Honglang Wang
Assistant Professor of Statistics
Department of Mathematical Sciences
School of Science
Indiana University-Purdue University Indianapolis
402 N.Blackford St., Indianapolis, IN, 46202

Office: LD 270B
Phone: (317) 274-7858
Fax: (317) 274-3460
Email: hlwang [at] iupui [dot] edu

Education

PhD in Statistics (2015): Department of Statistics and Probability, Michigan State University. Advisors: Yuehua Cui and Ping-Shou Zhong.
Dual PhD in Quantitative Biology (2015): Natural Science, Michigan State University. Advisors: C. Robin Buell and Yuehua Cui.
MS in Mathematics (2010): Center of Mathematical Sciences, Zhejiang University. Advisor: Kefeng Liu.
BS in Mathematics and Applied Mathematics (2007): Department of Mathematics, Tianjin University, Tian, China.

See my Curriculum Vitae for more information.

Research Interests

Statistical Analysis for Longitudinal and Functional Data
High Dimensional Statistical Inference and its Applications
Machine Learning/Deep Learning
Nonparametric Statistics
Empirical Likelihood Methods and its Applications
Statistical Genetics and Statistical Genomics

Publications

Gaussian Quadrature
Ruohong Li, Honglang Wang, Wanzhu Tu,
Wiley StatsRef-Statistics Reference Online, 2019, accepted

Robust graph change-point detection with application to brain evolvement study
Fang Han, Xi Chen, Honglang Wang, Lexin Li, Brian Caffo,
Submitted

The Effects of Spatial Frequency and Colormap Characteristics on the Perception of 2D Pseudocolor Scalar Fields
Pratik Nalawade, Kate Ansah-Koi, Khairi Reda, Fang Li, Honglang Wang, Wei Zheng,
Submitted

Expired Tidal Volume Variation in Extremely Low Birth Weight and Very Low Birth Weight Infants on Volume-Targeted Ventilation
Samuel Wong, Honglang Wang, Robert Tepper, Gregory M. Sokol , Rebecca Rose ,
The Journal of Pediatrics, 2018, accpeted

Bootstrap Methods: The Classical Theory and Recent Development
Honglang Wang, Wanzhu Tu,
Wiley StatsRef-Statistics Reference Online, 2018, accepted

Empirical Likelihood Ratio Tests for Coefficients in High Dimensional Heteroscedastic Linear Models
Honglang Wang, Ping-Shou Zhong, Yuehua Cui,
Statistica Sinica 28 (2018), 2409-2433

Unified empirical likelihood ratio tests for functional concurrent linear models and the phase transition from sparse to dense functional data
Honglang Wang, Ping-Shou Zhong, Yuehua Cui, Yehua Li,
Journal of the Royal Statistical Society: Series B (Statistical Methodology) 80.2 (2018): 343-364.

A provable smoothing approach for high dimensional generalized regression with applications in genomics
Fang Han, Hongkai Ji, Zhicheng Ji, Honglang Wang,
Electronic Journal of Statistics 2017, Vol. 11, No. 2, 4347-4403.

Statistical identification of gene-gene interactions triggered by nonlinear environmental modulation
Xu Liu, Honglang Wang, Yuehua Cui,
Current Genomics, 2016 Oct; 17(5): 388-395.

A powerful statistical method identifies novel loci associated with diastolic blood pressure triggered by nonlinear gene-environment interaction [PDF]
Honglang Wang, Tao He, Cen Wu, Ping-Shou Zhong, Yuehua Cui,
BMC Proceedings 2014, 8(Suppl 1):S61 (17 June 2014)

Funded Research Grants

§§§ Sole-PI, 09/2016-09/2017, NSF subcontract

News

§§§ Invited Talk---Robust Estimation of Heterogeneous Treatment Effect using Electronic Health Record Data, April 17, 2020 @ Department of Bioinformatics and Biostatistics Seminar @ University of Louisville
§§§ Invited Talk---Robust Graph Change-point Detection for Brain Evolvement Study, June 10, 2019 @ ICSA Applied Statistics Symposium @ Raleigh, North Carolina
§§§ Invited Talk---Robust Graph Change-point Detection for Brain Evolvement Study, May 31, 2019 @ Symposium on Data Science and Statistics @ Bellevue, Washington
§§§ Invited Talk---Robust Graph Change-point Detection for Brain Evolvement Study, October 28, 2018 @ AMS Sectional Meeting-Special Session on Big Data and Statistical Analytics @ San Francisco State University, San Francisco
§§§ Invited Talk---Robust Graph Change-point Detection for Brain Evolvement Study, July 04, 2018 @ 2018 ICSA China Conference with the Focus on Data Science @ Qingdao
§§§ Invited Talk---Empirical Likelihood Ratio Tests for Coefficients in High Dimensional Heteroscedastic Linear Models, July 01, 2018 @ The 8th International Forum on Statistics @ Renmin University of China, Beijing
§§§ Invited Talk---Robust Graph Change-point Detection for Brain Evolvement Study, June 25, 2018 @ College of Mathematics and Statistics @ SHunan Normal University, Changsha
§§§ Invited Talk---Robust Graph Change-point Detection for Brain Evolvement Study, June 13, 2018 @ School of Statistics and Management @ Shanghai University of Finance and Economics, Shanghai
§§§ Invited Talk---Unified empirical likelihood ratio tests for functional linear models and the phase transition from sparse to dense functional data, April 20, 2018 @ DMS Colloquium @ Auburn University, Auburn, Alabama
§§§ Poster---Empirical Likelihood Ratio Tests for Coefficients in High Dimensional Heteroscedastic Linear Models, August 12-14, 2017 @ Second Workshop on Higher-Order Asymptotics and Post-Selection Inference (WHOA-PSI)^{2} @ Washington University in St. Louis
§§§ Invited Talk---Empirical Likelihood Ratio Tests for Coefficients in High Dimensional Heteroscedastic Linear Models, June 25-28, 2017 @ 2017 ICSA Applied Statistics Symposium @ Hilton Chicago Downtown, Chicago
§§§ Poster---Unified empirical likelihood ratio tests for functional linear models and the phase transition from sparse to dense functional data, October 6-7, 2016 @ Nonparametric Statistics Workshop @ University of Michigan, Ann Arbor
§§§ Contributed Talk---Testing Low-dimensional Coefficients in High Dimensional Heteroscedastic Linear Models, Jul. 30-Aug. 04, 2016 @ Joint Statistical Meetings (JSM) @ McCormick Place, Chicago
§§§ Invited Talk---Unified empirical likelihood ratio tests for functional linear models and the phase transition from sparse to dense functional data, May 27-29, 2016 @ Big Statistics & Data Science Joint Conference @ Renmin University of China, Beijing, China
§§§ Contributed Talk---Provable Smoothing Approach in High Dimensional Generalized Regression Models, Mar. 07, 2016 @ ENAR @ JW Marriott Austin, in Austin, Texas
§§§ Research Talk---Provable Smoothing Approach in High Dimensional Generalized Regression Models, Feb. 03, 2016 @ Statistics Seminar @ IUPUI
§§§ Invited Talk---Unified empirical likelihood ratio tests for functional linear models and the phase transition from sparse to dense functional data, Sep. 18, 2015 @ Biostatistics Seminar @ IUPUI
§§§ Research Talk---Testing Low-dimensional Coefficients in High Dimensional Heteroscedastic Linear Models, Sep. 11, 2015 @ Statistics Seminar @ IUPUI
§§§ Organizing 2015 Summer Short Course: Neuroimaging Data Analysis, Instructor: Mark Reimers, May 26, June 2, June 9, @ MSU

Teaching

2020 Fall, Statistical Computing (STAT52100-24694) @ IUPUI
2020 Fall, Statistical Modelling Using R and SAS (STAT42100-27317) @ IUPUI
2020 Fall, Introduction to Statistics (STAT35000-28998) @ IUPUI
2020 Summer, Introduction to Statistics (STAT35000-11121) @ IUPUI
2020 Spring, Statistical Inference (STAT51700-20616) @ IUPUI
2020 Spring, Statistical Theory (STAT41700-20611) @ IUPUI
2020 Spring, Introduction to Statistics (STAT35000-21296) @ IUPUI
2019 Fall, Statistical Computing (STAT52100-24302) @ IUPUI
2019 Fall, Statistical Modelling Using R and SAS (STAT42100-27207) @ IUPUI
2019 Fall, Introduction to Statistics (STAT35000-30888) @ IUPUI
2019 Spring, Statistical Inference (STAT51700-21724) @ IUPUI
2019 Spring, Introduction to Statistics (STAT35000-22480) @ IUPUI
2018 Fall, Statistical Computing (STAT52100-22838) @ IUPUI
2018 Fall, Statistical Modelling Using R and SAS (STAT42100-26037) @ IUPUI
2018 Fall, Introduction to Statistics (STAT35000-25873) @ IUPUI
2018 Spring, Statistical Inference (STAT51700-22537) @ IUPUI
2018 Spring, Introduction to Statistics (STAT35000-23995) @ IUPUI
2017 Fall, Statistical Computing (STAT52100-22940) @ IUPUI
2017 Fall, Statistical Modelling Using R and SAS (STAT42100-26466) @ IUPUI
2017 Fall, Introduction to Statistics (STAT35000-26266) @ IUPUI
2017 Spring, Advanced Statistical Inference---Nonparametric Regression (STAT62800-31654) @ IUPUI
2016 Fall, Applied Regression Analysis (STAT51200-21329) @ IUPUI
2016 Fall, Introduction to Statistics (STAT35000-22433) @ IUPUI
2016 Spring, Introduction to Statistics (STAT35000-24592) @ IUPUI
2015 Fall, Introduction to Statistics (STAT35000-23646 and STAT35000-24842) @ IUPUI
2012 Summer, Intro Stats (STT200) @ MSU
2013 Summer, Intro Prob & Stat for Business (STT315) @ MSU

Service

2018 Fall-present, Faculty advisor of IUPUI ASA Student Chapter
2020 Fall, Organizer of Statistics Seminars @ IUPUI.
2020 Spring, Organizer of Statistics Seminars @ IUPUI.
2019 Fall, Organizer of Statistics Seminars @ IUPUI.
2019 Spring, Organizer of Statistics Seminars @ IUPUI.
2018 Fall, Organizer of Statistics Seminars @ IUPUI.
2018 Spring, Organizer of Statistics Seminars @ IUPUI.
2013 Fall, Chairman of Statistics Student Seminars (SSS) on Paper Reading @ MSU.
2012 Fall-2013 Spring, Chairman of Statistics Student Seminars (SSS) on Graphical Models @ MSU.
2011 Fall-2012 Spring, Chairman of Statistics Student Seminars (SSS) @ MSU.

Honors and Awards

Purdue Research Foundation Summer Faculty Grant (2019), Purdue University
Purdue Research Foundation International Travel Grant (2018), Purdue University
Travel Award for the "20th Meeting of New Researchers in Statistics and Probability" (2018), Institute of Mathematical Statistics
NSF Travel Award for The Nonparametric Statistics Workshop entitled "Integration of Theory, Methods and Applications" (2016), University of Michigan, Ann Arbor
College of Natural Science US15 Dissertation Completion Fellowship (2015), Michigan State University
College of Natural Science US14 Dissertation Continuation Fellowship (2014), Michigan State University
William L Harkness Teaching Award, Michigan State University (2014)
Travel Award of GAW18 (2012)
Second-class Award of Honor for Graduate, Zhejiang University (2008)
First Prize in the 13th National Graduate Summer School in Mathematics (2008)
Scholarship for Academic Excellence, Tianjin University (2005-2006)
6th Outstanding Student of Science and Technology in Tianjin University (2005)
Tianjin University-Yuandong Chunguang Scholarship (2005)
Scholarship for Academic Excellence, Tianjin University (2004)

Personal

Academic Blog

PhD Students

Ruohong Li

Ruohong Li --- PhD student in Biostatistics (co-advised with Dr. Wanzhu Tu)

Causal Inference, Machine Learning, Biostatistics

Wenzhe Jiao

Wenzhe Jiao --- PhD student in Earth Sicence (advised under Dr. Lixin Wang) with minor in applied statistics (advised under me)

Drought, Spatio-temporal, Machine Learning, Earth Science

Yishan Cui --- PhD student in Applied Statistics.

Semiparametric Inference

Xiang Wang --- PhD student in Applied Statistics.

Functional Data Analysis, Nonparametric Smoothing

Master Students


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