Accelerate your biomedical and healthcare research with AI-driven solutions
MATCH aims to ignite & accelerate AI and machine learning projects in biomedicine for AIM-AHEAD awardees and their teams.
Part of the AIM-AHEAD Data and Infrastructure Capacity Building (DICB) Program
Expand your team’s AI proficiency
MATCH with AIM-AHEAD experts and AI tools
Workshop dates 2025
April 22, 2025
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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
April 29, 2025
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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
May 2025
Prediction of health outcomes using electronic medical records (EMRs)
Carolina Vivas-Valencia, Ph.D.
Assistant Professor of Biomedical Engineering @ UTSA
May 2025
Reinforcement learning
Tej Pandit, M.S.
PhD Candidate @ UTSA Electrical Engineering
August 2025
Computer vision for 3D in vivo brain samples
David Hernandez-Guzman
PhD Candidate @ UTSA Biomedical Engineering
Core areas of expertise
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Fine-tuning LLMs
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Forecasting / prediction models
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Federated learning
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Continual learning
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Computer vision
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Molecular & omics data analysis
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Model benchmarking and scoring
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Geospatial population-level models