Lab profile
About AI MIND Lab
The AI MIND Lab advances artificial intelligence for healthcare through research at the intersection of computer science, medical imaging, and clinical medicine. The lab focuses on multimodal foundation models, vision-language models, agentic AI, and longitudinal learning, with emphasis on developing reliable, interpretable, and clinically grounded methods. Research addresses challenges in kidney disease, breast cancer screening, cardiovascular imaging, and surgical video understanding.
01 · Research focus
Research areas and highlights
Topics and recent work as stated on the lab’s own site.
- Kidney-VLM: Multimodal AI for Kidney DiseaseDeveloping kidney-specific vision-language models that integrate CT imaging, clinical reports, and quantitative imaging features for renal mass characterization and kidney stone analysis.
- Longitudinal Vision-Language Models for Breast ImagingDeveloping AI methods for longitudinal mammography analysis, with a focus on lesion localization and correspondence across screening examinations.
- Multimodal Foundation Models for Pan-Cancer ReasoningDeveloping multimodal AI frameworks that integrate radiology, digital pathology, genomics, and clinical information for patient-level cancer understanding.
- Agentic Vision-Language Models for Cardiac MRIDeveloping tool-augmented vision-language models for quantitative cardiac MRI analysis combining specialized image analysis tools with multimodal reasoning.
- Long-Form Video Understanding and Surgical AIDeveloping vision-language models with persistent memory and temporal reasoning capabilities for understanding long videos, with future applications in surgical video understanding and instrument tracking.
- Multimodal AI for Bone Metastasis Detection
- Longitudinal 3D AI for Breast Cancer Response
- Privacy-First Federated AI for Autism
02 · People
Leadership and researchers
People listed on the lab’s team pages, by role.
03 · Research intelligence
Research Intelligence evidence
Publications, grants and clinical trials linked to the lab’s researchers in Health AI Central’s research data.
Publications & preprints
- Human Evaluation of Synthetic Videostroboscopic Laryngeal Images Generated Using StyleGAN3.The Laryngoscope · 2026
- A Multimodal Approach for Deep-Learning Classification of Vocal Fold Pathologies in Stroboscopy.The Laryngoscope · 2026
- Exploring Real-Time Tracking of Vocal Fold Polyps in Video-Stroboscopy Using Deep Learning.The Laryngoscope · 2026
04 · Updates
Updates and lab news
News and events from the lab’s own site.
No news has been collected from the lab’s site yet.
05 · Official presence
Lab sources and channels
The lab’s own pages and accounts.
06 · Related
Related labs and centers
Labs at the same institution and labs working on similar topics.