Nilanjan

Nilanjan Chatterjee, PhD

Bloomberg Distinguished Professor

Department of Biostatistics, Bloomberg School of Public Health Department of Oncology, School of Medicine

Johns Hopkins University


Contact:
Johns Hopkins Bloomberg School of Public Health
Department of Biostatistics
615 N Wolfe Street
Baltimore, MD 21205
Phone: 410-502-8971
Fax: 410-955-0958
E-Mail: nilanjan@jhu.edu

Administrative Coordinator:
Kim Clay
Phone:  410-955-3067
Email:  kphilpo3@jhmi.edu

People

  • Kim Clay

    Administrative Coordinator to Nilanjan Chatterjee, PhD
    Bloomberg Distinguished Professor
    Johns Hopkins University
    Bloomberg School of Public Health
    Department of Biostatistics

    kphilpo3@jhmi.edu
    (Phone) 410-955-3067


    Advisees

  • Yuzheng Dun
    y3Yuzheng Dun is a second-year Ph.D. student in the Department of Biostatistics at Johns Hopkins University. He received his Bachelor's degree in statistics from Huazhong University of Science and Technology. He is interested in Bayesian statistics, statistical computing, and statistical genetics. Currently, I am working on developing statistical methods for multi-ethnic polygenetic risk score.


     

  • Wenxuan Lu
    WenxuanI am a second-year PhD student in the Department of Biostatistics at the Johns Hopkins Bloomberg School of Public Health, where I am advised by Dr. Nilanjan Chatterjee. Before starting my PhD, I earned a B.S. in Applied Mathematics and Statistics, with a second major in Computer Science, from the Johns Hopkins Whiting School of Engineering. My research interests focus on the development and application of statistical methods and computational tools for genetic risk prediction across diverse populations. My current project involves conducting genome-wide association studies (GWAS) in admixed populations by integrating GWAS summary statistics with individual-level data. Additionally, I am exploring methods that leverage functional annotations to enhance the performance and portability of polygenic risk scores (PRSs). My goal is to apply and adapt existing statistical methods to contribute to the development of more precise and equitable healthcare solutions.


     

  • Yujie (Phyllis) Wei
    phyllisYujie (Phyllis) Wei is a Ph.D. student in Biostatistics at Johns Hopkins University. At Chatterjee lab, she hopes to develop methods to help understand the genetic basis of complex traits and diseases and enhance disease risk prediction models through data integration. She received her bachelor's degree in Mathematics with a minor in Computer Science from Wellesley College.


     

  • Ziqiao Wang
    ziqiaoI am a postdoctoral fellow in Dr. Chatterjee’s lab. I want to find out the mechanisms behind complex human diseases using genetics and genomics data. Specifically, I currently focus on improving the interpretability and applicability of polygenic scores. My research include developing novel statistical methods to jointly estimate gene-environment interactions and correlations in case-control studies, and methods for direct and indirect polygenic effects and GxE interactions in family-based studies. My work also involves the integration of genetics with multi-omics data. Apart from being at my desk in the office, you can also find me in ballet studios. Here is my website: https://ziqiaow.github.io/


     

  • Brian Guo
    BrianGaoXinyu (Brian) Guo is an ScM student in the Department of Biostatistics at Johns Hopkins University. He obtained his Bachelor’s degree from Washington University in St. Louis. His current research with Nilanjan Chatterjee focuses on integrating the single-cell data with results from genetic studies to understand cell-type-specific effects on diseases. He also developed a subset-based method to detect associations between tissue-set and complex traits. His research interests include genetics and genomics data integration, statistical learning, and genomic reasoning in cancer biology.


     

  • Anagh Chattopahhayay
    AnaghI am currently a second-year Ph.D. candidate in the Department of Biostatistics, working with Professors Nilanjan Chatterjee and Elizabeth Ogburn, and my primary research interests are Statistical Genetics, Causal Inference, and Machine Learning. I also have a keen interest in the intersection of Health and Linguistics, exploring how language can influence health outcomes, which I pursue as a hobby. Before beginning my doctoral studies, I completed both my Bachelor’s (BStat) and Master’s (MStat) degrees in Statistics at the Indian Statistical Institute, in 2021 and 2023, respectively. For those interested in connecting, my website at anaghchattopadhyay.github.ioM.


     

  • Emily Norton
    AnaghEmily is a third year Ph.D. candidate in Biostatistics. Her research focuses on building better risk prediction models that may ultimately inform clinical decision-making to promote precision prevention equitably across diverse populations. She currently works on building and validating cancer risk prediction models using very large and diverse datasets in order to combine classical risk factors (e.g. age, sex, lifestyle, environment, etc.) and polygenic risk scores into a single model. To support this work, she will also validate new and existing transfer learning techniques - methods that are applied when large data gaps exist - to facilitate combining information across many different data sources. Outside of research, Emily enjoys swing dancing, camping, and crafting.


     

  • Charissa Luk
    AnaghCharissa is a junior studying biomedical engineering and computer science. She is interested in using data-driven methods to find solutions to complex biomedical problems. Her research aims to analyze large datasets to uncover insights into disease pathways and improve health outcomes.


     

  • Sameer Gabbita
    AnaghHi! I’m Sameer, a sophomore at Johns Hopkins from Northern Virginia majoring in biomedical engineering. I am interested in applying AI and statistical methods to study the function of regulatory elements in the genome and genetic variation.
  • Alumni

    Diptavo Dutta

    Post-doctoral Fellow (2019-2022), Current Position: Earl Stadtman Investigator, Division of Cancer Epidemiology and Genetics,National Cancer Institute.

    Jin Jin

    Post-doctoral Fellow (2019-2022) - NIH K99-ROO pathway to independence award winner, Current position: Assistant Professor, Division of Biostatistics and Epidemiology, University of Pennsylvania

    Projenjit Kundu

    PhD Student (2016-2020), Post-doctoral Fellow (2020-2023), Current position: Research Scientist, Pfeizer Inc.


    Jingning Zhang

    PhD Student (2019-2023), Current position: Assistant Manager, Statistical Genetics, Regeneron Inc.

    Martina Fu

    PhD Student (2020-2024), Current position: Post-doctoral Fellow, Stanford University

    Ruzhang Zhao

    PhD Student (2020-2024), Current position: TBA


    Parichoy Pal Choudhury

    Post-doctoral Fellow (2016-2019), Current Position: Principal Scientist, American Cancer Society

    Haoyu Zhang

    PhD Student (2015-2019), Current position: Earl Stadtman Investigator, Division of Cancer Epidemiology and Genetics, National Cancer Institute

    Dora Zhang

    Post-doctoral Fellow (2016-2019), Current position: Assistant Professor, The University of Hongkong


    Zhi Yu, BM, PhD

    PhD student (2017-2020), Current Position: Assistant Professor, Mass General Hospital and Harvard Medical School

    Allison Meisner, PhD

    Post-doctoral Fellow, 2018-2020, Current Position: Assistant Member, Fred Hutchinson Cancer Research Center

    Kayode Sosina, PhD

    PhD Student, 2017-2020, Current Position: Geneticist, Regeneron Pharmaceutical


    Guanghao Qi, PhD

    PhD Student, 2017-2020, Current Position: Assistant Professor, Department of Biostatistics, University of Washington, Seattle

    Batel Blatcher, PhD

    PhD Student, 2018-2021, Current Position: Post-doctoral Fellow,  National Cancer Institute

    Arkojyoti Saha, PhD

    PhD Student, 2018-2021, Current Position: Assistant Professor, Department of Statistics, University of California, Riverside


  • Undergraduate Interns, Research Assistants and Volunteers

    Tad Berkeley

    Tad Berkery is an undergraduate at Johns Hopkins University majoring in Computer Science and Economics. He primarily focuses on designing and implementing software and web applications that enable the public to make use of models originating in the lab. Outside of the lab, Tad also does research with the JHU Sports Analytics Research Group and is the published author of What’s the “Right” Career?

    Yuqi Zhang

    Yuqi Zhang is an undergraduate student at Johns Hopkins University. She is a double major in Biomedical Engineering and Computer Science. Part of her research is on community-level COVID mortality risk and identifying COVID infection risk factors. She also works on polygenic risk score calculation for predicting psychological diseases in the African Ancestry.