Join the Machine Learning in Medical Imaging Consortium (MaLMIC) for an opportunity to network on machine learning
MaLMIC Virtual Open Forum on Foundation Models and Multimodal AI in Brain Health
This MALMIC Virtual Forum will explore how artificial intelligence and multimodal data are transforming the future of brain health and medical imaging. Dr. Ruogo Fang will present advanced multimodal AI frameworks—including digital twins and foundation models—that move beyond “one-size-fits-all” approaches to enable more precise, equitable care. Complementing this, Dr. Kuang Gong will highlight cutting-edge innovations in PET imaging, showcasing how foundation models, 3D diffusion techniques, and vision-language approaches can significantly enhance image quality for improved diagnosis and disease monitoring.
April 10th, 2026
12:00 to 1:00 p.m. Eastern
Interested in joining? Please contact us.
MaLMIC Virtual Open Forum on Foundation Models and Multimodal AI in Brain Health
This MALMIC Virtual Forum will explore how artificial intelligence and multimodal data are transforming the future of brain health and medical imaging. Dr. Ruogo Fang will present advanced multimodal AI frameworks—including digital twins and foundation models—that move beyond “one-size-fits-all” approaches to enable more precise, equitable care. Complementing this, Dr. Kuang Gong will highlight cutting-edge innovations in PET imaging, showcasing how foundation models, 3D diffusion techniques, and vision-language approaches can significantly enhance image quality for improved diagnosis and disease monitoring.
April 10th, 2026
12:00 to 1:00 p.m. Eastern
Interested in joining? Please contact us.
Ruogu Fang, PhD
Associate Professor, Pruitt Family Endowed Faculty Fellow in the J. Crayton Pruitt Family Department of Biomedical Engineering at the University of Florida
Dr. Fang’s research focuses on integrating AI and deep learning with neuroscience, with two main themes: AI-driven precision brain health and brain-inspired AI. She works on early Alzheimer’s detection, predicting treatment outcomes, and designing personalized interventions using multimodal medical imaging. As founder and director of the SMILE Lab, she develops advanced AI models to better understand, diagnose, and treat brain disorders using complex datasets.
Talk Title: Brain Digital Twins and Foundation Model
Talk Description: The synergy of artificial intelligence (AI) and multimodality data is unlocking new frontiers in brain health. This talk delves into multimodal AI models that transcend traditional “one size fits all” methodologies, which often result in misdiagnoses, suboptimal treatment outcomes, and healthcare inequities. Specifically, Dr. Fang will talk about how an advanced multimodal AI framework, including multimodal digital twins and foundation models, paves the way for precision medicine in brain health from the bottom-up and top-down approaches.
Kuang Gong, PhD
Assistant Professor, J. Crayton Pruitt Family Department of Biomedical Engineering at the University of Florida
Dr. Gong’s research interests are centered around the convergence of deep learning, medical imaging, and data science to enhance the diagnosis and treatment monitoring of various diseases, particularly Alzheimer’s disease (AD) and cancer. His work involves developing novel methodologies in medical physics-informed deep learning, leveraging prior information-guided network design, and applying clinical task-driven network training for more accurate and precise results.
Talk Title: Foundational Models for PET image quality enhancement
Talk Description: PET image quality enhancement is essential for better disease diagnosis and progression monitoring. In his talk, Dr. Gong will discuss recent results from his lab on foundation models for PET image quality enhancement via 3D diffusion models, vision-language models, and agentic approaches will be discussed.