Fall 2026 Seminar Series

Center for Targeted Machine Learning and Causal Inference (CTML) Seminar Series

The CTML Seminar Series is a weekly, one-hour seminar held during the Fall and Spring semesters. The series serves as a central forum for CTML researchers to share ideas, discuss emerging work, and foster collaboration. Our goal is to empower every CTML researcher to become a skilled, confident presenter and leader. Through the seminar series, we support the professional development of our trainees by providing opportunities to communicate their research, receive constructive feedback, engage in scholarly discussion, and develop a deeper understanding of the broader research landscape.

Our Objectives

  • Build a welcoming environment where everyone is respected.

  • Promote curiosity and active learning through questions.

  • Offer constructive feedback to support and improve our speakers.

Check out our Fall 2026 CTML Seminar Series Syllabus!

For accessibility accommodations, please contact Christina Da Silva at cdasilva@berkeley.edu.

CTML Seminar Presenters

Ongoing Seminar Series

Fall 2026 CTML Seminar Series

PresenterResearch TopicsLink to ContentDate/Time
Anna Kathrin Menacher (Novo Nordisk)  

12-1PM,

Wed, Sept. 2

Yilong Hou (CTML GSR)  

11AM-12PM,

Thurs, Sept. 10

Jonas Knecht (CPH PhD Student & CTML Visiting Researcher)

12-1PM,

Wed, Sept. 16

Workshop by Alejandro Schuler (CTML Faculty)

Claude Code for Biostatistics Research

12-1PM,

Wed, Sept. 23

Jonathan Levy (Pharvaris)

12-1PM,

Wed, Sept. 30

Zachary Butzin-Dozier (Stanford University School of Medicine)

12-1PM,

Wed, Oct. 7

Andy Kim (CTML GSR)

12-1PM,

Wed, Oct. 21

 Tianyue Zhou (CTML GSR)

12-1PM,

Wed, Oct. 28

Joy Nakato (CTML GSR)

12-1PM,

Wed, Nov. 4

Kaitlyn Lee (CTML GSR)

12-1PM,

Tues, Nov. 10

Nolan Gunter (CTML GSR)

12-1PM,

Wed, Nov. 18

 Ivan Diaz (NYU Grossman School of Medicine)

12-1PM,

Wed, Dec. 2

Past CTML Seminar Series

Spring 2026 CTML Seminar Series

PresenterResearch TopicsLink to ContentDate/Time
Andy Kim Predicting Loss to Follow-Up Under Resource Constraints: Leveraging Registry-Linked Mobile Health Data in Trauma Care  

12-1PM,

Jan. 21

Kaitlyn Lee Improving Precision through Covariate Adjustment in RCTs with Binary Outcomes  

12-1PM,

Jan. 28

Toru Shirakawa

A Conformalized Inference on Unobservable Variables

12-1PM,

Feb. 4

Michael Wang

Highly Adaptive Principal Component Regression: Fast HAL/HAR via Outcome-Blind Kernel PCA

Slides | Video

12-1PM,

Feb. 11

Workshop by Alejandro Schuler 

Simulations Done Right

Slides | Video

12-1PM,

Feb. 18

Andrew Mertens

Spatial Superlearner for Subnational Micronutrient Deficiency Prediction and Proxy Identification in Data-sparse Settings

Slides | Video

12-1PM,

Feb. 25

Alissa Gordon

Average Mixed Derivative: A Nonparametric Framework of Interactivity

12-1PM,

Mar. 4

 Tianyue Zhou & Toru Shirakawa

Tianyue: Generating High-Quality Real-World Evidence at Scale with a Causal Roadmap Copilot

Toru: Survival Deep LTMLE with an Application to Longitudinal Chronic Disease Management

12-1PM,

Mar. 11

Marie Charpignon

Emulation of the ACORN RCT Using Observational Data from a Large Integrated Health System in California

12-1PM,

Mar. 18

Kirsten Landsiedel

Longitudinal Targeted Maximum Likelihood Estimation for Two-Stage Designs

12-1PM,

Apr. 1

Biostat & Epi Career Panel

Chair: Laura Balzer

Panelists: Courtney Schiffman, Milena Gianfrancesco, Lauren Dang, and Lina Montoya

We invite you to a dynamic career panel featuring distinguished biostatistics and epidemiology professionals who will share their research expertise, career stories, and unique perspectives on the field.

12-1:30PM,

Apr. 8

 Nolan Gunter

Aging Out of the Blue: Region-Specific Epigenetic Clock Calibration for a Blue Zone with the DNAm SuperLearner Slides

12-1PM,

Apr. 15

Stellarus Research Talks: Yun Hu, Roanne Toretsky, and Rupali Roy

Yun Hu: Early Prenatal Initiative: Risk Stratification Prototype

Roanne Toretsky: Operationalizing Targeted Maximum Likelihood Estimation in Practice

Rupali Roy: Non-Network Request (NNR) Reason Classification using LLMs

Yun Hu Slides

Roanne Toretsky Slides

Rupali Roy Slides

12-1:30PM,

Apr. 22

Biostsatistics and Epidemiology Research Showcase

May 1

Fall 2025 CTML Seminar Series

PresenterResearch TopicsLink to Content
Adam Yala  AI for Personalized Cancer Care  
Opher Baron and Zhenghang Xu Machine Learning, Causal Queueing, and SiMLQ for Data Driven Simulation  Slides | Video
Zachary Butzin-Dozier

 Causal Inference via Electronic Health Record Data

 
Wenxin Zhang

Efficient Statistical Estimation for Sequential Adaptive Experiments with Implications for Adaptive Designs

 
Devan Mehrotra - remote presenter

Covariate Adjustment Using Treatment-Blinded Covariate Selection Within Randomized Clinical Trials

Slides | Video
Michael Rosenblum

Methodological Problems in Every Black-Box Study of Forensic Firearm Comparisons

Slides 

Romain Neugebauer

Comparison of GLP-1RA, SGLT2i, and other Type 2 Diabetes Pharmacotherapy Regimens Using Targeted Learning – approach and results from the ON TARGET DM study

Slides | Video

Yi Li

Targeted Deep Architectures: A TMLE-Based Framework for Robust Causal Inference in Neural Networks

 Slides

Sky Qiu

A Class of TMLEs for Efficient Estimation Under Two-Phase Sampling

Slides | Video

Eva-Maria Oess

Heterogeneous Net Treatment Effects

 Slides | Video

Spring 2025 CTML Seminar Series

PresenterResearch TopicsLink to Content
Emilie Hojbjerre-Frandsen Prognostic Score Adjustment for Marginal Effect Estimation with GLMs
Kaiwen Hou Hierarchical Approximation of Universal Least Favorable Paths for Improved Efficiency  Slides | Video
Alissa Gordon

Bridging the Evidence Gap: Leveraging Historical Control Data to Address Underrepresentation in Health Research

Kara Rudolph

Improving Efficiency in Transporting Average Treatment Effects

 Slides | Video
Kaitlyn Lee

RieszBoost: Gradient Boosting for Riesz Regression

 Slides | Video
Andy Kim
The Object Bagplot for Non-Euclidean Spaces: A Visualization and Outlier Detection Tool for Hyperbolic Data
 Slides | Video
Philip Lee & Karissa Huang

Surrogate Modeling for Infectious Disease Dynamics Using Machine Learning

Biostatistics Career Panel

Chair: Alejandro Schuler

Panelist: Alejandra Benitez, Andy Wilson, Lauren Dang, and Nima Hejazi

 Video

Nolan Gunter

Improving Finite Sample Performance in Auto-Debiased Causal Neural Networks with RieszDragon

 Slides

Kirsten Landsiedel

Improving the Efficiency of Estimators for Survival in Resampling Designs

Ellie Matthay

Causal Inference Challenges in Research on the Health Effects of Social Policies: Heterogeneous Effects and Treatment-Confounder Feedback

 Slides | Video

Joy Nakato

Efficient estimation of causal effects of HIV prevention and care strategies in clustered data settings

Carlos García Meixide

Causal Inference Via Proxy Interventions

Fall 2024 CTML Seminar Series

PresenterResearch TopicsLink to Content
Seraphina (Junming) Shi Integrative Deep Multi-Learning for Predicting and Biclustering Cancer Drug Responses (impaCluster): Leveraging Omics and Drug Molecular Data
Tianyue Zhou Towards More Accurate, Reliable and Equitable Pulse Oximetry Slides 

Biostatistics Career Panel

Chair: Alejandro Schuler

Panelists: Aurelien Bibaut, Caleb Miles, Wenjing Zheng, Xiudi Li, and Yue You

2024 Biostatistics Career Panel

Video
Wenxin Zhang

Causal Inference for Evaluating the Effectiveness of Medical Tests

Andrew Mertens

Integrated Multi-Omics Analysis of Human Milk, Maternal Nutritional Supplementation, and Child Growth: Results from the IMiC Multi-Site Study

Yi Li

Towards Estimation of the Intensity

Slides
Mark Pletcher

Embedded RCTs in Learning Health Systems

Slides | Video

Jean Feng

Towards a Post-Market Monitoring Framework for Machine Learning-Based Medical Devices

Slides | Video

Wendy (Yunwen) Ji

Optimizing Variance Estimation for Causal Inference Through HAL-based Bootstrap

Slides | Video

Gilmer Valdes

Unleashing Sparse Regularization: Equation for Setting Regularization Strength to Achieve Targeted Compression in CNNs and Transformers

Stathis Gennatas

Theory, Education, Application, Deployment: Designing Software to Bring Advanced Health Data Science to All

Silje Post Stroem & Louise Oesterby Jespersen

Investigation of the Average Treatment Effect of Interest in the Presence of Rescue Medication in a Randomized Clinical Trial

Slides | Video

Spring 2024 CTML Seminar Series

PresenterResearch TopicsLink to Slides
Haodong Li Targeted Learning on a Variable Importance Measure for Treatment Heterogeneity Slides
Romain Pirracchio Clinical AI; What We Need From You to Make This Revolution a Reality Video
Toru Shirakawa Deep LTMLE: Longitudinal Targeted Maximum Likelihood Estimation with Temporal-Difference Heterogenous Transformer Video For access please contact ctml_admin@berkeley.edu
David McCoy Discovery of Critical Thresholds in Mixed Exposures and Estimation of Policy Intervention Effects Using Targeted Learning Slides
Ashley Buchanan Power and Sample Size for Evaluating Spillover Effects in Networks With Non-Randomized Interventions Slides
Ahmed Alaa Conformal Meta-learners for Predictive Inference of Individual Treatment Effects

Slides | Video | Publication

Kaitlyn Lee Causal Inference with Binarized Continuous Treatments Slides
Noel Pimentel Score Preserving Targeted Maximum Likelihood Estimation Slides
Zachary Butzin-Dozier Evaluating Preventive Interventions for Long COVID Through Targeted Machine Learning Slides
Bochra Zareini Does the Use of New Weight Loss Drugs/Diabetes Drugs (Glucagon-Like Peptide 1 Receptor Agonists) Increase the Risk of Depression, Suicide, and Self-Harm? Slides

Fall 2023 CTML Seminar Series

PresenterResearch TopicsLink to Slides
Rachael V. Phillips Federated Targeted Learning Slides
Lauren Liao Transfer Learning with Efficient Estimators to Optimally Leverage Historical Data in Trial Analysis Slides
Nerissa Nance 

Handling real-world challenges: the role of simulation in applied causal analysis

Slides
Wenxin Zhang 

Sequential Adaptive Designs that Learn Optimal Individualized Treatment Rules by Utilizing Surrogate Outcomes

Slides
Shalika Gupta

Longitudinal Mediation for Perinatal Epidemiology

Slides
Yi Li

Estimation of Bivariate Survival Function under Censoring through HAL

Slides
Sky Qiu

Adaptive-TMLE for Randomized Controlled Trial Augmented with Real-World Evidence

Slides

Yunwen (Wendy) Ji

Causal Surveillance with Targeted Variance Estimation

Slides

Seraphina Shi

HAL-based Plugin Estimation of the Causal Dose–Response Curve

Slides

Nolan Gunter

Andy Kim

Variable Selection For Optimizing Clustering in Resource Limited Context:  An Application for Efficient Determination of Socio-economic Status in Africa

Slides

Sylvia Cheng

The Process of Aging through a Causal Lens: Examining a Causal Effect of Depressive Symptoms on Metabolic Dysfunctions and Cellular Aging

Slides

Kirsten Landsiedel

Causal Inference with Missing Exposures, Missing Outcomes, and Dependence

Slides

Joy Zora Nakato

Addressing Mediation and Positivity Violations in Cluster Randomized Trial Settings

Slides

Visiting Scholar

Li Yin

Evaluation of the effectiveness of the Swedish colorectal cancer screening program Slides