CTML Events

3/19/25: Biostatistics Career Panel Spring 2025

Join us for our Spring Biostatistics Career Panel! We’re thrilled to bring you a career panel featuring leading figures in biostatistics. Dive into their career stories, explore their research, and their unique perspectives on the field. This is your chance to engage in lively discussions and discover the many exciting paths within biostatistics!

Date: Wednesday, March 19th

Time: 12:00pm - 1:30pm (This event will begin at 12pm sharp)

Location: Berkeley Way West, 5th Fl, Rm 5401

Spring 2025 CTML Seminar Series

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.

CTML Seminar Series - Spring 2025 Syllabus

For accessibility accommodations, please contact Christina Da Silva at...

3/12/25 Seminar: "Surrogate Modeling for Infectious Disease Dynamics Using Machine Learning"

Don't miss the next session of the CTML Seminar Series on March 12th, where Karissa Huang and Philip Lee will discuss "Surrogate Modeling for Infectious Disease Dynamics Using Machine Learning." This talk will take place from 12:00PM-1:00PM at Berkeley Way West, 5th Floor, Room 5401.

Model complexity can often make parameter estimation challenging and inefficient in epidemiological models. In this work we propose a framework for using surrogate models to estimate the likelihood for compartmental models. The surrogate modeling approach reduces the computational costs of analyzing...

Biostatistics Research Social Hour Sponsored by CTML

Date: March 19th, 2025 Time: 1:30 PM - 3:00 PM Location: 2121 Berkeley Way West | 5th Floor Terrace Audience: Open to entire Biostatistics Community

OTMLE Reading Group - Fridays @ 2pm

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...