Biostatistics Student-Invited Speaker: Minimax optimal causal inference in high dimensions
Speaker: Edward Kennedy, PhD, Associate Professor Statistics & Data Science, Carnegie Mellon University
Presentation: Minimax optimal causal inference in high dimensions
Abstract: In this talk I survey recent work on causal inference in complex yet common settings with high-dimensional confounders, treatments, or outcomes. First we consider high-dimensional discrete confounders, where popular assumptions like sparsity and smoothness do not apply. We give new error bounds for standard estimators and show they are unimprovable in a minimax sense, illustrating fundamental limits of high-dimensional confounding adjustment. We then study the role of effect homogeneity and knowledge of the covariate distribution, showing how this additional structure can mitigate the curse of dimensionality and allow for faster convergence rates. Next we study high-dimensional treatments (both multi- and vector-valued), which bring distinct complications, such as high-dimensional target parameters and positivity violations. We…
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.
Mini Symposium on Genetic Epidemiology and Population Genetic Screening
The Institute for Public Health Genetics is hosting a mini symposium on genetic epidemiology and population screening! Events include a seminar with Dr. Stella Aslibekyan of the new 23andMe Research Institute (1-2:30 p.m.), a panel discussion on Population Genetic Screening opportunities and controversies (2:30-4 p.m.), and a networking reception (4-4:30 p.m.).
Panel discussion is hosted by Dr. Liz Blue and includes Drs. Stella Aslibekyan (23andMe Research Institute), Sarah Knerr (UW Department of Health Systems and Population Health), Brad Rolf (UW Genetic Counseling), and Nini Shridhar (WA Department of Health Genomic Services).
Please RSVP no later than Wednesday, April 22, 2026.
Event interval: Single day event. Campus location: South Campus Center (SOCC). Campus room: SOCC 316. Accessibility Contact: Alison Fohner, phgallfac@u.washington.edu. Event Types: Conferences.
Tuesday, April 28, 2026, 1:00 PM – 4:30 PM.
Biostatistics Seminar: Germline mutation rate modifers are conspicuously absent from 200,000 UK Biobank whole genomes
Speaker: Kelley Harris, PhD, Associate Professor of Genome Sciences
Presentation: Germline mutation rate modifers are conspicuously absent from 200,000 UK Biobank whole genomes
Abstract: Most studies of human mutation rate variation rely on whole-genome sequencing of parent-offspring trios. These studies find that most variation is random or driven by parental age, with only a small proportion attributable to genetic effects. However, because trio sequencing is expensive, such studies are typically smaller than state-of-the-art GWAS and only well powered to detect large-effect modifiers that increase the mutation rate by two-fold or more. To overcome this limitation, we developed a method that detects mutation rate modifiers using long IBD haplotypes shared between distant cousins in population biobanks. Applying this method to DNA repair gene variation in 200,000 UK Biobank whole genomes, we demonstrate power to detect modifier alleles that raise the mutation rate by as little as 10%, provided they are…
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.
Industry Interview Session | Tackling Technical Questions
Join Noah Simon, PhD (former department faculty) next Friday for a practical session on acing industry interviews. Noah will focus on technical interviews and how to handle questions you don’t know the answer to. Those applying, or planning to apply, to jobs and internships soon will find this session helpful.
Please register here to receive the zoom link: https://washington.zoom.us/meeting/register/Kw8t40B2RNeE6g37Ow5A5g.
Event interval: Single day event. Campus room: Zoom. Accessibility Contact: Maggie Tarnawa. Event Types: Information Sessions. Target Audience: Biostatistics students and alumni.
Friday, May 1, 2026, 3:00 PM – 4:00 PM.
Zoom.
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. Introduction to Survival Analysis - Summer Institutes Online Short Course
Time-to-event data are common in biomedical research and present unique challenges for analysis, given many subjects under study will not experience the event of interest. After outlining the basic structure of survival data, we will the cover the key methods for survival analysis including Kaplan Meier survival curves; the log-rank test and alternative testing procedures for group comparisons; and the Cox proportional hazards model. Analytical approaches for survival data with competing risks will also be introduced. Emphasis in this module will be on the practical application of these methods, with illustrative examples from medical and public health research being used throughout. Examples will feature best practices for reporting of results and analysis pitfalls to avoid. As time allows, we will consider concepts and controversies for survival analysis estimands and fundamental issues for study design and power. All examples will be conducted using R.
Event interval: Single day event. Campus room: Online. Accessibility Contact: Deb Nelson, nelsod6@uw.edu, 206-685-9323. Event Types: Special Events. Workshops.
Thursday, July 9, 2026, 1:00 PM – Friday, July 10, 2026, 4:30 PM.
For more info visit si.biostat.washington.edu. Topics in Clinical Trials: Issues in Non-Inferiority Trials and Addressing Missing Data - Online Short Course
Over the past 7 decades, the randomized clinical trial (RCT) has become the gold standard for evaluation of new drugs, biologics, devices, procedures, and behavioral interventions. In a half-day short course, two critically important topics will be discussed that have broad implications in the design and conduct of clinical trials: the Design of Non-Inferiority Trials and the Prevention of Missing Data.
Event interval: Single day event. Campus room: Online. Accessibility Contact: Deb Nelson, nelsod6@uw.edu, 206-685-9323. Event Types: Workshops. Special Events.
Friday, July 10, 2026, 8:30 AM – 12:00 PM.
For more info visit si.biostat.washington.edu. Data Wrangling with R - Summer Institutes Online Short Course
Participants will learn how to prepare and process data, a key step prior to visualization and statistical analysis. Our approach focuses on the concept of creating “tidy data” e.g. data that is organized into readable and distributable files. In this module, we will: Use hands-on examples covering concepts on data retrieval, cleaning, manipulation, and formatting. , Touch on reproducible research using R Markdown and collaborative code sharing using GitHub.
Some familiarity with R is needed for this module.
Event interval: Single day event. Campus room: Online. Accessibility Contact: Deb Nelson, nelsod6@uw.edu, 206-685-9323. Event Types: Workshops. Special Events.
Monday, July 13, 2026, 8:00 AM – Wednesday, July 15, 2026, 2:30 PM.
For more info visit si.biostat.washington.edu. Generalized Estimating Equations and Mixed-Effects Models for Longitudinal Data Analysis - Summer Institutes Online Short Course
Longitudinal studies follow individuals over time and repeatedly measure health status, which facilitates prospective ascertainment of exposures and incident outcomes, and identification of changes over time within individuals. Analyses of longitudinal data must account for the correlation that arises from collecting repeated measures on the same individuals over time.
This module will introduce statistical methods for the analysis of longitudinal data, with a focus on marginal (or, population-averaged) models fit via generalized estimating equations and conditional (or, subject-specific) models fit via generalized linear mixed-effects models. Relevant theoretical background will be provided. Illustrative examples and interactive activities (conducted in R) will be used to practice analysis approaches, modeling strategies, and interpretation of results.
This course is targeted toward individuals with little or no prior experience with statistical methods for longitudinal data analysis. Experience with using…
Event interval: Single day event. Campus room: Online. Accessibility Contact: Deb Nelson, nelsod6@uw.edu, 206-685-9323. Event Types: Workshops. Special Events.
Monday, July 13, 2026, 8:30 AM – Wednesday, July 15, 2026, 12:00 PM.
For more info visit si.biostat.washington.edu. Multi-state Models for Time-to-Event Data, with Applications to Clinical Research - Summer Online Short Course
Course description coming soon.
Event interval: Single day event. Campus room: Online. Accessibility Contact: Deb Nelson, nelsod6@uw.edu, 206-685-9323. Event Types: Workshops. Special Events.
Monday, July 13, 2026, 8:30 AM – Wednesday, July 15, 2026, 12:00 PM.
For more info visit si.biostat.washington.edu. Design and Analysis of Two-Phase Studies - Summer Institutes Online Short Course
Researchers often need to measure new variables, or validate existing measurements. Doing this for a whole cohort or database can be prohibitively expensive, so techniques are needed for choosing good subsamples and analyzing them efficiently. This module will give both a conceptual and practical introduction to planning and analyzing modern two-phase study designs. We will cover efficient weighted estimation using the whole cohort, and the optimal design and allocation of subsamples. Exercises will focus on practical aspects of implementing methods using the R survey package.
Open configuration options.
Event interval: Single day event. Campus room: Online. Accessibility Contact: Deb Nelson, nelsod6@uw.edu, 206-685-9323. Event Types: Workshops. Special Events.
Wednesday, July 15, 2026, 1:00 PM – Thursday, July 16, 2026, 4:30 PM.
For more info visit si.biostat.washington.edu. Joint Modeling of Longitudinal and Survival Data - Summer Institutes Online Short Course
Longitudinal studies follow individuals over time and repeatedly measure health status. Analyses of longitudinal data are often complicated by several factors that can threaten the validity of standard analysis methods. First, missing data in longitudinal outcomes can arise when individuals are lost to follow-up, either due to drop-out (e.g. in randomized trails) or death (e.g. in long-term observational studies). Second, when modeling intermittently measured time-dependent covariates in a survival analysis, biological variation can lead to measurement error. Joint modeling of longitudinal and survival outcomes has emerged as a novel approach to handle these issues.
We will detail the use of mixed-effects models for the analysis of repeated longitudinal measures, Cox regression models for the analysis of event-time outcomes with longitudinal measures as time-dependent covariates, and their combination in a joint modeling framework. An in-depth data analysis (conducted in R) will be used to discuss analysis…
Event interval: Single day event. Campus room: Online. Accessibility Contact: Deb Nelson, nelsod6@uw.edu, 206-685-9323. Event Types: Workshops. Special Events.
Thursday, July 16, 2026, 8:30 AM – Friday, July 17, 2026, 12:00 PM.
For more info visit si.biostat.washington.edu.