Fall 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 - Fall 2025 Syllabus

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

Ongoing Seminar Series

Fall 2025 CTML Seminar Series

Presenter	Research Topics	Link 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
Kirsten Landsiedel

Upcoming Seminar Series

Spring 2026 CTML Seminar Series

Presenter	Research Topics	Link to Content

Past CTML Seminar Series

Spring 2025 CTML Seminar Series

Presenter	Research Topics	Link 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

Presenter	Research Topics	Link 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

Presenter	Research Topics	Link 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

Presenter	Research Topics	Link 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

Topics

CTML Events topic page, Featured Events topic page