Epidemiology & Biostatistics

The Wesley Tansey Lab

Research

Wesley Tansey
Wesley Tansey, PhD

The Tansey lab focuses on solving frontier problems in cancer data science through the development of innovative statistical machine learning methods. How do we discover effective combination therapies when the search space of possible combinations is vast? Are there patterns of spatial architecture in the tumor microenvironment that predict whether a patient will respond to a specific therapy? How do we build powerful-yet-interpretable multimodal models of medical images, laboratory tests, and clinical records that can inform and improve treatment decisions in the clinic? The goal of our lab is to distill these kinds of important scientific questions into precise mathematical statements, then derive answers in the form of computationally efficient and statistically principled methods. We are interested in a number of areas in statistics and computer science, including graphical models, Bayesian methods, deep learning, hypothesis testing, conditional density estimation, spatial statistics, active learning, and causal inference. Ultimately, we seek to lay the statistical and computational foundations necessary to deliver on the promise of precision medicine: delivering the right treatment, for the right patient, at the right moment, and at the right dose.

The Wesley Tansey Lab

Publications Highlights

Zhang H, Hunter MV, Chou J, Quinn JF, Zhou M, White RM, Tansey W. BayesTME: An end-to-end method for multiscale spatial transcriptional profiling of the tissue microenvironment. Cell Syst. 2023 Jul 19;14(7):605-619.e7. doi: 10.1016/j.cels.2023.06.003. PMID: 37473731; PMCID: PMC10368078.

Freeman BA, Jaro S, Park T, Keene S, Tansey W, Reznik E. MIRTH: Metabolite Imputation via Rank-Transformation and Harmonization. Genome Biol. 2022 Sep 1;23(1):184. doi: 10.1186/s13059-022-02738-3. PMID: 36050754; PMCID: PMC9438248.

Tansey W, Li K, Zhang H, Linderman SW, Rabadan R, Blei DM, Wiggins CH. Dose-response modeling in high-throughput cancer drug screenings: an end-to-end approach. Biostatistics. 2022 Apr 13;23(2):643-665. doi: 10.1093/biostatistics/kxaa047. PMID: 33417699; PMCID: PMC9007438.

Sudarshan M, Tansey W, Ranganath R. Deep direct likelihood knockoffsAdv Neural Inf Process Syst. 2020 Dec;33:5036-5046. PMID: 33953523; PMCID: PMC8096517.

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People

Wesley Tansey

Wesley Tansey, PhD

  • The Tansey lab focuses on solving frontier problems in cancer data science through the development of innovative statistical machine learning methods.
  • PhD in Computer Science, University of Texas at Austin
[email protected]
Email Address
646-608-7669
Office Phone

Members

Bektas
Ayyüce Begüm Bektaş

Research Fellow

Jacqueline Chou

PhD student in Physiology, Biophysics, and Systems Biology at Weill Cornell Medical College

Thomas Dougherty

PhD Student

Karl Pichotta
Karl Pichotta

MSK MIND Scholar

Jeffrey Quinn
Jeffrey Quinn

Bioinformatics Engineer IV

Christopher Tosh
Christopher Tosh

Associate Research Scientist

Jessica White
Jessica White

PhD student in the Tri-Institutional Program for Computational Biology and Medicine

Amy Xie
Amy Xie

PhD student in the BCMB Allied Program in the Graduate School of Weill Cornell

Haoran Zhang
Haoran Zhang

PhD student in Computer Science at the University of Texas at Austin

Lab Alumni
Casey Bradshaw
Casey Bradshaw

PhD student in Statistics at Columbia University

Shounak Chattopadhyay
Shounak Chattopadhyay

PhD student in Statistics at Duke University

Mauricio Garcia Tec
Mauricio Garcia Tec

PhD student in Statistics and Data Sciences at the University of Texas at Austin

Brian Manzo
Brian Manzo

PhD student in Statistics at University of Michigan

Lab Affiliations

Open Positions

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Disclosures

Doctors and faculty members often work with pharmaceutical, device, biotechnology, and life sciences companies, and other organizations outside of MSK, to find safe and effective cancer treatments, to improve patient care, and to educate the health care community.

MSK requires doctors and faculty members to report (“disclose”) the relationships and financial interests they have with external entities. As a commitment to transparency with our community, we make that information available to the public.

Wesley Tansey discloses the following relationships and financial interests:

No disclosures meeting criteria for time period


The information published here is for a specific annual disclosure period. There may be differences between information on this and other public sites as a result of different reporting periods and/or the various ways relationships and financial interests are categorized by organizations that publish such data.


This page and data include information for a specific MSK annual disclosure period (January 1, 2022 through disclosure submission in spring 2023). This data reflects interests that may or may not still exist. This data is updated annually.

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