Jingchen Liu - Department of Statistics - Columbia University

Jingchen Liu June 9, 2017 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 Foundation – 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 – 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 H¨ older 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) Statistics 19. Xiaoou Li, Jingchen Liu, and Zhiliang Ying. Chernoff Index for Cox Test of Separate Parametric Families. The Annals of Statistics. To appear. 20. 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. 21. Xiaoou Li, Jingchen Liu, and Zhiliang Ying. Generalized Sequential Probability Ratio Test. Sequential Analysis, 33, 539-563, 2014. 22. 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. 23. 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. 24. 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. 25. 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. 26. Jingchen Liu, Gongjun Xu, and Zhiliang Ying. Theory of Self-learning Q-matrix. Bernoulli, 19(5A), 17901817, 2013. 27. 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. Psychometrics, measurements, and related publications 28. Yunxiao Chen, Xiaoou Li, Jingchen Liu, and Zhiliang Ying. Recommendation System for Adaptive Learning. Applied Psychological Measurements. To appear. 29. Yunxiao Chen, Xiaoou Li, Jingchen Liu, Gongjun Xu, and Zhiliang Ying. Exploratory Item Classification via Spectral Graph Clustering. Applied Psychological Measurement. To appear. 30. Yunxiao Chen, Xiaoou Li, Jingchen Liu, and Zhiliang Ying. Regularized Latent Class Analysis with Application in Cognitive Diagnosis. Psychometrika. To appear. 31. Jingchen Liu. On the Consistency of Q-matrix Estimation – a Commentary. Psychometrika. To appear. 32. Jianan Sun, Yunxiao Chen, Jingchen Liu, Zhiliang Ying, and Tao Xin. Latent Variable Selection for Multidimensional Item Response Theory Models via L1 Regularization. Psychometrika, 81(4), 921-939, 2016. 33. 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. 34. 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. 35. Yunxiao Chen, Jingchen Liu, and Zhiliang Ying. Online Item Calibration for Q-Matrix in CD-CAT. Applied Psychological Measurement, 39(1), 5-15, 2015. 36. 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

Jingchen Liu, Page 4 37. Jingchen Liu, Gongjun Xu, and Zhiliang Ying. Data-driven Learning of Q-matrix. Applied Psychological Measurement, 36(7), 609-618, 2012. Other journal publications 38. Margarita Alegria, Robert E. Drake, Hyeon-Ah Kang, Justin Metcalfe, Jingchen Liu, Karissa DiMarzio, and Naomi Ali. Simulations Test Impact of Education, Employment, And Income Improvements On Minority Patients With Mental Illness. Health Affairs, 36(6), 1024-1031, 2017. 39. Shang Li, Xiaoou Li, Xiaodong Wang, and Jingchen Liu. Decentralized Sequential Composite Hypothesis Test Based on One-bit Communication. IEEE Transactions on Information Theory, 63(6), 3405 - 3424, 2017. Publications in Book Chapters, Refereed Volumes, and Encyclopedia 40. Jingchen Liu and Gongjun Xu. Cognitive Diagnosis. The SAGE Encyclopedia of Educational Research, Measurement, and Evaluation. Submitted or under revision 41. Jingchen Liu, Gongjun Xu, and Zhiliang Ying. Hypothesis Testing of the Q-matrix. Psychometrika. In revision 42. Yunxiao Chen, Xiaoou Li, Jingchen Liu, and Zhiliang Ying. A Fused Latent and Graphical Model for Multivariate Binary Data. Journal of the American Statistical Association. In revision. 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. Journal of the American Statistical Association. In revision. 44. Xiaoou Li and Jingchen Liu. A Multilevel Approach towards Unbiased Sampling of Random Elliptic Partial Differential Equations. Journal of Applied Probability. In revision. 45. Shang Li, Xiaoou Li, Xiaodong Wang, and Jingchen Liu. Sequential Hypothesis Test with Online UsageConstrained Sensor Selection. IEEE Transactions on Information Theory. In revision. 46. Angela Huyue Zhang, Jingchen Liu, and Nuno Garoupa. Judging in Europe: Does Legal Tradition Matter? 47. Xiaoou Li, Jingchen Liu, Jianfeng Lu, and Xiang Zhou. Moderate Deviation for Random Elliptic PDE with Small Noise. 48. Yunxiao Chen, Xiaoou Li, Jingchen Liu, Zhiliang Ying. Robust Measurement via A Fused Latent and Graphical Item Response Theory Model. 49. Guanhua Fang, Jingchen Liu, and Zhiliang Ying. On the Identifiability of Diagnostic Classification Models. 50. Haochen Xu, Guanhua Fang, Yunxiao Chen, Jingchen Liu, and Zhiliang Ying. Latent Class Analysis of Recurrent Events in Problem-Solving Items 51. Xiaoou Li, Jingchen Liu, Jianfeng Lu, and Xiang Zhou. Rare-event Simulation for Random Elliptic PDES with Small Noise. Refereed Conference Proceedings 52. 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. 53. 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. 54. Jingchen Liu and Gongjun Xu. Rare-event Simulation for Exponential Integrals of Smooth Gaussian Processes. Proceedings of the 2012 Winter Simulation Conference, 2012. 55. 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.

Jingchen Liu, Page 5 56. 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. 57. 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. 58. 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. 59. 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. 60. Jose H. Blanchet and Jingchen Liu. Path-sampling for State-dependent Importance Sampling. Proceedings of the 2007 Winter Simulation Conference, 380-388, 2007. 61. 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. 62. 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 63. Jingchen Liu and Zhiliang Ying. Special Issue: Editorial. Applied Psychological Measurement, 2015. 64. Jingchen Liu. Effective Modeling and Scientific Computation with Applications to Health Study, Astronomy, and Queueing Network. Harvard University Doctoral Dissertation, 2008. 65. 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. 66. 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 67. Henrik Hult, Jingchen Liu, and Xuan Yang. Self-learning Markov Chain Monte Carlo From a Large Deviations Point of View. 68. Jingchen Liu, Jianfeng Lu, and Xiang Zhou. On the Large Deviations Principle of Random Partial Elliptic Differential Equations. 69. Jose H. Blanchet, Peter W. Glynn and Jingchen Liu. Efficient Rare-Event Simulation for Heavy-tailed Multiserver Queues. 70. Guanhua Fang, Jingchen Liu, and Zhiliang Ying. Latent Variable Selection via Overlap Group LASSO. 71. Hyeon-Ah Kang, Jingchen Liu, and Zhiliang Ying. Graphical Diagnostic Classification Model. 72. Hok Kan Ling, Jingchen Liu, and Angela Huyue Zhang. A Graphical Mixed Model for Judging in European Courts. 73. Hyeon-Ah Kang, Siliang Zhang, Yunxiao Chen, Jingchen Liu, and Zhiliang Ying. Multidimensional Latent Trait Models via Low-rank Second Order Exponential Family. 74. Xuan Yang, Richard Davis, and Jingchen Liu. On Central Limit Theorems For Random Fields and Weak Dependence.

Jingchen Liu, Page 6

Services Editorial services Associate editor, Journal of Applied Probability/Advances in Applied Probability,

2016 - present

Associate editor, Psychometrika,

2015 - present

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 Guest editor, special issue at Applied Psychological Measurements,

2013 - 2016 2015

Refereed for 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

First position: Wells Fargo Stephanie Zhang, Department of Statistics, Columbia University,

May, 2014

First position: Google Gongjun Xu, Department of Statistics, Columbia University, Current position: assistant professor, University of Michigan, Ann Arbor

May, 2013

Jingchen Liu, Page 7 Postdoctoral Fellow Xueying Tang, Department of Statistics, Columbia University,

current

Hyeon-Ah Kang, Department of Statistics, Columbia University,

2016 - 2017

Current position: assistant professor, University of Texas, Austin Doctoral dissertation committees Shang Li, Department of Electrical Engineering, Columbia University,

2017

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, 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

Teaching Experience Columbia University, New York, New York

2007 2004 - 2006

Jingchen Liu, Page 8 Stat W 4201: Advanced Data Analysis

Fall 2008 - 2012, Spring 2014 - 2016

Stat W 4315: Linear Regression Models

Fall 2014, 2017

Stat W 1211: Introduction to Statistics

Spring 2012

Stat G 8325: Topics in Advanced Statistics

Fall 2010, Spring 2012

Stat G 6102: Statistical Modelling and Data Analysis II

Spring 2009 - 2011

Teaching Fellow, Harvard University, Cambridge, Massachusetts Stat 212: Probability and Mathematical Statistics III: Special Topics

Fall 2007

Stat 170/270: Introduction to Quantitative Methods in Finance

Spring 2007

Stat 210: Probability Theory and Mathematical Statistics

Fall 2006

Stat 100: Introduction to Quantitative Methods

Summer 2006

Stat 171: Introduction to Stochastic Processes

Spring 2006

Stat 139: Statistical Sleuthing Through Linear Models (twice)

Spring and Fall 2005

Seminar Talks/short courses Tsinghua Universiy, Center for Statistical Science, short course on latent variable models

July 2017

University of California at Davis, Department of Statistics

April 2017

Google

April 2017

Stanford University, Management Science & Engineering

April 2017

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 Fudan University, Department of Statistics, China,

October 2016 September 2016 August 2016 November 2015 July 2015 March 2015 February 2015 March 2014

September 2008, February 2014 November 2013

Jingchen Liu, Page 9 USTC, Department of Statistics, China, Rutgers University, Department of Statistics Chinese Academy of Sciences, Duke University, Department of Mathematics, University of Virginia, Department of Statistics, Michigan State University, Department of Statistics and Probability,

November 2013 April 2011, September 2013 July 2011, January 2013 April 2013 November 2012 October 2012

University of Minnesota, Industrial and Systems Engineering,

May 2012

New York University, Courant Institute,

April 2012

Columbia University, New York State Psychiatric Institute Chinese University of Hong Kong, Department of Statistics U.C. Berkeley, Department of Statistics

November 2008, February 2012 July 2011 March 2011

Brown University, Division of Applied Mathematics

February 2011

Boston University, Department of Mathematics

February 2011

Columbia University, Department of Electrical Engineering City University of New York, Department of Statistics Columbia University, Department of Statistics

March 2010 October 2008 September 2008