Consulting Team

Director and Associate Director

Director: Minge Xie  (Ph.D. Illinois)

Dr. Xie’s main research interest lies in developing new statistical methodologies and theories for problems stemming from interdisciplinary research. His research interests include statistical applications in Bio-medical Sciences, Social Sciences, Industry, Engineering, and Environmental Sciences.  In the past six years, Dr. Xie has conducted research projects sponsored by grants from the National Science Foundation (NSF),  the National Institute of Health (NIH),  The Department of Veterans Affairs (VA), the Federal Aviation Administration (through RU IE department),  the American Diabetes Association, among others. 

Associate Director: Steven Buyske (Ph.D. Brown; Ph.D. Rutgers)

Dr. Buyske's main research interests are in statistical genetics, biostatistics, psychometrics, and experimental design.  He holds adjunct appointments in the Genetics Department and the Center of Alcohol Studies, and is actively involved in several interdisciplinary research projects with colleagues in the Genetics, Molecular Biology, and Psychology Departments, the Center of Alcohol Studies, and the UMDNJ Departments of Psychiatry, Neurology, and Surgery. Dr. Buyske's research projects are supported in part by grants from the National Institutes of Health as well as the National Alliance for Autism Research.

Associate Director: Michael LuValle (Ph.D. University of California, Davis)

Dr. LuValle's main research interests lies in integrating physical, chemical, and biological theory into statistics, to develop statistical frameworks which result in novel experiment design and data analysis tools. His work includes developing assistive intelligence computing frameworks for experimental design and data analysis in both accelerated testing, and in modeling chaotic systems.

Contact Information

Telephone: 848-445-2690
FAX: 732-445-3428
E-mail: osc@stat.rutgers.edu

Or, Write to:

Office of Statistical Consulting 
Department of Statistics
501 Hill Center-Busch Campus
Rutgers, The State University of New Jersey
110 Frelinghuysen Rd
Piscataway, NJ 08854-8019, USA

Faculty Advisory Board

  • Professor Regina Liu, Chair, Department of Statistics, Rutgers University
  • Professor John Kolassa, Graduate Director,  Department of Statistics, Rutgers University
  • Professor Harold Sackrowitz, Undergraduate Director, Department of Statistics, Rutgers University

Faculty and Areas of Expertise

  • Pierre Bellec. Assistant Professor. Ph.D ENSAE. High dimensional Statistics, aggregation of estimators, shape constrained problems in Statistics, Probability Theory.
  • Steve Buyske. Associate Research Professor. Ph.D. Brown; Ph.D. Rutgers. Teaching and research in statistical genetics, biostatistics, psychometrics, item response, and experimental design.
  • Javier Cabrera. Professor.  Ph.D. Princeton. Teaching and research in biostatistics, data mining methodology for clinical trial data, functional genomics data, DNA & protein array data, and DNA barcode data; statistical computing, graphics, and machine vision. Fulbright Scholar.
  • Rong Chen. Professor & Director, FSRM Program. Ph.D. Carnegie Mellon. Teaching and research in nonlinear-nonparametric time series analysis, Monte Carlo methods and statistical applications in bioinformatics, finance and engineering. Current co-editor, JBES. Elected Fellow: American Statistical Association, Institute of Mathematical Statistics. Elected member: International Statistical Institute.
  • Harry Crane. Assistant Professor. Ph.D. U. Chicago. Teaching and research in combinatorial stochastic processes, probabilistic symmetry, discrete probability theory, applied probability, combinatorial statistical inference.
  • Tirthanker Dasgupta. Associate Professor. Ph.D Georgia Institute of Technology. Teaching and research in experimental design, casual inference.
  • Lee Dicker. Assistant Professor. Ph.D. Harvard. Teaching and research into high-dimensional data analysis, applications of random matrix theory, statistics in finance, and the analysis of genomic and proteomic data.
  • Richard F. Gundy. Distinguished Professor. Ph.D. U. Chicago (Statistics); Ph.D. U. Indiana (Experimental Psychology). Teaching and research in probability theory. Former associate editor: Potential Analysis, Coloques Mathematicae (UAM, Barcelona); Associate editor: Applied and Computational, Harmonic Analysis.  Fellow (Inaugural class) American Mathematics Society.  Elected Fellow: Institute of Mathematical Statistics.
  • Donald Hoover. Professor. Ph.D. Stanford. Teaching and research in clinical trials, epidemiology, longitudinal methods, group randomization and multiple comparisons. Core member: Institute for   Health, Health Care Policy and Aging Research.
  • Ying Hung.  Associate Professor.  Ph.D. Georgia Institute of Technology. Teaching and research in design of experiment, computer experiment, cell adhesion. Recipient of the 2014 Tweedie New Research Award.
  • John Kolassa. Professor & Graduate Director. Ph.D. U. Chicago. Teaching and research in asymptotics, saddle point approximation, biostatistics, Former Associate Editor, Journal of American Statistical Association. Elected member:  International Statistical Institute. Elected Fellow: American Statistical Association, Institute of Mathematical Statistics.
  • Ping Li. Associate Professor. Ph.D. Stanford. Teaching and research in big data, data mining, statistical learning and computing. Recipient: ONR-YIP Award (2009), Recipient of the NSF “Big Data” Award (2013), AFOSR-YIP Award (2013).
  • Michael LuValle. Instructor. Ph.D University of California, Davis. Teaching and reserach in developing Statistical framework.
  • Regina Y. Liu. Distinguished Professor & Chair. Ph.D. Columbia. Teaching and research in data depth, text mining, resampling, statistical control, aviation safety & risk management, extremes.  Former Editor: J. of Multivariate Analysis. Associate Editor: J. American Statistical Association, Annals of Statistics, TEST, Advances in Stat. Analysis. IMS Medallion Lecturer. 2011 Stieltjes Professor, The Netherlands. Elected Fellow: American Statistical Association, Institute of Mathematical Statistics. Elected Member: International Statistical Institute.
  • Joseph Irwin Naus. Professor. Ph.D. Harvard. Teaching and research in applied probability, sampling theory, data quality control, clustering and coincidence models, scan statistics, matching in DNA sequences. Elected Fellow:  American Statistical Association.  
  • Neville O’Reilly. Research Professor & Associate Director, FSRM Program. Ph.D. Columbia. Teaching and research in financial statistics, application of statistics to risk management. Held senior management positions in the insurance, credit card processing and private equity industries before assuming his post at Rutgers University.
  • Harold B. Sackrowitz.  Distinguished Professor & Undergraduate Director. Ph.D. Columbia. Teaching and research in statistical inference and decision theory, multiple endpoint procedures, order restricted inference. Elected Fellow: American Statistical Association, Institute of Mathematical Statistics.
  • William E. Strawderman. Distinguished  Professor. Ph.D. Rutgers. Teaching and research in decision theory, Bayesian analysis, multivariate statistics. Operations research and applied statistics analyst, Bell Telephone Laboratories. Associate Editor: Institute of Mathematical Statistics Lecture Note Series, Associate Editor: Journal of American Statistical Association, Former Associate Editor: Annals of Statistics, Member of Council Institute of Mathematical Statistics, Former President Northern N.J. Chapter of American Statistical Association. Adjunct Professor, UMDNJ. IMS Medallion Lecturer. Elected Fellow: American Statistical Association, Institute of Mathematical Statistics.
  • Zhiqiang Tan. Professor. Ph.D. U.  Chicago. Teaching and research in  nonparametric and semiparametric statistics, causal inference, missing data problems, survey sampling, Monte Carlo integration. Associate Editor, Biometrics, Annals of Statistics.  NSF Career Award.
  • David E. Tyler. Distinguished Professor. Ph.D. Princeton. Teaching and research in multivariate analysis, robust statistics, directional data, computer vision and time series. Associate Editor, J. of the Royal Statistical Society-B, J. Statistical Planning and Inference.  Elected Fellow: Institute of Mathematical Statistics.
  • Han Xiao. Assistant Professor. Ph.D. U.  Chicago. Teaching and research in time series, high dimension data, probability theory, data mining.
  • Minge Xie. Professor & Director, Office of Statistical Consulting. Ph.D. U. Illinois at Urbana-Champaign. Teaching and research in statistical models, inference, asymptotic, distributional inference, meta-analysis, interdisciplinary research. Elected Fellow: American Statistical Association. Elected Member: International Statistical Institute.  
  • Dan Yang. Assistant Professor. Ph.D. U. of Pennsylvania. Teaching and research in high-dimensional data, multivariate analysis, observational data, and imaging data.
  • Cun-Hui Zhang. Distinguished Professor. Ph.D. Columbia. Teaching and research in high-dimensional data, empirical Bayes, functional MRI, network data, semiparametric and nonparametric methods, survival analysis, statistical inference, probability theory. IMS Medallion Lecturer. Elected Fellow: American Statistical Association, Institute of Mathematical Statistics.