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)

Location: Berkeley Way West | Colloquia Room 1102 & 1104

Lightning Talk Presentations

  1. "Improving Efficiency in Causal Estimation and Adaptive Experimental Design" - Wenxin Zhang
  2. "Weight What? Estimating/Targeting Known Weights to Boost Efficiency" - Kirsten Landsiedel
  3. "Nonparametric Sensitivity Analysis for Hybrid Control Trials" - Alissa Gordon
  4. "Developing a Risk Prediction Model for Newborn Screening Refusal in California" - Christina Lin
  5. "Navigating the Spectrum: From Stratified to Pooled Estimation in Clustered Data" - Joy Nakato
  6. "Targeted Neural Network (TNN) An Efficient Plug-in Neural Network" - Yi Li
  7. "Longitudinal Causal Inference with Deep Targeted Learning" - Toru Shirakawa
  8. "Generative AI Assisted Response Adaptive Factorial Design" - Rita Lyu
  9. "Latent Profile Analysis to Classify US States into Typologies of Structural Racism" - Stephanie Veazie
  10. "Theoretical Foundations for Universal Least Favorable Paths in Semiparametric Statistics" - Kaiwen Hou

Poster Session Presentations

  1. "Causal Inference and Adaptive Design for Evaluating Effectiveness of Medical Tests and Devices" - Wenxin Zhang
  2. "Deep Causal Behavioral Policy Learning: Applications to Healthcare" - Jonas Knecht

  3. "Enhancing Hybrid Control Trials: Non-Parametric Sensitivity Analysis for Safe Integration of External Data" - Alissa Gordon

  4. "Developing a Risk Prediction Model for Newborn Screening Refusal in California" - Christina Lin
  5. "Patience Pays Off: Improving Causal Neural Network Training For Infant Health Outcomes Under Finite Samples" - Nolan Gunter
  6. "RieszBoost: Gradient Boosting for Riesz Regression" - Kaitlyn Lee
  7. "Language Model Augmented Semi-Supervised Statistical Inference" - Xinrui Ruan
  8. "Doubly Robust Policy Learning for Causal Stochastic Interventions through Neural Networks" - Sylvia Cheng
  9. "Theoretical Foundations for Universal Least Favorable Paths in Semiparametric Statistics" - Kaiwen Hou
Biostat Research Showcase

Topics

Archived Events topic page