The Gilbert Group’s research program centers on the statistical design and analysis of vaccine efficacy trials, especially HIV Vaccine Trials Network (HVTN) trials of candidate HIV vaccines, and also trials of candidate vaccines against other genetically-diverse infectious diseases including dengue, malaria, and SARS-CoV-2. The research integrates novel statistical methods with applications, with major application area the assessment of “immune correlates of vaccine protection” including the “sieve analysis” of pathogen sequences infecting trial volunteers, a statistical field that Dr. Gilbert pioneered and led development with colleagues. The novel methods research contributes to general biostatistical fields including competing risks survival analysis, missing data (e.g., two-phase sampling designs), causal inference (e.g., principal stratification and mediation), and the evaluation of surrogate endpoints; the methods focus on robust and efficient techniques including targeted learning methods that integrate machine learning into inferences. Closely connected to its HVTN research on HIV vaccines, the Gilbert Group also focuses on HVTN efficacy trials of broadly neutralizing monoclonal antibodies for prevention of HIV infection, and on COVID-19 Prevention Network (CoVPN) (https://www.coronaviruspreventionnetwork.org/) harmonized phase 3 COVID-19 vaccine efficacy trials. The Gilbert Group conducts the research through extensive collaboration with University of Washington biostatistics doctoral and masters students.