Mathematics & Statistics Colloquium: Fri, June 19: Alexander Rodriguez

Join us for our next REU/summer colloquium talk covering The talk covers AI-driven public health pipelines, outbreak response, uncertainty quantification, multimodal data, and LLMs for forecasting and policy analysis.

Date and Time: Friday, June 19th from 11am-12:30pm

Location: CASL 2048

Speaker: Prof. Alexander Rodríguez (Assistant Professor, Computer Science and Engineering, University of Michigan) 

Title: AI for Complex Health Systems: Learning, Simulation, and Decision-Making

Abstract: In this talk, I will present our efforts in developing AI-driven pipelines for public health. I will first discuss deep learning architectures for real-time outbreak response, highlighting how our frameworks quantify uncertainty and leverage multimodal data. I will then present our work on LLMs for simulation-driven decision-making that operate on scientific simulators to support robust forecasting and policy analysis.
 

Bio: Alexander Rodríguez is an Assistant Professor of Computer Science and Engineering at the University of Michigan. His research addresses problems at the intersection of machine learning, time series analysis, scientific modeling (AI for Science), uncertainty quantification, and multi-agent systems, with primary applications in health sciences and engineering. He received his Ph.D. in Computer Science from the Georgia Institute of Technology in 2023 and previously served as a Research Fellow in the Division of Epidemiology at the Mayo Clinic.