Archived Events

2/11/26 Seminar: "Highly Adaptive Principal Component Regression: Fast HAL/HAR via Outcome-Blind Kernel PCA"

This week’s seminar brings another thought-provoking discussion! Join us on February 11th to hear from CTML GSR Mingxun (Michael) Wang presenting his talk on "Highly Adaptive Principal Component Regression: Fast HAL/HAR via Outcome-Blind Kernel PCA." The seminar will take place at 12:00 PM in Berkeley Way West, 5th Floor, Room 5401.

Abstract: The Highly Adaptive Lasso (HAL) has strong rate guarantees under minimal smoothness assumptions, but can be computationally prohibitive in moderate to high dimensions due to its...

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

2/4/26 Seminar: "A Conformalized Inference on Unobservable Variables"

We’re pleased to welcome Toru Shirakawa, CTML GSR and CPH PhD Student, to next week’s CTML Seminar on Wednesday, February 4th, presenting on “A Conformalized Inference on Unobservable Variables.” The seminar will take place at 12:00 PM in Berkeley Way West, 5th Floor, Room 5401.

Abstract: Quantifying uncertainty in predicted unobservable variables is a critical area of research in statistics, artificial intelligence, and empirical science. Most scientific studies assume a specific structure involving unobservable...

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...

Seminar 1/28/26: "Improving Precision through Covariate Adjustment in RCTs with Binary Outcomes"

Connect with the CTML community! This week’s seminar on Wednesday, January 28th, will feature CTML GSR Kaitlyn Lee presenting her talk, "Improving Precision through Covariate Adjustment in RCTs with Binary Outcomes." The seminar will take place at 12:00 PM in Berkeley Way West, 5th Floor, Room 5401. Please note that this week’s session will be open exclusively to the CTML and UC Berkeley community.

Abstract: Covariate adjustment is a general method for improving precision when estimating treatment effects in...

Seminar 1/21/26: "Predicting Loss to Follow-Up Under Resource Constraints: Leveraging Registry-Linked Mobile Health Data in Trauma Care"

The CTML Spring Seminar Series kicks off on Wednesday, January 21, with a talk by CTML GSR Andy Kim: “Predicting Loss to Follow-Up Under Resource Constraints: Leveraging Registry-Linked Mobile Health Data in Trauma Care.” Join us at 12:00 PM in Berkeley Way West, 5th Floor, Room 5401.

Abstract: Traumatic injury remains a leading cause of morbidity and mortality in sub-Saharan Africa, with a substantial proportion of adverse outcomes occurring after hospital discharge due to missed follow-up care. Leveraging linked-data from the...

11/12/25 Seminar: "Heterogeneous Net Treatment Effects"

We're pleased to welcome Eva-Maria Oess, CTML Visiting Student Researcher, as the speaker for this week’s CTML Seminar on Wednesday, November 12th. She wil be presenting on "Heterogeneous Net Treatment Effects" joint work with Lennard Maßmann. This talk will take place at 12:00PM at Berkeley Way West, 5th Floor, Room 5401.

We introduce a novel method for estimating heterogeneous net treatment effects under unit-varying outcome...

11/5/25 Seminar: "A Class of TMLEs for Efficient Estimation Under Two-Phase Sampling"

This week’s seminar brings another thought-provoking discussion! Join us on Wednesday, November 5th, as CTML GSR Sky Qiu presents "A Class of TMLEs for Efficient Estimation Under Two-Phase Sampling." This talk will take place at 12:00PM at Berkeley Way West, 5th Floor, Room 5401.

In a typical two-phase design, a random sample is drawn from the target population in phase-1, and partial covariate information is collected. In phase-2, a subsample is selected from the initial sample, and full covariate information...

5/2/25: Biostatistics Research Showcase

Join us for the Biostatistics Research Showcase! The showcase opens with rapid-fire Lightning Talks featuring biostatistics researchers presenting cutting-edge work in causal inference, machine learning, and public health applications. Then, dive deeper into innovative research in statistical methodology and health science during our Poster Session, showcasing projects from across the biostatistics community.

Date: Friday, May 2, 2025
Time: 2:00 PM – 3:00 PM (Lightning Talks) | 3:00 PM – 4:00 PM (Poster Session)

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10/29/25 Seminar: "Targeted Deep Architectures: A TMLE-Based Framework for Robust Causal Inference in Neural Networks"

Continuing our CTML Seminar Series is CTML GSR, Yi Li. His talk, "Targeted Deep Architectures: A TMLE-Based Framework for Robust Causal Inference in Neural Networks" will take place on October 29th at 12:00PM at Berkeley Way West, 5th Floor, Room 5401. You won't want to miss it!

Modern neural networks excel at prediction but often produce biased estimates and unreliable uncertainty for causal target parameters(e.g., average treatment effects or entire survival curves). This talk introduces Targeted Deep...