The ACM Transactions on Modeling and Computer Simulation, 24(2),
1-24, 2014.
7. Jose H. Blanchet and Jingchen Liu. Total Variation Approximations and Conditional Limit Theorems for
Multivariate Regularly Varying Random Walks Conditioned on Ruin. Bernoulli, 20(2), 416-456, 2014.
8. Jingchen Liu and Xiang Zhou. Extreme Analysis of a Random Ordinary Differential Equation. Journal of
Applied Probability, 51(4), 2014.
9. Jingchen Liu and Jae-Kyung Woo. Asymptotic Analysis of Risk Quantities Conditional on Ruin For Multidimensional Heavy-tailed Random Walks. Insurance: Mathematics and Economics, 55, 1-9, 2014.
10. Jingchen Liu and Gongjun Xu. On the Density Functions of Integrals of Gaussian Random Fields. Advances
in Applied Probability, 45(2), 398-424, 2013.
11. Jingchen Liu and Xiang Zhou. On the Failure Probability for One Dimensional Random Material under
delta External Force. Communications in Mathematical Sciences, 11(2), 499 - 521, 2013.
12. Jose H. Blanchet and Jingchen Liu. Efficient Simulation and Conditional Functional Limit Theorems for
Ruinous Heavy-tailed Random Walks. Stochastic Processes and Their Applications, 122(8), 2994-3031,
2012.
13. Robert J. Adler, Jose H. Blanchet, and Jingchen Liu. Efficient Monte Carlo for High Excursions of Gaussian
Random Fields. The Annals of Applied Probability, 22(3), 1167-1214, 2012.
14. Jingchen Liu. Tail Approximations of Integrals of Gaussian Random Fields. The Annals of Probability,
40(3), 1069 - 1104, 2012.
15. Jingchen Liu and Xuan Yang. The Convergence Rate and Asymptotic Distribution of Bootstrap Quantile
Variance Estimator for Importance Sampling. Advances in Applied Probability. 44(3), 815-841, 2012.
16. Jose H. Blanchet and Jingchen Liu. Efficient Importance Sampling in Ruin Problems for Multidimensional
Regularly Varying Random Walks. Journal of Applied Probability, 47(2), 301-322, 2010. (Finalist of Junior
Faculty Interest Group (JFIG) paper competition, INFORMS, 2010)
17. Jose H. Blanchet and Jingchen Liu. State-dependent Importance Sampling for Regularly Varying Random
Walks. Advances in Applied Probability, 40, 1104-1128, 2008.
Jingchen Liu, Page 3
18. Jose H. Blanchet, Peter Glynn, and Jingchen Liu. Fluid Heuristics, Lyapunov Bounds and Efficient Importance Sampling for a Heavy-tailed G/G/1 Queue. Queueing Systems: Theory and Applications, 57, 99 113, 2007. (Best Publication in Applied Probability Award, Applied Probability Society of INFORMS, 2009)
Psychometrics, measurements, and related publications
19. Yunxiao Chen, Xiaoou Li, Jingchen Liu, and Zhiliang Ying. Regularized Latent Class Analysis with Application in Cognitive Diagnosis. Psychometrika. To appear.
20. Jianan Sun, Yunxiao Chen, Jingchen Liu, Zhiliang Ying, and Tao Xin. Latent Variable Selection for Multidimensional Item Response Theory Models via L1 Regularization. Psychometrika. To appear.
21. Jingchen Liu. On the Consistency of Q-matrix Estimation – a Commentary. Psychometrika. To appear.
22. Jingchen Liu, Zhiliang Ying, and Stephanie Zhang. A Rate Function Approach to the Computerized Adaptive
Testing for Cognitive Diagnosis. Psychometrika, 80(2), 468-490, 2015.
23. Yeojin Chung, Andrew Gelman, Sophia Rabe-Hesketh, Jingchen Liu, and Vincent Dorie. Weakly Informative
Prior for Point Estimation of Covariance Matrices in Hierarchical Models. Journal of Educational and
Behavioral Statistics, 40(2), 136-157, 2015.
24. Yunxiao Chen, Jingchen Liu, and Zhiliang Ying. Online Item Calibration for Q-Matrix in CD-CAT. Applied
Psychological Measurement, 39(1), 5-15, 2015.
25. Yeojin Chung, Sophia Rabe-Hesketh, Vincent Dorie, Andrew Gelman, and Jingchen Liu. A Non-degenerate
Estimator for Variance Parameters in Multilevel Models via Penalized Likelihood Estimation. Psychometrika,
78, 685-709, 2013
26. Jingchen Liu, Gongjun Xu, and Zhiliang Ying. Data-driven Learning of Q-matrix. Applied Psychological
Measurement. 36(7), 609-618, 2012.
Statistics and related publications
27. Xiaoou Li, Jingchen Liu, and Zhiliang Ying. Chernoff Index for Cox Test of Separate Parametric Families.
The Annals of Statistics. To appear.
28. Yunxiao Chen, Jingchen Liu, Gongjun Xu, and Zhiliang Ying. Statistical Analysis of Q-matrix Based
Diagnostic Classification Models. Journal of the American Statistical Association, 110(510), 850-866,
2015.
29. Xiaoou Li, Jingchen Liu, and Zhiliang Ying. Generalized Sequential Probability Ratio Test. Sequential
Analysis, 33, 539-563, 2014.
30. Xiaodong Li, Jingchen Liu, Naihua Duan, Ragy Girgis, Huiping Jiang, and Jeffrey Lieberman. Cumulative
Sojourn Time in Longitudinal Studies: A Sequential Imputation Method to Handle Missing Health State
Data Due to Dropout. Statistics in Medicine, 33(12), 2030-2047, 2014.
31. Jingchen Liu, Andrew Gelman, Jennifer Hill, Yu-Sung Su, and Jonathan Kropko. On the Stationary Distribution of the Iterative Imputations. Biometrika, 101(1), 155-173, 2014.
32. Jingchen Liu, Xiao-Li Meng, Margarita Alegria, and Chih-nan Chen. Statistics Can Lie But Can Also Correct
for Lies: Reducing Response Bias in NLAAS via Bayesian Imputation. Statistics and Its Interface, 6(3),
387-398, 2013.
33. Jingchen Liu and Gongjun Xu. Some Asymptotic Results of Gaussian Random Fields with Varying Mean
Functions and the Associated Processes. The Annals of Statistics. 40(1), 262-293, 2012.
34. Jingchen Liu, Gongjun Xu, and Zhiliang Ying. Theory of Self-learning Q-matrix. Bernoulli, 19(5A), 17901817, 2013.
35. Richard A. Davis and Jingchen Liu. Discussion to “A Statistical Analysis of Multiple Temperature Proxies”
by Blackely B. McShane and Abraham J. Wyner. The Annals of Applied Statistics, 5(1), 52-55, 2011.
Publications in Refereed Volumes and Encyclopedia
Jingchen Liu, Page 4
36. Jingchen Liu and Gongjun Xu. Cognitive Diagnosis. The SAGE Encyclopedia of Educational Research,
Measurement, and Evaluation.
Submitted or under revision
37. Jingchen Liu, Gongjun Xu, and Zhiliang Ying. Hypothesis Testing of the Q-matrix. Psychometrika. In
revision
38. Shang Li, Xiaoou Li, Xiaodong Wang, and Jingchen Liu. Decentralized Sequential Composite Hypothesis
Test Based on One-bit Communication. IEEE Transactions on Information Theory. In revision.
39. Yunxiao Chen, Xiaoou Li, Jingchen Liu, Gongjun Xu, and Zhiliang Ying. Exploratory Item Classification via
Spectral Graph Clustering. Applied Psychological Measurement. In revision.
40. Xiaoou Li and Jingchen Liu. A Multilevel Approach towards Unbiased Sampling of Random Elliptic Partial
Differential Equations.
41. Xuan Yang, Richard Davis, and Jingchen Liu. On Central Limit Theorems For Random Fields and Weak
Dependence.
42. Shang Li, Xiaoou Li, Xiaodong Wang, and Jingchen Liu. Sequential Hypothesis Test with Online UsageConstrained Sensor Selection.
43. Xiaoou Li, Yunxiao Chen, Xi Chen, Jingchen Liu, and Zhiliang Ying. Optimal Stopping and Worker Selection
in Crowdsourcing: an Adaptive Sequential Probability Ratio Test Framework.
44. Angela Huyue Zhang, Jingchen Liu, and Nuno Garoupa. Judging in Europe: Does Legal Tradition Matter?
45. Yunxiao Chen, Xiaoou Li, Jingchen Liu, and Zhiliang Ying. A Fused Latent and Graphical Model for
Multivariate Binary Data.
46. Xiaoou Li, Jingchen Liu, Jianfeng Lu, and Xiang Zhou. Moderate Deviation for Random Elliptic PDE with
Small Noise.
47. Yunxiao Chen, Xiaoou Li, Jingchen Liu, Zhiliang Ying. Robust Measurement via A Fused Latent and
Graphical Item Response Theory Model.
48. Yunxiao Chen, Xiaoou Li, Jingchen Liu, Zhiliang Ying. Recommendation System for Adaptive Learning.
Refereed Conference Proceedings
49. Shang Li, Xiaoou Li, Xiaodong Wang, and Jingchen Liu. Optimal Sequential Test with Finite Horizon and
Constrained Sensor Selection. Proceeding of IEEE International Symposium on Information Theory (ISIT),
2016.
50. Shang Li, Xiaoou Li, Xiaodong Wang, and Jingchen Liu. Multi-Sensor Generalized Sequential Probability Ratio Test Using Level-Triggered Sampling. Proceeding of 3rd IEEE Global Conference on Signal &
Information Processing, 2015.
51. Jingchen Liu and Gongjun Xu. Rare-event Simulation for Exponential Integrals of Smooth Gaussian Processes. Proceedings of the 2012 Winter Simulation Conference, 2012.
52. Jingchen Liu, Xiang Zhou, Rohit Patra, and Weinan E. Failure of Random Materials: A Large Deviation
and Computational Study. Proceedings of the 2011 Winter Simulation Conference, 2011.
53. Jose H. Blanchet, Jingchen Liu, and Xuan Yang. Monte Carlo for Large Credit Portfolios with Potentially
High Correlations. Proceedings of the 2010 Winter Simulation Conference, 2810-2820, 2010.
54. Robert J. Adler, Jose H. Blanchet, and Jingchen Liu. Efficient Simulation for Tail Probabilities of Gaussian
Random Fields. Proceedings of the 2008 Winter Simulation Conference, 328-336, 2008.
55. Jose H. Blanchet, Jingchen Liu, and Bert Zwart. Large Deviations Perspective on Ordinal Optimization of
Heavy-tailed Systems. Proceedings of the 2008 Winter Simulation Conference, 489-494, 2008.
56. Jose H. Blanchet and Jingchen Liu. Rare-event Simulation for A Multidimensional Random Walk with t
Distribution Increments. Proceedings of the 2007 Winter Simulation Conference, 395-402, 2007.
57. Jose H. Blanchet and Jingchen Liu. Path-sampling for State-dependent Importance Sampling. Proceedings
of the 2007 Winter Simulation Conference, 380-388, 2007.
Jingchen Liu, Page 5
58. Jose H. Blanchet and Jingchen Liu. Efficient Simulation for Large Deviation Probabilities of Sums of Heavytailed Increments. Proceedings of the 2006 Winter Simulation Conference, 757 - 764, Monterey, California,
2006.
59. Jose H. Blanchet, Jingchen Liu and Peter W. Glynn. State-dependent Importance Sampling and Large
Deviations. Proceedings of the 1st International Conference on Performance Evaluation Methodologies and
Tools, Article No. 20, Pisa, Italy, 2006.
Other Publications
60. Jingchen Liu and Zhiliang Ying. Special Issue: Editorial. Applied Psychological Measurement, 2015.
61. Jingchen Liu. Effective Modeling and Scientific Computation with Applications to Health Study, Astronomy,
and Queueing Network. Harvard University Doctoral Dissertation, 2008.
62. Jingchen Liu, Xiao-Li Meng, Margarita Alegria and Chen, Chih-nan. Multiple Imputation for Response
Biases in NLAAS Due to Survey Instruments. ASA Proceedings of the Joint Statistical Meetings, 3360 3366, American Statistical Association, (Alexandria, VA), 2006.
63. Xiao-Li Meng, Margarita Alegria, Chih-nan Chen and Jingchen Liu. A nonlinear hierarchical model for
estimating prevalence rates with small samples. ASA Proceedings of the Joint Statistical Meetings, 110120, American Statistical Association (Alexandria, VA), 2005.
Technical Reports
64. Henrik Hult, Jingchen Liu, and Xuan Yang. Self-learning Markov Chain Monte Carlo From a Large Deviations
Point of View.
65. Jingchen Liu, Jianfeng Lu, and Xiang Zhou. On the Large Deviations Principle of Random Partial Elliptic
Differential Equations.
66. Jose H. Blanchet, Peter W. Glynn and Jingchen Liu. Efficient Rare-Event Simulation for Heavy-tailed
Multiserver Queues.
67. Jingchen Liu. Latent variable selection via Overlap Group LASSO.
68. Hyeon-Ah Kang, Jingchen Liu, and Zhiliang Ying. Graphical Diagnostic Classification Model.
69. Guanhua Fang, Jingchen Liu, and Zhiliang Ying. On the Identifiability of Diagnostic Classification Models.
Services
Editorial services
Associate editor, Journal of Applied Probability/Advances in Applied Probability,
2016 - present
Associate editor, Psychometrika,
2015 - present
Guest editor, special issue at Applied Psychological Measurements,
2015
Associate editor, Extremes
2015 - present
Associate editor, Statistica Sinica
2014 - present
Associate editor, British Journal of Mathematical and Statistical Psychology
2013 - present
Associate editor, STAT
2012 - present
Associate editor, Operations Research Letters
2010 - present
Advisory editor, Journal of Educational Measurement
Refereed for
2013 - 2016
Jingchen Liu, Page 6
Journal of the American Statistical Association, The Annals of Applied Statistics, Bernoulli, Statistica Sinica,
Mathematics of Operations Research, Management Science, ACM: Transactions on Modeling and Computer
Simulation, Queueing Systems - Theory and Applications, Journal of Official Statistics, Journal of Educational
and Behavioral Statistics, Computational Statistics and Data Analysis, Journal of Applied Probability, Biometrics,
Biometrika, Psychometrika, Journal of Educational Measurement, Stochastic Models, Finance and Stochastics,
Operations Research.
Ph.D. students (co-)advising
Guanhua Fang, Department of Statistics, Columbia University,
current
Hok Kan Ling, Department of Statistics, Columbia University,
current
Yunxiao Chen, Department of Statistics, Columbia University,
May 2016
Current position: assistant professor, Emory University
Xiaoou Li, Department of Statistics, Columbia University,
May 2016
Current position: assistant professor, University of Minnesota Twin Cities
Xuan Yang, Department of Statistics, Columbia University,
May, 2014
Current position: Morgan Stanley
Stephanie Zhang, Department of Statistics, Columbia University,
May, 2014
Current position: Google
Gongjun Xu, Department of Statistics, Columbia University,
May, 2013
Current position: assistant professor, University of Michigan, Ann Arbor
Postdoctoral Fellow
Hyeon-Ah Kang, Department of Statistics, Columbia University,
2016 - 2017
Doctoral dissertation committees
Meng-ta Chung, Teachers College, Columbia University,
2014
Shuheng Zheng, Department of Industrial Engineering and Operations Research,
2013
Chen-Miao Chen, Teachers College, Columbia University,
2013
Heng Liu, Department of Statistics, Columbia University,
2012
Yixi Shi, Department of Industrial Engineering and Operations Research, Columbia University,
2012
Chun Yip Yau, Department of Statistics, Columbia University,
2010
Conference and seminar organizers
Organizer, The Fourth Conference on the Statistical Methods in Psychometrics, Columbia University,
2016
Organizer, International Conference on Applied Probability and Computational Methods in Applied Sciences,
Jingchen Liu, Page 7
Shanghai Center for Mathematical Sciences,
2015
Organizer, Workshop on Statistical Methods in Diagnostic Assessments,
Shanghai Center for Mathematical Sciences,
2014
Organizer, Workshop on Statistical Methods in Diagnostic Assessments, Columbia University,
2012 and 2013
Organizer, The Second Workshop on Computational Methods in Applied Sciences, Columbia University,
2012
Organizer, Workshop on Performance Analysis of Monte Carlo Methods, ICERM, Brown University,
2012
Organizer, Workshop on Computational Methods in Applied Sciences, Columbia University,
2011
Session organizer, Winter Simulation Conference,
2011
Session organizer, Joint Statistical Meeting,
Chair, Statistics Seminar Series, Columbia University,
2010, 2011, 2012
Fall 2008, Spring & Fall 2010
Organizing committee member, Workshop on Analysis of Monte Carlo Methods, Harvard University,
Treasurer, Harvard Chinese Students and Scholars Association
2007
2004 - 2006
Teaching Experience
Columbia University, New York, New York
Stat W 4201: Advanced Data Analysis
Fall 2008 - 2012, Spring 2014 - 2016
Stat W 4315: Linear Regression Models
Fall 2014
Stat W 1211: Introduction to Statistics
Spring 2012
Stat G 8325: Topics in Advanced Statistics
Stat G 6102: Statistical Modelling and Data Analysis II
Fall 2010, Spring 2012
Spring 2009 - 2011
Teaching Fellow, Harvard University, Cambridge, Massachusetts
Stat 212: Probability and Mathematical Statistics III: Special Topics
Stat 170/270: Introduction to Quantitative Methods in Finance
Stat 210: Probability Theory and Mathematical Statistics
Stat 100: Introduction to Quantitative Methods
Stat 171: Introduction to Stochastic Processes
Stat 139: Statistical Sleuthing Through Linear Models (twice)
Seminar Talks
Fall 2007
Spring 2007
Fall 2006
Summer 2006
Spring 2006
Spring and Fall 2005
Jingchen Liu, Page 8
Northwestern University, Department of Industrial Engineering and Management Sciences
Harvard University, Department of Statistics
City University of Hong Kong, Department of Mathematics
Tsinghua University, Center for Statistical Science
Peking University, Department of Statistics
Bejing Normal University, Department of Statistics
IBM T.J. Watson Lab
University of Toronto, Department of Statistics
City University of New York, Department of Mathematics
October 2016
September 2016
August 2016
November 2015
July 2015
March 2015
February 2015
March 2014
September 2008, February 2014
Fudan University, Department of Statistics, China,
November 2013
USTC, Department of Statistics, China,
November 2013
Rutgers University, Department of Statistics
Chinese Academy of Sciences,
Duke University, Department of Mathematics,
April 2011, September 2013
July 2011, Jan 2013.
April 2013
University of Virginia, Department of Statistics,
Nov 2012
Michigan State University, Department of Statistics and Probability,
Oct 2012
University of Minnesota, Industrial and Systems Engineering,
May 2012
New York University, Courant Institute,
April 2012
Columbia University, New York State Psychiatric Institute
Nov 2008, Feb 2012
Chinese University of Hong Kong, Department of Statistics
July 2011
U.C. Berkeley, Department of Statistics
Mar 2011
Brown University, Division of Applied Mathematics
Feb 2011
Boston University, Department of Mathematics
Feb 2011
Columbia University, Department of Electrical Engineering
Mar 2010
City University of New York, Department of Statistics
Oct 2008
Columbia University, Department of Statistics
Sep 2008