Zheng Xu

Education and Training

• • Postdoc. University of North Carolina at Chapel Hill, Bio-statistics and Genetics, Chapel Hill, NC, 2012-2016. Adviser: Prof. Yun Li

  • Ph.D. Iowa State University, Statistics and Economics, Ames, IA, 2012. Advisers: Prof. Song Xi Chen and Prof. David Hennessy

  • M.Sc. Illinois State University, Applied Economics, Normal, IL, 2005.

  • B.Econ. Fudan University, International Economics with the Minor in Computer Science, Shanghai, China, 2001.

Working Experience

• Associate Professor, Department of Mathematics and Statistics, Wright State University, Dayton, OH, 2025-now

• Assistant Professor, Department of Mathematics and Statistics, Wright State University, Dayton, OH, 2019-2025

• Research Assistant Professor, Department of Statistics, University of Nebraska-Lincoln, Lincoln, Nebraska, 2016-2019

• Postdoctoral Research Associate , Departments of Biostatistics and Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 2012-2016

• Risk Analyst Intern, Noble Americas Company, Stamford, CT, 2011

• Teaching Assistant and Research Assistant, Department of Statistics, Iowa State University, Ames, IA 2009-2012

• Teaching Assistant, Department of Economics, Iowa State University, Ames, IA 2005-2009

• Graduate Assistant, Department of Economics, Illinois State University, IL 2003-2005

Research Interest

• Biostatistics, Statistical Genetics, Genetic Epidemiology, Bioinformatics, Genome Structure

• Machine Learning, Prediction, Nonparametric Methods, Time Series, Stochastic Process 

• Agricultural Statistics, Econometrics, Financial Statistics, Image Analysis

Teaching

Wright State University

• STT 1600, Statistical Concepts (Fall 2024, Fall 2025) ; STT 3700 Introduction to Statistical Inference (Fall 2025)

• STT 4110/6110 Applied Time Series (Spring 2020, Spring 2021, Fall 2024) 

• STT 4260/6260 Survival Analysis (Fall 2025); STT 4300/6300 Biostatistics  (Fall 2020)

• STT 4640/6640 Machine Learning (Fall 2020, Spring 2025); STT 4660/6660 Statistical Methods I (Fall 2021, Fall 2022)

• STT 4670/6670 Statistical Methods II (Spring 2022, Spring 2023, Spring 2024)

• STT 7020 Applied Stochastic Process (Spring 2020, Spring 2022)

• STT 7140 Statistical Modelling for Environmental Data (Spring 2021, Spring 2024)

• STT 7400 Categorical Data Analysis (Fall 2022, Fall 2024); STT 7440 Applied Multivariate Analysis (Fall 2019, Fall 2021)

• STT 7670 Applied Regression Analysis (Spring 2023, Spring 2025); STT 7910 Statistical Consulting (Spring 2025)

University of Nebraska - Lincoln

• STAT 981 Statistical Learning (Spring 2019)

• STAT 841 Statistical Methods for High-throughput Biological Data (Fall 2018)

• STAT 883 Mathematical Statistics II - Statistical Inference (Spring 2018) 

• STAT 802 Design and Analysis of Research Studies (Fall 2017) 

• STAT 982 Advanced Inference (Spring 2017)

• STAT 980 Advanced Probability Theory 1 (Fall 2016)

• LIFE 891-002 Special Topics in Life Sciences (2-3 weeks in each Spring Semester of 2017, 2018, 2019)

Publications 

A complete list of publications can be found in Google Scholar: https://scholar.google.com/citations?user=OzNHuxcAAAAJ&hl=en

Have received 2582 citations in Google Scholar and have published 70 journal articles and 2 book chapters.

List of Selected Publications 

1. Z Xu, 2025, An expectation-maximization algorithm for logistics regression based on individual-level predictors and aggregate-level  response", forthcoming in Statistics in Transition New Series. (R).

2. Z Xu, S Yan, C Wu, Q Duan, S Chen, Y Li, 2023, Next-generation sequencing data-based association testing of a group of genetic markers for complex responses using a generalized linear model framework, Mathematics, 11, 2560. Impact Factor: 2.592. (R).

3. Z Xu, S Yan, S Yuan, C Wu, S Chen, Z Guo, Y Li, 2023, Efficient two-stage analysis for complex trait association with arbitrary depth sequencing data, Stats, 6, 468-481. Impact Factor: 0.9. (R). 

4. C Yin, C Zhou, Y Ge, X Gao, C Wu, Z Xu, C Huang, G Hu, P Liu, C Yin, X Guo, Effects and potential mechanism of dietary vitamin C supplementation on hepatic lipid metabolism in growing laying hens under chronic heat stress, Journal of Animal Science, 2023, 101. (R).

5. Z Xu, 2023, Logistics regression based on individual-level predictors and aggregate-level responses, Mathematics, 11, 276. Impact Factor: 2.592 (R).

6. C Jiang, X Hou, X Gao, P Liu, X Guo, G Hu, Q Li, C Huang, G Li, W Fang, W Mai, C Wu, Z Xu, P Liu, 2023, The 16S rDNA high-throughput sequencing correlation analysis of milk and gut microbial communities in mastitis Holstein cows, BMC Microbiology 23. 180. Impact Factor: 4.31. (R).

7. Z Xu, C Wu, 2023, Combination of transfer deep learning and classical machine learning models for multi-view image analysis, Computer Sciences and Mathematics Forum, 2023, 1, 13. (R)

8. S Chen, AM Woodruff, J Campbell, S Vesely, Z Xu, C Snider, 2023, Combining probability and nonprobability samples by using multivariate mass imputation approaches with application to biomedical research, Stats, 6, 617–625. Impact Factor: 1.3. (R).

9. A Kochvar, Y Liu, M Mnunafo, Z Xu, H Dai, 2023, Genetic and environmental influences on early-age susceptibility and initiation of nicotine-containing product use: A twin-pairs study, Tobacco Prevention and Cessation, 9, 34. (R).

10. Z Xu, 2023, Association testing of a group of genetic markers based on next generation sequencing data and continuous response using a linear model framework. Mathematics, 11, 1285. Impact Factor: 2.592. (R).

11. H Zhao, Y Zhan, Z Xu, JJ Nduwamungu, Y Zhou, R Powers, C Xu, 2022, The application of machine-learning and Raman spectroscopy for the rapid detection of edible oils type and adulteration, Food Chemistry, 373, Part B, 2022, 131471. Impact Factor: 7.514. (R).

12. H Dai, L Henriksen, Z Xu, N Rathnayake, 2022, Using place-based characteristics to inform FDA tobacco sales inspections: results from a multilevel propensity score model, Tobacco Control 2022:31:e148-e155. Impact Factor: 6.726.

13. S Khan, N Ahamad, S Bhadra, Z Xu, YJ Xu, 2022, Smc5/6 complex promotes Rad3ATR checkpoint signaling at the perturbed replication fork through sumoylation of the RecQ helicase Rqh1. Mol. Cell. Biol. 42(6). Impact Factor: 3.2. This paper is featured on the journal cover.

14. C Wu, Z Xu, G Li, Z Zou, T Wang, 2022, The correlation between gut microbiota and bovine mastitis, Animal Health Perspectives, Unique Scientific Publishers. (R).

15. Q Zhang, Z Xu, Y Lai, 2021, An empirical Bayes approach for the identification of long-range chromosomal interaction from Hi-C data, Statistical Applications in Genetics and Molecular Biology, 20, 1-15. Impact Factor: 0.778. (R).

16. T Wang, Z Xu, D Kolady, JD Ulrich-Schad, D Clay, 2021, Cover crops usage in south Dakota: farmer perceived profitability and future adoption decisions. Journal of Agricultural and Resource Economics 46, 2, 287-30. Impact Factor: 1.184. (R).

17. T Wang, Y Fan, Z Xu, S Kumar, B Kasu, 2021, Adopting cover crops and buffer strips to reduce nonpoint source pollution: Understanding the farmers’ perspectives in the U.S. Northern Great Plains, Journal of Soil and Water Conservation. Impact Factor: 2.209.

18. L Huang, X Guo, P Liu, Y Zhao, C Wu, C Zhou, C Huang, G Li, Y Zhuang, S Cheng, H Cao, C Zhang, Z Xu, X Liu, G Hu, P Liu, 2021, Correlation between acute brain injury and brain metabonomics in dichlorvos-poisoned broilers, Journal of Hazardous Materials, 422, 2022, 126849. Impact Factor: 10.588. (R).

19. Z Xu, C Wu, 2020, Machine learning and statistical approaches for plant phenotyping, Intelligent Image Analysis for Plant Phenotyping, 1st edition, edited by A Samal and SD Choudury, CRC Press. ISBN: 9781315177304. (R).

20. X Dai, Z Xu, Z Liang, X Tu, S Zhong, J Schnable, P Li, 2020, Non-homology-based prediction of gene functions in maize (Zea mays ssp. mays), Plant Genome, 13, e20015. Impact Factor: 3.847. (R).

21. C Miao, A Pages, Z Xu, E Rodene, J Yang, J Schnable, 2020, Semantic segmentation of sorghum organs using hyperspectral data identifies genetic associations, Plant Phenomics, 2020, 4216373. Impact Factor: 6.961. (R).

22. H Dogan, J Shu, Z Hakguder, Z Xu, J Cui, 2020, Elucidation of molecular links between obesity and cancer through microRNA regulation, BMC Medical Genomics, 13, 161 (2020). Impact Factor: 2.57. (R). 

23. J Reinhardt, JJ Romine, Z Xu, 2020, Factors contributing to student satisfaction with dental loupes and headlights, European Journal of Dental Education, 24, 266-271. Impact Factor: 1.05. (R).

24. L Lu, X Liu, WK Huang, P Giusti-Rodriguez, J Cui, S Zhang, W Xu, Z Wen, S Ma, JD Rosen, Z Xu, C Bartels, R Kawaguchi, M Hu, PC Scacheri, Z Rong, Y Li, PF Sullivan, H Song, G Minf, Y Li, ,F Jin, 2020, Robust Hi-C Maps of Enhancer-Promoter Interactions Reveal the Function of Non-coding Genome in Neural Development and Diseases, Molecular Cell, 79, 521-534. Impact Factor: 15.584

25. M Li, NK Wijewardane, Y Ge, Z Xu, MR Wilkins, 2020, Visible/near infrared spectroscopy and machine learning for predicting polyhydroxybutyrate production cultured on alkaline pretreated liquor from corn stover, Bioresource Technology Reports, 9, 100386. (R).

26. H Zhao, Y Zhan, Z Xu, JJ Nduwamungu, Y Zhou, C Xu, 2020, Machine learning-driven Raman spectroscopy for rapidly detecting type, adulteration, and oxidation of edible oils, INFORM, 31 (4), 12-15. (R).

27. Q Duan, Z Xu, L Raffield, S Chang, D Wu, EM Lange, AP Reiner, Y Li, 2018, A robust and powerful two-step testing procedure for local ancestry adjusted allelic association analysis in admixed populations, Genetic Epidemiology, 42, 288-302. Impact Factor: 1.954

28. Z Xu, C Valdes, J Clarke, 2018, Existing and potential statistical and computational approaches for the analysis of 3D CT images of plant roots, Agronomy, 8, 71. (R).

29. WE Huffman, Y Jin, Z Xu, 2018, The economic impacts of technology and climate change: new evidence unearthed from crop yields, Agricultural Economics, 49, 463-479. Impact Factor: 2.263. (R)

30. Z Xu, Q Duan, J Cui, Y Qiu, Q Jia, C Wu, J Clarke, 2018, Analysis of genetic and non-genetic factors influencing triglycerides-lowering fenofibrate drug effects based on paired observations, BMC Proceedings, 12, 46. (R).

31. J Martin, Z Xu, AP Reiner, KL Mohlke, P Sullivan, B Ren, M Hu and Y Li, 2017, HUGIn: Hi-C Unifying Genomic Interrogator. Bioinformatics, 33, 3793-3795. Impact Factor: 5.61

32. Z Xu, 2016, An alternative circular smoothing method to nonparametric estimation of periodic functions, Journal of Applied Statistics, 43, 1649-1672. 

33. G Zhang, KC Huang, Z Xu, JY Tzeng, KN Conneely, W Guan, J Kang and Y Li, 2016, Across-platform imputation of DNA methylation levels using penalized functional regression, Genetic Epidemiology, 40, 333-340. Impact Factor: 1.954

34. Z Xu, G Zhang, C Wu, M Hu, Y Li, 2016, Fast-HiC: a fast and accurate algorithm to detect long-range chromosomal interactions from Hi-C data, Bioinformatics, 32, 2692-2695.

35. AD Schmitt, M Hu, I Jung, Z Xu, Y Qiu, CL Tan, Y Li, CL Barr and B Ren, 2016, A compendium of chromatin contract maps reveal frequently interacting regions in the human genome, Cell Reports, 17, 2042-2059.  Impact Factor: 8.109

36. Z Xu, Q Duan, G Zhang, S Chai, B Zhang, C Wu, F Jin, F Yue, Y Li and M Hu, 2016, HiView: An integrative genome browser to leverage Hi-C results for the interpretation of GWAS data, BMC Research Notes, 9, 159.

37. C Wu, Z Xu, R Gai, K Huang, 2016, Matrine ameliorates spontaneously developed colitis in Interleukin-10-deficient mice, International Immunopharmacology, 36, 256-262. Impact Factor: 3.943

38. Z Xu, G Zhang, F Jin, M Chen, TS Furey, PF Sullivan, Z Qin, M Hu, Y Li, 2015, A hidden Markov random field-based Bayesian method for the detection of long-range chromosomal interactions in Hi-C data, Bioinformatics, 32, 650-656. Impact Factor: 5.61

39. S Yan, S Yuan, Z Xu, B Zhang, B Zhang, G Kang, A Byrnes and Y Li, 2015, Likelihood based complex trait association testing for arbitrary depth sequencing data, Bioinformatics, 31, 2955-2962. Impact Factor: 5.61

40. Z Xu, Q Duan, SYan, W Chen, M Li, E Lange, Y Li, 2015, DISSCO: Direct imputation of summary statistics allowing covariates, Bioinformatics, 31, 2434-2442. 

41. SX Chen, Z Xu, 2014, On implied volatility for options – Some reasons to smile and more to correct, Journal of Econometrics, 179, 1-15.

42. J Kang, KC Huang, Z Xu, Y Wang, GR Abecasis and Y Li, 2013, AbCD: Arbitrary coverage design for sequencing-based genetic studies, Bioinformatics, 29, 799-801. Impact Factor: 5.61

43. SX Chen, Z Xu, 2013, On smoothing estimation for seasonal time series with long cycles, Statistics and Its Interface, 6, 435-447. 

44. Z Xu, DA Hennessy, K Sardana and G Moschini, 2013, The realized yield effect of genetically engineered crops: U.S. maize and soybean, Crop Science, 53, 735-745. Impact Factor: 1.878

45. Z Xu, 2013, Estimation of parametric homogeneous stochastic volatility pricing formulae based on option data, Economics Letters, 120, 369-373.  

Academic Services

• Associate Editor (2016-) for Statistical Papers

• Associate Editor (2022-) for Journal of Statistical Computation and Simulation

• Guest Associate Editor (2017-2018) and Associate Editor (2018-) for Statistical Analysis and Data Mining

• Academic Editor (2021-) for PLOS ONE

• Associate Editor (2017-) for Bio-Med Central (BMC) Research Notes

• Reviewer for Journals: Statistical Sinica; Biometrics; Journal of Business and Economics Statistics; Bioinformatics; Journal of Applied Statistics; Human Genetics; Gene; PLOS One; Scientific Reports;  BMC Health Services Research; Public Health Nutrition; Journal of Financial Economic Policy; China Health Review; Journal of Finance and Economics; Frontiers in Public Health, section Epidemiology; Journal of Finance and Accounting; Journal of Agricultural Science and Technology;  etc. 

• Reviewer for Conference: Genetic Analysis Workshop (GAW) 20

Conferences

• Detect chromatin interaction from multiple Hi-C datasets by hierarchical hidden Markov random field model (Paper Presentation), International Chinese Statistical Association Applied Statistics Symposium 2016

• Rare variant test based on next-generation sequencing data with arbitrary length (Paper Presentation), Joint Statistical Meetings 2016

• A hidden Markov random field based Bayesian method for the detection of long-range chromosomal interactions in Hi-C Data (Poster), American Society of Human Genetics 2015

• Comparison of alignment strategies for allelic expression imbalance (Poster), American Society of Human Genetics 2015

• Development of statistical methods and bioinformatics tools for genome-wide chromosome interaction data (Poster), Second Annual Research Symposium 2015

• Alternative peak calling methods on Hi-C data accommodating the whole spectrum of dispersion (Poster), American Society of Human Genetics 2014

• A HMRF-based Bayesian method for chromatin interaction calling (Paper Presentation), Joint Statistical Meetings 2014

• Econometric estimates of the contribution of genetic modification to yield potential and damage control: evidence from state average corn yields (Paper Presentation), Symposium and Festschrift in Honor of Wallace Huffman

• Some reasons to smile: implied volatilities in presence of pricing error (Paper Presentation), Joint Statistical Meetings 2010

• Have biotech seeds increased maize yields (Poster), Agricultural and Applied Economic Association Meeting 2010

Computer Skills

• • Engineering programing by JAVA, C/C#/C++, PYTHON, MATLAB, Mathematica and Perl.

  • Statistical and econometric programing by R, SAS, GAUSS, STATA and TSP.

  • Bloomberg interface, Logical Information Machine, XML, SQL, ArcGIS and Excel VBA.

  • Website programing by HTML, PHP and JavaScript.

  • Rich experience in handling large data and Linux server.

Certifications

• • Oracle Certified Professional JAVA SE Programmer (OCPJP) Certification (96% in JAVA 6). 

  • Certified Financial Analyst (CFA) Exam 1. 

  • Associate of the Society of Actuaries (ASA) All Required Exams: (i) Probability, (ii) Financial Mathematics, (iii) Models for Life Contingencies, (iv) Construction and Evaluation of Actuarial Models and (v) Models for Financial Economics.

Awards

• T.A. Bancroft Award, Department of Statistics, Iowa State University, 2010.

• People’s Scholarship, Fudan University, 1998.