Upcoming Events

Friday, March 7th 12:00pm - 1:00pm, ARB 627 or Zoom Zoom ID: 957 7525 9475 Passcode: 834911 Kaizheng Wang, PhD Assistant Professor of Industrial Engineering and Operations Research Columbia University Conditional Diffusion Models for Missing Data Imputation: Part II Abstract: Diffusion models have emerged as a powerful generative framework, achieving state-of-the-art performance across diverse applications. They have shown remarkable potential for missing data imputation, offering a flexible and effective solution to this fundamental challenge. In this talk, Professor Wang will begin with an overview of diffusion models for unconditional data generation, explaining the core concepts of the forward (noise-adding) and reverse (denoising) processes. Building on this foundation, he will then introduce conditional diffusion models tailored for missing data imputation, covering both continuous and discrete data scenarios. Key topics include modeling techniques, conditioning mechanisms, and training strategies. Why Diffusion Models? As data grows increasingly complex, diffusion models offer a cutting-edge approach to handling missing entries, generating realistic synthetic data, and improving the robustness of predictive tasks. These methods stand at the forefront of generative AI techniques, making them a valuable tool for both methodological research and practical applications. Speaker Bio: Kaizheng Wang is an assistant professor of Industrial Engineering and Operations Research and a member of the Data Science Institute at Columbia University. He works at the intersection of statistics, machine learning, and optimization.   About TRAIL4Health & the Brown Bag Learning Series TRAIL4Health is a Translational AI Laboratory committed to advancing public health through innovative applications of artificial intelligence and data science. At TRAIL4Health, we host a variety of events to foster learning, collaboration, and the exchange of ideas at the intersection of AI, public health, and medicine.  The TRAIL Brown Bag Learning Series is a weekly informal gathering held on Fridays at noon in Room 627 of the Allen Rosenfield Building. These sessions are an opportunity for faculty, students, and researchers to come together and learn something new—whether it be a dataset, software, new article, or simply to exchange ideas. This informal setting provides a platform for sharing knowledge, stimulating discussions, and fostering collaboration in a relaxed environment. 

Friday, March 14th 11:45am - 1:00pm, ARB Hess Commons Weining Shen, PhD Associate Professor, Donald Bren School of Information & Computer Sciences University of California, Irvine Data integration in clinical trials and sports analytics Many real-world applications require collecting and analyzing data from multiple sources. In this talk, I will present two projects related to data integration. The first project focuses on evaluating the sports understanding of mainstream large language models, using newly introduced benchmark datasets. Our evaluation covers a range of tasks, from basic queries about rules and historical facts to complex, context-specific reasoning, as well as assessing the sports reasoning capabilities of video language models. The second project is about selecting relevant external data to improve inference of long-term efficacy for gene therapies. We will introduce a new Bayesian selection framework and discuss its theoretical properties and empirical performance in a real-world gene therapy trial. Biostatistics Departmental Seminars & Lectures Lectures are in-person only unless marked otherwise. For all Zoom inquiries to attend seminars with a listed virtual option, please send an email to Erin Elliott, Programs Coordinator (ee2548@cumc.columbia.edu). During the Fall and Spring semesters, the Department of Biostatistics holds regular seminars on Thursdays, called the Levin Lecture Series, on a wide variety of topics which are of interest to both students and faculty. Over each semester, there are also often guest lectures outside the regular Thursday Levin Lecture Series, to provide a robust schedule the covers the wide range of topics in Biostatistics. The speakers are invited guests who spend the day of their seminar discussing their research with Biostatistics faculty and students.