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Ruogu Fang

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Associate Professor

University of Florida
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About

Ruogu Fang is an Associate Professor at the University of Florida, United States. His research areas include deep learning applications in medicine, neuroimaging, and machine learning techniques for drug discovery and cognitive enhancement. Recent publications highlight his work on foundation models in medicine, emotion selectivity in neural networks, and techniques for unsupervised segmentation in neuroimaging.

Recent Grants

Grant: Close

Collaborative Research: SCH: Trustworthy and Explainable AI for Neurodegenerative Diseases

Open Date: 2021-10-01

Close Date: 2025-09-30

Grant: Close

Mechanisms, response heterogeneity and dosing from MRI-derived electric field models in tDCS augmented cognitive training: a secondary data analysis of the ACT study

Open Date: 2021-06-01

Close Date: 2024-05-31

Grant: Close

III: Small: Modeling Multi-Level Connectivity of Brain Dynamics

Open Date: 2019-10-01

Close Date: 2023-09-30

Grant: Close

CRII: SCH: Characterizing, Modeling and Evaluating Brain Dynamics

Open Date: 2017-06-15

Close Date: 2019-04-30

Grant: Close

CRII: SCH: Characterizing, Modeling and Evaluating Brain Dynamics

Open Date: 2016-05-01

Close Date: 2017-10-31

Positions (1)

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Ruogu Fang

University Name
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University of Florida

The Smart Medical Informatics Learning and Evaluation (SMILE) Lab at the University of Florida is recruiting for fully funded PhD and postdoctoral positions for 2025–2026, with additional opportunities for RA and internship roles. The lab, led by Ruogu Fang , works at the intersection of neuroscience, artificial intelligence, intelligent agents, brain-inspired AI, multimodal learning, affective computing, and cognitive modeling . Research directions highlighted in the post include brain world models , agentic AI / agentic systems , neuroscience × AI , medical AI , generative AI , foundation models , LLMs , and digital twins . The lab also mentions NSF-supported work on brain-inspired AI education and next-generation AI learning platforms. Funding is described as fully funded , supported by new NIH and NSF funding. The post specifically states that multiple fully funded PhD positions and fully funded postdoc positions are open. Remote and summer RA/internship options are also mentioned. Preferred applicants have a background in Computer Science, AI, Electrical Engineering, Statistics, Mathematics, Neuroscience, or Biomedical Engineering . Strong Python and deep learning skills are expected, and experience with PyTorch , LLMs/VLMs , reinforcement learning , or multimodal data is a plus. The lab also values prior publications in top AI venues and strong self-motivation for interdisciplinary research. To apply, email your CV to [email protected] with the subject line format provided in the post. The lab website’s Openings page is also referenced for more details.

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Collaborators (5)

Joseph Gullett

Assistant Professor

University of Florida

UNITED STATES
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Juan E. Gilbert

University of Florida

UNITED STATES
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Jiang Bian

Associate Professor

University of Florida

UNITED STATES
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Ivana Parker

University of Florida

UNITED STATES
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Gustavo Seabra

Research Associate Professor

University of Florida

UNITED STATES
View details
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