Erin Gabriel

Professor in Biostatistics,

University of Copenhagen

My research focuses on biostatistical methods development and the proper application of methods to problems in the treatment and prevention of disease.

I am currently working on methodological research in the areas of nonparametric causal bounds, designs and estimation methods for emulated and randomized clinical trials for the evaluation of prediction-based decision rules, and surrogate evaluation. My general statistical areas of interest are in causal inference and randomized trials. Although most of my previous applications have been in infectious disease and vaccination, I have recently started working in common complex diseases.

Education

PhD in Biostatistics, 2012

University of Washington
MS in Economics, 2004

McGill University
BA in Mathematics, 2002

Washington College

Funding

Pioneer Center for SMARTbiomed

Funded by a consortium of Danish foundations
Data Science Ascending Investigator

Novo Nordisk Foundation
Starting Grant

Interdisciplinary Grant

Environment Grant

Vetenskapsrådet
Young Scholar Award

Strategic Funding Area: Epi and Biostatistics

Affiliations

Associate Member

Department of Statistics

University of Oxford

November 2024 – Present Oxford, United Kingdom

Codirector

Pioneer Centre for SMARTbiomed

July 2024 – Present Copenhagen, Denmark

Current Members

Michael C Sachs

Biostatistician working on the development and evaluation of risk prediction models and biomarkers, assay development and validation, statistical computing, causal inference in observational studies, and tools for reproducible research.

Paweł Morzywołek

Assistant Professor working on causal and statistical inference with an emphasis on infinite-dimensional parameters and their applications to understanding common complex diseases.

Alex Markham

Postdoc interested in using perturb-seq data to learn causal graphical models that facilitate reasoning about regulatory pathways underlying common complex diseases.

Zehao Su

Postdoc working on data integration methods for inference on causally interpretable estimands with a special focus on clinical trial data.

Mark Bech Knudsen

PhD student interested in causal inference in time-to-event analysis and settings with lack of identifiability.

Marie Skov Breum

Postdoctoral researcher working on causal inference methods. My current research focuses on mediation analysis and methods for longitudinal data including time-to-event analysis.

Emilie Wessel Pedersen

PhD student developing methods for causal inference on (key features of) heterogeneous effects using efficient targeted nonparametric estimation.

Christoffer Sejling

PhD student working with the development of statistical methods for quantifying clinically relevant traits of continuous glucose monitor measurements from Type I Diabetes patients.