Haoyu Zhang

Haoyu Zhang

Earl Stadtman tenure-track investigator

National Cancer Institute

About

Welcome to my homepage! My name is Haoyu Zhang, and I am currently an Earl Stadtman tenure-track investigator at National Cancer Institute, Division of Cancer Epidemiology and Genetics. My lab focuses on developing scalable statistical methods and software to analyze large-scale multi-ancestry genetic data to address questions related to health disparities and to advance genetic research in diverse populations. Real-world challenges drive the majority of methodology projects. The lab works closely with several large genetic consortia, including the Breast Cancer Association Consortium (BCAC), the Polygenic Risk Method in Diverse Populations Consortium (PRIMED), and the International Lung Cancer Consortium (ILCCO). I am looking for postdocs and students to work on fascinating research topics. If you are interested, please email me.

I received postdoc training in the Department of Biostatistics at Harvard T.H. Chan School of Public Health working with Xihong Lin. I received my Ph.D. from the Department of Biostatistics at Johns Hopkins Bloomberg School of Public Health under the guidance of Nilanjan Chatterjee and Ni Zhao. I also received the graduate student fellowship from National Cancer Institute under the guidance of Montserrat García-Closas.

Interests
  • Statistical Genetics
  • Risk Prediction
  • Causal Inference
  • Machine Learning
Education
  • PhD in Biostatistics, 2019

    Johns Hopkins University

  • BS in Statistics, 2014

    Zhejiang University

Overview of Research

The current large data era provides unprecedented opportunities to understand human diseases, identify drug targets and develop personalized therapies. I am very excited to work on cutting-edge statistical methodologies and software for all kinds of data-driven problems to improve human health. My primary goal is to become a leading interdisciplinary researcher studying diverse populations and reducing health disparities in genetic research, with expertise in scalable statistical methods for analyzing multi-ethnic genetic and biobank data, advanced knowledge of underlying genetic architectures of complex traits and diseases.


Multi-anestry polygenic risk predictions

Multi-anestry polygenic risk predictions

Polygenic risk scores are useful for predicting various phenotypes; however, most PRS are developed using predominately European ancestry data, their performance in non-European populations is often poorer. To improve PRS performance in non-European populations, we propose a new method, which takes advantage of both existing large GWAS from European populations and smaller GWAS from non-European populations.

Robust Mendelian randomization methods incorporating weak and correlated instruments

Robust Mendelian randomization methods incorporating weak and correlated instruments

Mendelian randomization (MR) is a major tool to test the causal association between risk factors and disease using genetic variants as instrumental variables.MR makes several strong assumptions, which can be violated in practice and lead to biased estimates and statistical inference. We develop a robust and powerful MR method requiring weaker and more realistic assumptions.

Testing for genetic association association and building risk prediction models for cancer incorporating tumor characteristics

Testing for genetic association association and building risk prediction models for cancer incorporating tumor characteristics

Breast cancer represents a heterogeneous group of diseases with different molecular and clinical features. Thus, clarifying potential heterogeneous associations between genes and disease subtypes offers a tremendous opportunity to characterize distinct etiological pathways. I proposed several new computational and statistical approaches to develop powerful genetic associations tests.

Scientific collaborations

Scientific collaborations

As a statistician and data scientist, I sincerely believe collaborations across disciplines are critical to scientific discovery and methodology development. I participated in broad research collaborations, including genetic association analysis for gall bladder cancer, effect-size distribution analysis for fourteen cancers, gene-environment interaction testing, risk factor analysis for bladder cancer, etc.

Talks & Posters

Quantifying the transmission dynamics of COVID-19 using U.S. states and county level data

Quantifying the transmission dynamics of COVID-19 using U.S. states and county level data

Methods for developing ancestry specific polygenic risk scores

Robust Mendelian randomization analysis with weak instruments

A mixed-model approach for powerful testing of genetic associations with cancer risk incorporating tumor characteristics

Teaching

Lab instructor for Statistical Methods in Public Health II-III (Biostat 622-623)
Lab Instructor for Statistical Methods in Public Health II-III (Biostat 622-623)
Teaching Assistnat for Statistical Methods in Public Health I-IV (Biostat 621-624)
Teaching Assistnat for Statistical Theory I-IV (Biostat 731-734)
Teaching Assistnat for Survey Methodology

Grants & Fellowship

K99/R00 NCI Pathway to Independence Award
Methods for Mendelian randomization and mediation analysis using integrative genetic and genomic data for breast cancer. (Role: PI)

Experience

 
 
 
 
 
Postdoral fellow
Aug 2019 – Present Boston, MA, USA
 
 
 
 
 
Special volunteer
Aug 2019 – Present Rockville, MD, USA
 
 
 
 
 
Pre-doctoral fellow
Jul 2017 – May 2019 Rockville, MD, USA
 
 
 
 
 
Research assistant
Oct 2015 – May 2019 Baltimore, MD, USA
 
 
 
 
 
Research assistant
Jul 2013 – Sep 2013 New Haven, CA, USA
 
 
 
 
 
Research assistant
Jul 2012 – Aug 2012 Brisbane, Australia
 
 
 
 
 
Volunteer
Sharadadevi Gramudyog Utpadak Mandali Ltd (SGS)
Jun 2011 – Aug 2011 Baroda, India

Hobby

🏃
Running

Aim to qualify for Boston marathon in 2025

🏀
Basketball

Fan of Miami Heat!

🎮
Gaming

Monster Hunter World, Civiliation 6, NBA 2K

🚣‍♂️
Dragon boat

Member of dragonboat team

⛰️
Hiking
♥️
Poker

Texas Holdem, Shengji, Mahjong