DR. YUEXIAO DONG. Department of Statistics Fox School of Business Temple University 1810 N. 13th Street Philadelphia, PA 19122

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1 Department of Statistics Fox School of Business Temple University 1810 N. 13th Street Philadelphia, PA Phone: (1-) ydong/index.html Employment Assistant Professor (Tenure Track) in Department of Statistics, Fox School of Business, Temple University, July Present. Education Grants Ph.D. in Statistics ( ), Pennsylvania State University. Ph.D Dissertation: Dimension Reduction for Non-Elliptically Distributed Predictors. B.S. in Mathematics ( ), Tsinghua University, Beijing, P. R. China. National Science Foundation (NSF) New Developments in Sufficient Dimension Reduction. DMS Sole Investigator: September 2011-August ($100,000) Status: Awarded. Institute for Business and Information Technology (IBIT) Big Data Grant Towards Understanding the Dimension Reduction Methodologies and Organizational Capabilities Required for Competing in the Big Data Era. Lead Investigator: Yuexiao Dong. ($2500) Status: Awarded. Young Researcher Scholars Seed Fund Further Investigation into Customer Focus and its Consequences in a Business Marketing Context. Principal Investigator: Neeraj Bharadwaj. ($500) Status: Awarded. Open Evaluation for Open Innovation: Collective Intelligence Aggregated with Prediction Market. Principal Investigator: Pei-Yu Chen. ($500) Status: Awarded. Papers & Manuscripts Refereed Journal Publications 1. Yu, Z., Dong, Y., and Huang, M. (2014) General Directional Regression. Journal of Multivariate Analysis, 124, Dong, Y., and Zhu, L. P. (2013) Direction Estimation in Single-Index Model with Missing Values. Statistics and Its Interface, 6, Dong, Y., Yu, Z., and Sun, Y. (2013) A Note on Robust Kernel Inverse Regression. Statistics and Its Interface, 6, Zhu, L. P., Dong, Y., and Li, R. (2013) Semi-Parametric Estimation of Conditional Heteroscedasticity via Single-Index Modeling. Statistica Sinica, 23, Yu, Z., Dong, Y., and Guo, R. (2013) On Determining the Structural Dimension via Directional Regression. Statistics and Probability Letters, 83, Dong, Y., and Yu, Z. (2012) Dimension Reduction for the Conditional K-th Moment via Central Solution Space. Journal of Multivariate Analysis, 112, Dong, Y., and Zhu, L. P. (2012) A Note on Sliced Inverse Regression with Missing Predictors. Statistical Analysis and Data Mining, 5, Dong, Y., and Li, B. (2010) Dimension Reduction for Non-Elliptically Distributed Predictors: Second-Order Methods. Biometrika, 97,

2 9. Dong, Y., and Zhu, L. P. (2010) Discussion of Envelope Models for Parsimonious and Efficient Multivariate Linear Regression. Statistica Sinica, 20, Yu, Z., Dong, Y., and Fang, Y. (2010) Marginal Coordinate Tests for Central Mean Subspace with Principal Hessian Directions. Chinese Journal of Applied Probability and Statistics, 26, Li, B., and Dong, Y. (2009) Dimension Reduction for Non-Elliptically Distributed Predictors. Annals of Statistics, 37, Inter-Disciplinary Research 12. Bharadwaj, N., and Dong, Y. (2014) Toward Further Understanding the Marketsensing CapabilityValue Creation Relationship. Journal of Product Innovation Management, 31, Manuscripts In Preparation 13. Dong, Y., Yu, Z., and Zhu, L. P. Robust Inverse Regression for Dimension Reduction. 14. Dong, Y., Yu, Z., and Zhu, L. P. Model-Free Variable Selection for Conditional Mean in Regression. 15. Yu, Z., Dong, Y., and Zhu, L. X. Trace Pursuit: A General Framework for Model-free Variable Selection. 16. Artemiou, A., and Dong, Y. Sufficient Dimension Reduction via Principal Lq Support Vector Machine. 17. Bharadwaj, N., Dong, Y., and Naik, P. Sparse Constrained Inverse Regression for Big Data Analytics. 18. Dong, Y. A Note on Moment-Based Sufficient Dimension Reduction Estimators. 19. Yu, Z., and Dong, Y. Model-free Coordinate Test and Variable Selection via Directional Regression. 20. Dong, Y., Yu, Z., and Kai, B. Dimension Reduction via Local Rank Regression. 21. Kai, B., Huang, M., Yao, W., and Dong, Y. Local Linear Quantile Regression via a Global MM Algorithm. Non-Refereed Proceeding Publications Dong, Y. and Yu, Z. (2010) Estimating the Central Kth Moment Space via an Extension of Ordinary Least Squares JSM Proceedings. Li, B., and Dong, Y. (2009) Central solution space for dimension reduction JSM Proceedings. Monograph Sufficient Dimension Reduction for the Conditional K-th Moment: A New Approach through Central Solution Space. Dong, Y. (2009) VDM Verlag. ISBN-13: Conference Presentations At Professional Conferences and Meetings & Presentations via Principal Lq Support Vector August, Joint Statistical Meetings, Boston, MA. Sufficient Dimension Reduction Machine. June, Joint Applied Statistics Symposium of International Chinese Statistical Association and Korean International Statistical Society, Portland, Oregon. Sufficient Dimension Reduction via Principal Lq Support Vector Machine. June, International Symposium on Business and Industrial Statistics/Conference of ASA Section on Statistical Learning and Data Mining, Durham, NC. Model-free Variable Selection.

3 December, The 9th ICSA International Conference: Challenges of Statistical Methods for Interdisciplinary Research and Big Data, Hong Kong. Trace Pursuit: A General Framework for Model-free Variable Selection. July, IMS China, Chengdu, China. General Directional Regression. February, Winter Marketing Educators Conference, Las Vegas, Nevada. Structured Dimension Reduction for Marketing with Big Data. August, Joint Statistical Meetings, San Diego, California. Sufficient Dimension Reduction in Data-Rich Marketing Research. May, Big Data Symposium, Institute for Business & Information Technology (IBIT) at the Fox School, Temple University. In Search of What Counts in Big Datasets. December, Workshop on Information Systems Economics (WISE), Shanghai, P. R. China. Open Evaluation for Open Innovation: Collective Intelligence Aggregated by Prediction Market Mechanism. Presented by Yang Yang, a Ph.D. student from Management Information Systems. November, INFORMS Annual Meeting, Charlotte, North Carolina. Robustified Inverse Regression. August, Joint Statistical Meetings, Miami, Florida. Applying new developments in dimension reduction techniques in statistics to data-rich marketing research. July, IMS-China International Conference on Statistics and Probability, Xi an, P. R. China. Robustified inverse regression. June, ICSA 2011 Applied Statistics Symposium, New York City. A note on sliced inverse regression with missing predictors. December, International Workshop on Emerging Issues and Challenges to Statistics, Xiamen, P. R. China. An iterative algorithm for dimension reduction with nonelliptically distributed predictors. August, Joint Statistical Meetings, Vancouver, Canada. An iterative algorithm for dimension reduction. July, The Thirteenth Meeting of New Researchers in Statistics and Probability, Vancouver, Canada. An iterative algorithm for dimension reduction. May, Conference on Nonparametric Statistics and Statistical Learning, Ohio State University, Columbus. Dimension reduction for the conditional K-th moment via central solution space. March, Eastern North American Region/International Biometric Society Meeting, New Orleans. Dimension reduction for the conditional K-th moment via central solution space. August, Joint Statistical Meetings, Washington D.C. Central solution space for dimension reduction. March, Eastern North American Region/International Biometric Society Meeting, San Antonio. Central solution space for dimension reduction. Presentations At Departmental Colloquia February, Department of Statistics, Kansas State University, KS. Model-free Variable Selection. April, Department of Statistics, University of Illinois at Urbana-Champaign, IL. General Directional Regression. October, Department of Mathematics and Statistics, University of Maryland Baltimore County, Baltimore, MD. Directional Regression Revisited.

4 Teaching Experience October, Division of Biostatistics, Thomas Jefferson University, Philadelphia, PA. A Review of Sliced Inverse Regression and Its Variations. September, Department of Management Science, University of Miami, Coral Gables, FL. Directional Regression Revisited. April, Department of Statistics, George Mason University, Fairfax, VA. Directional Regression Revisited. December, Department of Mathematical Sciences, Michigan Technological University, Houghton, MI. Robustified Inverse Regression. July, School of Finance and Statistics, East China Normal University, Shanghai, P. R. China. New developments in sufficient dimension reduction. January, Department of Statistics, Temple University, Philadelphia, PA. Dimension reduction for non-elliptically distributed predictors. December, Department of Mathematics, University of New Orleans, New Orleans, LA. Dimension reduction for non-elliptically distributed predictors. Temple University, August 2009-Present. Undergraduate Courses Taught: Stat 2521, Data Analysis & Statistical Computation, Fall 2012, CATE Q8 score: 4.5/5.0 Stat 3503, Linear Regression & Time Series, Spring 2012, CATE Q8 score: 4.8/5.0 Stat 2512, Intermediate Business Statistics, Fall 2011, CATE Q8 score: 5.0/5.0 Stat 2103, Business Statistics, Spring 2011, CATE Q8 score: 3.6/5.0 Stat 3503, Linear Regression & Time Series, Spring 2010, CATE Q8 score: 4.4/5.0 Stat 2102, Selected Topics in Statistics, Fall 2009, CATE Q8 score: 4.3/5.0 Graduate Courses Taught: Stat 8108, Applied Multivariate Analysis, Fall 2012, CATE Q8 score: 4.6/5.0 Stat 8109, Linear Regression & Time Series, Spring 2012, CATE Q8 score: 5.0/5.0 Stat 8108, Applied Multivariate Analysis, Fall 2011, CATE Q8 score: 4.9/5.0 Stat 8002, Probability Theory II, Spring 2011, CATE Q8 score: 3.9/5.0 Stat 8108, Applied Multivariate Analysis, Fall 2010, CATE Q8 score: 4.8/5.0 Stat 8001, Probability Theory I, Fall 2010, CATE Q8 score: 3.8/5.0 Stat 8109, Linear Regression & Time Series, Spring 2010, CATE Q8 score: 5.0/5.0 Stat 8108, Applied Multivariate Analysis, Fall 2009, CATE Q8 score: 4.1/5.0 Workshop Taught: Math Bootcamp for incoming Ph.D. Students, Summer Math Bootcamp for incoming Ph.D. Students, Summer SAS Workshop for incoming Ph.D. Students, Spring/Summer Pennsylvania State University, January 2008-May Courses Taught: Elementary Probability; Mathematical Statistics. Dissertation Alicia Strandberg, Ph.D. (graduated in Summer 2012) A Nonparametric Test for Deviation Committees from Randomness with Applications to Stock Markdet Index Data. Committee member, August 2010 to August Bhramori Banerjee, Ph.D. (graduated in Fall 2011) Multiple Testing in the Presence of Correlations. Committee member, July 2010 to December Li He, Ph.D. (graduated in Summer 2011) Incorporating Correlations to Improve Multiple Testing Procedures Controlling False Discoveries. Committee member, January 2010 to May 2011.

5 Shuo Zheng, Ph.D. (graduated in Spring 2011) New Hierarchical Nonlinear Modeling for Count Data: Estimation and Testing in the Presence of Overdispersion. Committee member, November 2009 to May Yang Yang, Department of Management Information Systems, Ph.D. (graduated in Fall 2011), Open Innovation Contests in Online Markets: Idea Generation and Idea Evaluation with Collective Intelligence. Committee member, September 2010 to December Ibrahim Turkoz, Ph.D. candidate, Application of Bayesian Analysis in Time to Event Data in Clinical Trials. Committee member, September 2010 to present. Siwei Gao, Ph.D. candidate, Department of Risk Management and Insurance. reviewer. Outside Thesis Yizhi Sun, Bachelor of Statistics (graduated in Summer 2010). Robust Sliced Inverse Committees Regression. Committee chair, January 2010 to May Xiaoran Zhang, Bachelor of Accounting (graduated in Summer 2010). An Attempt to Estimate Life Expectancy in Life Tables. Committee member, January 2010 to May Services Department Service 1. Graduate Affairs Committee, Fall 2009-Present; 2. Department Seminar Organizer, Fall 2011-Spring 2012; 3. Search Committee, Fall 2010-Spring 2012; 4. Personnel Committee, Fall 2009, Fall 2010, Fall School Service 1. Center for Statistical Analysis Executive Committee, Fall 2011-Present; 2. Doctoral Program Committee, Fall 2010-Present; 3. Master Program Committee, Spring 2013-Present; 4. MBA/MS Planning Committee, Fall 2011-Spring 2012; 5. Merit Committee, Fall 2010, Fall Profession Service Reviewer for a total of 20 journals: Annals of Statistics (JVC A), Journal of the American Statistical Association (JVC A), Journal of Multivariate Analysis (JVC A-), Computational Statistics and Data Analysis (JVC A-), Journal of Machine Learning Research, Statistica Sinica, Sankhya, Science China Mathematics, Statistics in Biopharmaceutical Research, Statistics and Probability Letters, Statistics and Its Interface, Communications in Statistics, Statistical Analysis and Data Mining, Journal of Nonparametric Statistics, Journal of Statistical Computation and Simulation, Statistical Methodology, Survey Methodology, Wiley Interdisciplinary Reviews: Computational Statistics, Astrophysical Journal, Journal of Economics and Business. Organizer of a special session for Winter Marketing Educators Conference 2013, American Marketing Association. Big Data Analysis: Exploring Methodological Advances at the Statistics-Marketing Interface. Co-organizer, Bharadwaj, N. Honors & Pass with distinction for Ph.D. candidacy test, Department of Statistics, Pennsylvania Awards State University, Eberly College of Science Fellowship Award, Pennsylvania State University, Membership Institute of Mathematical Statistics. American Statistical Association.

6 International Chinese Statistical Association. Industry Working Experience Research Intern at Lubrizol, Statistics & Intelligent Systems Group, Summer Research Intern at FDA, Division of Biometrics I of CDER, Summer Student Consultant at Statistical Consulting Center, Pennsylvania State University, 2005.