MATCH with AIM-AHEAD experts and AI tools

Expand your team’s AI proficiency

Part of the AIM-AHEAD Data and Infrastructure Capacity Building (DICB) Program

MATCH aims to ignite & accelerate AI and machine learning projects in biomedicine for AIM-AHEAD awardees and their teams

Workshops

April 22, 2025

This tutorial will introduce the core concepts of Continual Learning, focusing on how models can learn incrementally without forgetting previous knowledge. Participants will engage in hands-on exercises to implement key continual learning techniques using PyTorch. The session will also cover practical applications in AI and healthcare, demonstrating the importance of continual learning in real-world scenarios.

Jayanta Dey, Ph.D.
Post-doctoral research fellow @ UTSA MATRIX AI Consortium

April 29, 2025

Increasingly, generative AI models have shown a lot of promise in a variety of biomedical applications, such as Alpha-Fold for generating sequences of proteins and Evo for generating DNA sequences. This workshop gives an overview of current state-of-the-art methods for biomedical applications and how users can get started using code.

Sambit Panda, Ph.D.
AI Research Scientist @ UTSA MATRIX AI Consortium

Christian Cruz
AI Engineer @ UTSA MATRIX AI Consortium

June 2025

This webinar introduces key concepts and methods for building predictive models using electronic health records. Participants will explore how to prepare and structure clinical data, discuss common modeling approaches, and engage in hands-on exercises using open-source tools and sample datasets. The session will highlight opportunities and challenges in working with EHR data for biomedical research, including ethical considerations and potential applications in health equity and clinical decision support.