Archived Events

3/12/24 The Latest in Public Health Research Series: "Preventive Interventions for Long COVID"

Date and Time: Tuesday, March 12 | 12:10 PM

Location: Online | Pre-register for the zoom link HERE(link is external)

CTML Guest Speaker: ...

3/6/24 - 3/9/24 ISBS Symposium

ISBS Symposium

Date(s): Wednesday, March 6 - Saturday, March 9

Location: Hilton Baltimore Inner Harbor, Maryland, USA

CTML Guest Speaker(s): Mark van der Laan, Ph.D., Susan Gruber, Ph.D. (CTML Alum),...

4/11/24 CAMSE/CLIMB Mini-Conference

Date and Time: Thursday, April 11| 1:30 – 5:30 PM

Location: 250 Sutardja Dai Hall, 2594 Hearst Ave, Berkeley, CA 94720, USA

CTML Guest Speaker: Alejandro Schuler, Ph.D.

Alejandro will be presenting his project on "Lassoed Tree Boosting," click on the link here for further information on his publication:...

4/9/24 Seminar: "Evaluating Preventive Interventions for Long COVID Through Targeted Machine Learning"

Join us next week to hear a talk from Zach Butzin-Dozier in our CTMLSpring 2024 Seminar Series. His talk on "Evaluating Preventive Interventions for Long COVID Through Targeted Machine Learning" will take place on April 9 at 12 PM.“In this presentation, I will discuss two studies that applied a Targeted Machine Learning approach to data from N3C. First, I will present our findings from the Long COVID Computational Challenge,...

3/14/24 Join us for Big Give 2024!

The Center for Targeted Machine Learning and Causal Inference (CTML) at UC Berkeley is a vibrant hub where students from different disciplines come together to push the boundaries of public health and clinical medicine research. With over 15 Graduate Student Researchers (GSR), CTML is at the forefront of blending statistical theory with the latest in machine learning and causal inference to create strong, evidence-based advancements in health research. CTML GSRs have led projects on novel methods on the integration of observational and randomized data, on targeted learning treatment...

10/24/23 Seminar: Causal Inference and LLMs: A New Frontier

You can find a recording of Dr. Kiciman's Talk here.

Dr. Emre Kiciman, Senior Principal Researcher at Microsoft Research, gave insightful and timely seminar on causal inference and large language models (LLMs) and the larger impacts, followed by an engaging discussion.

This seminar is co-presented by the Center for Targeted Machine Learning and Causal Inference (CTML) at UC Berkeley, and Computational Precision Health.

Abstract: The...