People

The group, its alumni, and how to join

Zheyang Wu

Professor of Mathematical Sciences, Worcester Polytechnic Institute. CV · ORCID · Google Scholar

  • Professor of Mathematical Sciences, WPI, since 2021. Associate Professor, 2015–2021. Assistant Professor, 2009–2015.
  • Ph.D. in Biostatistics, Yale University, 2009. M.Phil. in Epidemiology and Public Health, Yale University, 2007. M.S. in Mathematics, University of New Orleans, 2004. B.S., Chongqing University, 1998.

Current students

  • Victoria Pan (Data Science and Bioinformatics and Computational Biology) and Saahithi Kura (Bioinformatics and Computational Biology), MQP, 2026. GLOW on Hail: Distributed Computing and Application.

Joining the group

I advise PhD students in the Statistics, Bioinformatics and Computational Biology, and Data Science programs at WPI, master’s students in Applied Statistics and Bioinformatics and Computational Biology, and undergraduates through MQPs, IQPs and independent studies. If our research interests you, email me at zheyangwu@wpi.edu with a short note on your background and what you would like to work on. The Teaching page says how projects run.

Alumni

PhD

  • Shaoming Yin (Data Science), 2026. Innovative Statistical and Computational Methods for Clinical Trials.
  • Shuaichuan Feng (Statistics), 2025. Innovative Statistical Methods for Genetic Data Analysis: Heritability Estimation and Rare Variant Analysis by Discrete P-Value Combination.
  • Ming Liu (Bioinformatics and Computational Biology), 2025. Novel Integrative Analysis of Large Genomic Data.
  • Xiaohui Chen (Statistics), 2023. Novel Statistical Methods for Aggregating Correlated and Missing Data with Applications to Chronic Disease Research.
  • Hong Zhang (Statistics), 2018. Novel P-Value Combination Method for Signal Detection in Large-Scale Data Analysis.

Postdoctoral fellows

  • Tharindu De Alwis, 2023 (co-advised with Fangfang Wang and Oren Mangoubi).
  • Gonzalo Contador, 2019–2022 (co-advised with Jian Zou).
  • Mihnea Stefan Andrei, 2019–2020 (co-advised with Jian Zou).
  • Yevgeniy M. Ptukhin, 2018–2019 (co-advised with Jian Zou).

Master’s theses

  • Yifan Ma (Applied Statistics), 2023. On Sample Size for Improving Prediction Accuracy of Linear Regression Model.
  • Ruosi Zhang (Bioinformatics and Computational Biology), 2019. Simulations of Different P-value Combination Methods Using SNPs at Diverse Biology Levels.
  • Yibo Wu (Bioinformatics and Computational Biology), 2019. Genome Studies of Gene Expression and Alternative Splicing During iPSC Skeletal Muscle Induction and Differentiation.
  • Siqin Li (Bioinformatics and Computational Biology), 2018. Genome Studies of Chromatin Accessibility and Gene Expression during iPSC Skeletal Muscle Induction and Differentiation.
  • Xiaohui Chen (Applied Statistics), 2018. Bahadur Efficiencies for Statistics of Truncated P-Value Combination Methods.
  • Jiadong Fang (Applied Statistics), 2018. Calculating One-sided P-Value for TFisher Under Correlated Data.
  • Xue Li (Bioinformatics and Computational Biology), 2015. Predicting Gene Expression through Integrating Epigenetic Data by Mixed-Effect Model.

Master’s capstone and research projects

  • Wesley Lo (Applied Mathematics), 2024. Contextualized Analysis of Anxiety Phenotypes Using All of Us Data.
  • Usha Appadu (Bioinformatics and Computational Biology), 2024. A comparative analysis of Alzheimer’s Data from All of Us Program Researcher Workbench using Hail and Plink tools.
  • Samuel Berbeco (Applied Statistics), 2023. Testing the Power of the Genomic Burden Test Under Various Weighting Mechanisms.
  • Jingyan Sun (Bioinformatics and Computational Biology), 2020. Incorporating functional information to genetic association detection by GFisher.
  • Xuan Jiang (Applied Statistics), 2018. Comparison of several predictive methods of identifying vulnerable plaque progression.
  • Yifan Zhao (Bioinformatics and Computational Biology), 2017. Understanding the Graphlet Algorithm and Applying it to GWAS Analysis.
  • Shanzhang Nong (Applied Statistics), 2016. The Algorithm and Computation of the Graphlet Screening Procedure.
  • Jun Zhang (Applied Statistics), 2016. Use Linear Mixed Effect Model to Control the Dependence in Gene Expression Prediction.
  • Zhuoying Wang (Applied Statistics), 2015. Apply Orthogonal Matching Pursuit Algorithm to Detection of Missing Heritability.
  • Yijun Zhang (Applied Statistics), 2015. EM Algorithm and Bayesian Method for Protein Motif Identification.
  • Jason Kost (Bioinformatics and Computational Biology), 2015. Exome Sequencing Data Process and Analysis for Amyotrophic Lateral Sclerosis.
  • Leyi Zhang (Applied Statistics), 2014. \(L_0\)-Norm Based Model Selection Strategies for Weak Signal Detection and Gene Hunting.
  • Huaming Sun (Applied Statistics), 2014. Differential gene expression analysis of RNA-seq in Caenorhabditis elegans with Cuffdiff, DESeq2 and DEXSeq.
  • Jing Xuan (Applied Statistics), 2013. Higher Criticism Approach to Detect Rare Variants Using Whole Genome Sequencing Data.
  • Li Yang (Applied Statistics), 2013. Novel SNP-set Methods for Genetic Association Study Using Sequencing Data.
  • Taoye Chen (Applied Statistics), 2013. A Multi-level Model for Analyzing Whole Genome Sequencing Family Data with Longitudinal Traits.
  • Lillian Carrasquillo (Industrial Mathematics), 2012. Hypotension in Sepsis ICU Patients: Predictive Value of Attribute Subsets (co-advised with Natasha Markuzon, Draper Laboratory).
  • Shiquan He (Applied Statistics), 2009. A Review of Linear Regression and Some Basic Proofs for Lasso.
  • Ya Zhang (Applied Statistics), 2009. Pharmaceutical Market Research Based on Statistical Analysis.

Undergraduate projects

  • Peter Howell and Kylie Hoar, MQP, 2024–2025. Distributed Computing for Association Analysis of Whole Genome Sequencing Data. 2025 Provost’s MQP Award.
  • Taya Yakovenko, MQP, 2023–2024. Utilizing Cloud Computing for Whole Genome Sequencing Association Studies.
  • Ethan D. Gouveia, MQP, 2017–2018. Graphlet Feature Selection.
  • Kevin Brian Specht, MQP, 2016–2017. Network Medicine (co-advised with Dmitry Korkin).
  • Joe Brigham, Jiali Gao, Will Lynch and Josh Nottage, MQP, 2014–2015. Credibility Methods in Life and Disability Insurance (sponsor: Unum Group; co-advised with Jon P. Abraham).
  • Dongni Zhang, MQP, 2014. Integrating Protein-Protein Interaction Network into Genetic Association Studies.
  • Yilan Liu, MQP, 2013–2014. GPU-Accelerated Computation for Statistical Analysis of the Next-Generation Sequencing Data.
  • Jacob Peskoe, MQP, 2012. Evaluation of Different Clustering and Classification Algorithms for Continuous and Discrete Data Sets (sponsor and co-advisor: BAE Systems).
  • William Elmore, Tuhina Bhattacharya, Xuyu Qian and Luyang Zhang, IQP, 2011–2012. Impact of new genome technologies.