Come join us for our next talk in our seminar series on April 23rd. Joy Nakato, CTML GSR will present her talk on "Efficient estimation of causal effects of HIV prevention and care strategies in clustered data settings." The talk will take place at 12 PM at Berkeley Way West, 5th Floor, Room 5101 (Caravan Room). Please note the room change this week.
In this mock QE talk, I will present ongoing work focused on developing, evaluating, and applying efficient and robust estimators...
Be part of the conversation! On Wednesday, April 16th our CTML Seminar Series welcomes Ellie Matthay, Assistant Professor of Population Health at NYU Grossman School of Medicine. Ellie will present her talk on “Causal Inference Challenges in Research on the Health Effects of Social Policies: Heterogeneous Effects and Treatment-Confounder Feedback.” The talk will take place at 12:00PM at Berkeley Way West, 5th Floor, Room 5401. Speaker will be presenting remotely.
Calling all biostatistics students, postdocs, and staff! Have exciting research to share? The Biostatistics Research Showcase is your chance to present your work to faculty, peers, and special guests! Whether through a lightning talk, a poster, or both, this is your opportunity to showcase your contributions to the field.
Date: Friday, May 2, 2025 Time: 1:00 PM – 4:00 PM Location: Berkeley Way West | Colloquia Room 1102
CTML Seminar Series: Presentations and Resources The following tables provide easy access to presenter information, research topics, and slide decks, making it a valuable resource for all members of the CTML community and anyone interested in the forefront of scientific inquiry.
Starting January 24th, the OTMLE (Optimal Transport and Targeted Maximum Likelihood Estimation) reading group will further investigate the geometry of probability spaces and the implications for TMLE’s structure and behavior. Topics include deeper explorations of how optimal transport’s spatial and dynamic properties provide insights into likelihood-based optimization and its role in semiparametric models. Rather than diving into specific optimization techniques like natural gradient descent or Newton’s method, this semester focuses on laying the theoretical groundwork for...
