Biostatistics Seminar: Robust methods for meta-analysis of dose-response relationships.
Speaker: Aleksandr Aravkin, PhD, Associate Professor, UW Department of Applied Mathematics; Director, Math Sciences, Institute for Health Metrics and Evaluation; Adjunct Professor, Health Metrics Sciences, Mathematics, Statistics, and Computer Science & Engineering
Presentation: Robust methods for meta-analysis of dose-response relationships.
Abstract: We present the Burden of Proof framework, a set of innovations for meta-analysis to improve estimation of nonlinear dose-response relationships as well as provide additional metrics for broader comparisons of risk-outcome relationships to each other. We discuss technical challenges in modeling nonlinear risks and incorporating reported observations, as well as robust trimming strategies to reduce sensitivity to outliers. Shifting to new metrics and cross-pair comparisons, we define a burden of proof risk function: a quantile of the risk curve that represents a conservative effect size consistent with the available evidence after accounting for uncertainty…
Event interval: Single day event. Campus location: Hans Rosling Center for Population Health (HRC). Campus room: HRC 135. Accessibility Contact: Deb Nelson, nelsod6@uw.edu, 206-685-9323. Event Types: Lectures/Seminars.
Thursday, April 9, 2026, 3:30 PM – 4:30 PM.
General Exam - James Peng
Committee: Peter Gilbert (chair), Pamela Shaw, Linbo Wang, Amy Willis, Thomas Richardson, Lillian Cohn (GSR)
Presentation: Statistical methods for using deep viral sequencing data in HIV-1 prevention trial sieve analyses
Abstract: Human immunodeficiency virus (HIV) exhibits substantial genetic diversity both across individuals and within a single infection, where rapidly evolving viral populations form complex within-host quasispecies. This diversity poses a major challenge for biomedical prevention strategies, as interventions such as vaccines or monoclonal antibodies may protect against some viral variants but not others. Sieve analysis provides a framework for evaluating whether prevention efficacy varies across viral characteristics, offering insight into mechanisms of protection and immune escape.
Recent advances in sequencing technologies have transformed the data available for sieve analysis. Rather than observing a single viral sequence per infected participant, investigators can now observe up to…
Event interval: Single day event. Campus location: Hans Rosling Center for Population Health (HRC). Online Meeting Link: https://washington.zoom.us/j/95825337295. Campus room: HRC 342. Accessibility Contact: Deb Nelson, nelsod6@uw.edu, 206-685-9323. Event Types: Academics.
Friday, April 10, 2026, 1:00 PM – 3:00 PM.
Biostatistics Seminar: Two Approaches for Uncertain Auxiliary Covariates in Two-Phase Study Design and Analysis
Speaker: Osvaldo Espin-Garcia, PhD, Assistant Professor, Epidemiology and Biostatistics, Western University
Presentation: Two Approaches for Uncertain Auxiliary Covariates in Two-Phase Study Design and Analysis
Abstract: The two-phase study is cost-effective way to collect and analyze expensive predictors data by accruing data in two phases. In the phase 1, observed outcomes and/or inexpensive (auxiliary) covariates for all subjects are used to identify a subset of informative subjects for expensive predictor measurement. In the phase 2, all available data are analyzed by leveraging missing data methods.Existing literature implicitly assumes that auxiliary covariates are certain, i.e. are known and well-characterized (e.g. assume a single auxiliary covariate linearly relates to the outcome and/or the expensive predictor), while work on uncertain auxiliary covariates has received little to no attention. Here, I present two approaches that challenge this assumption.
The first one, motivated by…
Event interval: Single day event. Campus room: Online. Accessibility Contact: Deb Nelson, nelsod6@uw.edu, 206-685-9323. Event Types: Lectures/Seminars.
Thursday, April 16, 2026, 3:30 PM – 4:30 PM.
Biostatistics Student-Invited Seminar: Edward Kennedy, PhD, Associate Professor Statistics & Data Science, Carnegie Mellon University
Speaker: Edward Kennedy, PhD, Associate Professor Statistics & Data Science, Carnegie Mellon University
Presentation title and abstract coming soon.
Event interval: Single day event. Campus location: Hans Rosling Center for Population Health (HRC). Campus room: HRC 135. Accessibility Contact: Deb Nelson, nelsod6@uw.edu, 206-685-9323. Event Types: Lectures/Seminars.
Thursday, April 23, 2026, 3:30 PM – 4:30 PM.
Biostatistics Seminar: Kelley Harris, PhD, Associate Professor of Genome Sciences
Speaker: Kelley Harris, PhD, Assistant Professor of Genome Sciences
Presentation title and abstract coming soon.
Event interval: Single day event. Campus location: Hans Rosling Center for Population Health (HRC). Campus room: HRC 135. Accessibility Contact: Deb Nelson, nelsod6@uw.edu, 206-685-9323. Event Types: Lectures/Seminars.
Thursday, April 30, 2026, 3:30 PM – 4:30 PM.
Biostatistics Seminar: Tools for Interpreting Single-Cell Differentiation Trajectories
Speaker: Manu Setty, PhD, Associate Professor, Basic Sciences Division and Herbold Computational Biology Program, Public Health Sciences Division, Fred Hutch Cancer Center
Presentation: Tools for Interpreting Single-Cell Differentiation Trajectories
Abstract: Cellular differentiation unfolds as a continuous process across gene expression and chromatin landscapes, yet many single-cell analysis methods impose discrete categories that obscure the underlying dynamics. We have developed a suite of tools for interpreting differentiation trajectories directly from high-dimensional single-cell measurements: Mellon learns smooth, differentiable density functions over cell-state space using scalable Gaussian processes, capturing both local geometry and global topology of phenotypic landscapes in any single-cell modality. This continuous density representation provides a principled foundation for downstream inference. Kompot builds on this representation to perform differential analysis across conditions and detects…
Event interval: Single day event. Campus location: Hans Rosling Center for Population Health (HRC). Campus room: HRC 135. Accessibility Contact: Deb Nelson, nelsod6@uw.edu, 206-685-9323. Event Types: Lectures/Seminars.
Thursday, May 7, 2026, 3:30 PM – 4:30 PM.
Joint UW Biostatistics/Fred Hutch Seminar: Evaluating Conversational AI for Medical Diagnosis and Management
Speaker: Anil Palepu, PhD, Research Scientist, Google Research
Presentation: Evaluating Conversational AI for Medical Diagnosis and Management
Abstract: The medical interview has been termed “the most powerful, sensitive, and versatile instrument available to the physician.” While Large Language Models (LLMs) have achieved expert-level scores on medical board examinations, these static benchmarks fail to capture the essence of clinical practice: the ability to intelligently and compassionately acquire information under conditions of uncertainty. To bridge this gap, we must evaluate AI through frameworks that mirror the complexity of human practice—most notably the Objective Structured Clinical Examination (OSCE), a validated gold standard for assessing clinical competence in medical trainees.
In this talk, I will discuss AMIE (Articulate Medical Intelligence Explorer), a research program from Google dedicated to developing and robustly evaluating AI capabilities for clinical reasoning and dialogue. Moving…
Event interval: Single day event. Campus room: Fred Hutch Arnold Building, Behnke Suite (M1-A307). Accessibility Contact: Deb Nelson, nelsod6@uw.edu, 206-685-9323. Event Types: Academics.
Thursday, May 21, 2026, 12:00 PM – 1:00 PM.
Biostatistics Seminar: William DeWitt, PhD, Assistant Professor, Genome Sciences, University of Washington
Speaker: William DeWitt, PhD, Assistant Professor, Genome Sciences, University of Washington
Presentation title and abstract coming soon.
Event interval: Single day event. Campus room: HRC 135. Accessibility Contact: Deb Nelson, nelsod6@uw.edu, 206-685-9323. Event Types: Lectures/Seminars.
Thursday, May 28, 2026, 3:30 PM – 4:30 PM.
Biostatistics Seminar: Matheus Viana, PhD, Associate Director, Image Analysis and Descr Modeling, Allen Institute
Speaker: Matheus Viana, PhD, Associate Director, Image Analysis and Descr Modeling, Allen Institute.
Event interval: Single day event. Campus location: Hans Rosling Center for Population Health (HRC). Campus room: HRC 135. Accessibility Contact: Deb Nelson, nelsod6@uw.edu, 206-685-9323. Event Types: Lectures/Seminars.
Thursday, June 4, 2026, 3:30 PM – 4:30 PM.
Causal Inference with Observational Data: Common Designs and Statistical Methods - Summer Institutes Online Short Course
Observational studies are non-interventional empirical investigations of causal effects and are playing an increasingly vital role in healthcare decision making in the era of data science. The study design is particularly important in planning observational studies due to the lack of randomization. Aspects of design include defining the objectives and context under investigation, collecting the right data, and choosing suitable strategies to remove bias from measured and unmeasured confounders. Statistical analysis should also align with the design.
This module covers key concepts and useful methods for designing and analyzing observational studies. The first part of the module will focus on matching and weighting methods for cohort and case-control studies for causal inference. Specific topics include basic tools of matching and weighting, randomization inference, and sensitivity analysis. The second part of the module will focus on methods to address unmeasured confounding via causal exclusion. Specific to…
Event interval: Single day event. Campus room: Online. Accessibility Contact: Deb Nelson, nelsod6@uw.edu, 206-685-9323. Event Types: Workshops. Special Events. Target Audience: Target audiences for this module are: 1. clinical researchers who need to use observational data to.
Tuesday, July 7, 2026, 8:30 AM – 12:00 PM.
For more info visit si.biostat.washington.edu. Design and Analysis of Clinical Trials - Summer Institutes Online Short Course
The design and analysis of a randomized clinical trial involves a series of decisions, including the choice of the primary outcome, sample size, randomization algorithm, interim monitoring plan, and the choice of the primary analysis and estimand of interest. This course will focus on the statistical considerations that inform each of these decisions. Additional topics include addressing multiple comparisons, handling missing data, and whether to consider an adaptive design. We will present a set of simple tools and principles that go a long way towards defining a robust clinical trial design. We will also shed light on some common pitfalls to avoid. Discussions will be driven by examples of trials from a variety of domains including cardiovascular disease, infectious disease (HIV, Ebola, COVID-19), as well as other settings.
We assume enrollees will be familiar with topics taught in introductory statistics (t-tests, regression, confidence intervals, p-values, and a basic understanding of the central limit…
Event interval: Single day event. Campus room: Online. Accessibility Contact: Deb Nelson, nelsod6@uw.edu, 206-685-9323. Event Types: Workshops. Special Events.
Tuesday, July 7, 2026, 8:30 AM – Thursday, July 9, 2026, 12:30 PM.
For more info visit si.biostat.washington.edu.