About AI MIND Lab
About AI MIND Lab
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The AI MIND Lab (Artificial Intelligence for Medical Innovation and Novel Discoveries) at the University of Central Florida advances artificial intelligence for healthcare through research at the intersection of computer science, medical imaging, and clinical medicine. Our work focuses on multimodal foundation models, vision-language models, agentic AI, and longitudinal learning, with an emphasis on developing reliable, interpretable, and clinically grounded methods. Our research addresses challenges in kidney disease, breast cancer screening, cardiovascular imaging, and surgical video understanding. Through interdisciplinary collaborations, we aim to advance medical AI research, improve clinical decision-making, and train the next generation of researchers.
Current Research Team
Current Research Team
Principal Investigator
Principal Investigator
Pegah Khosravi, PhD
Associate Professor at University of Central Florida (UCF)
Institute for Artificial Intelligence, Department of Computer Science
Department of Clinical Sciences, College of Medicine
Senior Deputy Editor of AI, Journal of Magnetic Resonance Imaging
Board Member, Society of Incisionless Surgery (SIS)
GoogleScholarGitHubOpportunities at UCF AI MIND Lab
Opportunities at UCF AI MIND Lab
Fall 2026–Spring 2028 Notice
Fall 2026–Spring 2028 Notice
The AI MIND Lab research team for the 2026–2028 academic years has been finalized, and we are not accepting additional Ph.D. students, graduate research assistants, or other lab-funded researchers during this period. All graduate research assistant funding is fully committed to existing team members through the end of 2028.
Postdoctoral Opportunities: While we do not currently have funding for new postdoctoral positions, exceptional candidates with secured external postdoctoral fellowships may be considered, subject to research alignment and UCF appointment policies.
Ph.D. Student Research Expectations
Ph.D. Student Research Expectations
AI MIND Lab Ph.D. students are expected to pursue rigorous, independent research and develop a strong publication record in leading AI and medical imaging conferences and journals. Students are encouraged to take intellectual ownership of their projects, contribute original research, collaborate across disciplines, and demonstrate consistent progress toward their doctoral goals. As a general lab research milestone, students are expected to work toward at least three first-author papers at highly selective conferences and three first-author journal articles before graduation. These are lab mentoring goals rather than formal UCF degree requirements. Publication authorship and contributions are determined according to established academic and research ethics standards.
UCF Computer Science Ph.D. Application Deadlines
UCF Computer Science Ph.D. Application Deadlines
Fall Admission
Fall Admission
December 1: International applicants
July 1: Domestic applicants
Spring Admission
Spring Admission
July 1: International applicants
December 1: Domestic applicants
Prospective applicants should consult the official UCF Graduate Studies doctoral admissions page for the most current information. Admission to UCF does not guarantee placement in the AI MIND Lab.
Participation Requirements
Participation Requirements
AI MIND Lab researchers are expected to maintain consistent research engagement, attend scheduled meetings, meet agreed-upon milestones, communicate progress regularly, and contribute meaningfully to their projects. Due to the nature of our research, including access to clinical data and sponsored research resources, all participants must have an appropriate UCF affiliation and an approved research appointment or academic arrangement. The lab does not accept informal volunteer researchers. Research appointments and assistantships are subject to satisfactory research progress, available funding, appointment terms, and applicable UCF policies.
Ongoing Projects
Kidney-VLM: Multimodal AI for Kidney Disease
Developing kidney-specific vision-language models that integrate CT imaging, clinical reports, and quantitative imaging features for renal mass characterization and kidney stone analysis. Our research focuses on image segmentation, clinically grounded reasoning, and interpretable diagnostic support.
Longitudinal Vision-Language Models for Breast Imaging
Developing AI methods for longitudinal mammography analysis, with a focus on lesion localization and correspondence across screening examinations. Our research combines medical imaging and vision-language models to improve temporal understanding of breast findings.
Multimodal Foundation Models for Pan-Cancer Reasoning
Developing multimodal AI frameworks that integrate radiology, digital pathology, genomics, and clinical information for patient-level cancer understanding. Our research focuses on cross-modal reasoning, multimodal question answering, and robust interpretation of heterogeneous clinical evidence.
Agentic Vision-Language Models for Cardiac MRI
Developing tool-augmented vision-language models for quantitative cardiac MRI analysis. Our research combines specialized image analysis tools with multimodal reasoning to assess cardiac structure, ventricular function, and imaging-derived phenotypes.
Long-Form Video Understanding and Surgical AI
Developing vision-language models with persistent memory and temporal reasoning capabilities for understanding long videos. Our research focuses on tracking objects and their changing states over time, with future applications in surgical video understanding and instrument tracking.
Computing Infrastructure and Research Resources
AI MIND Lab maintains dedicated computing and data storage infrastructure to support large-scale medical AI research. The lab operates three GPU workstations, each equipped with two NVIDIA RTX PRO 6000 Blackwell Max-Q GPUs (96 GB ECC memory per GPU), AMD Threadripper PRO processors, and high-speed local storage. The lab also has approximately 250 TB of dedicated research storage through UCF's RStore system. In addition to these dedicated resources, the lab has access to the University of Central Florida's Advanced Research Computing Center (ARCC), including the Newton GPU cluster with NVIDIA V100 and H100 accelerators, the Stokes CPU cluster, and associated high-performance computing infrastructure. These resources support the development and evaluation of medical foundation models, vision-language models, agentic AI systems, and longitudinal and temporal learning methods, with applications in medical imaging, clinical reasoning, and decision support.
Top Medical AI Conferences
🧠General AI and ML Conferences
🧠General AI and ML Conferences
ICML: Jul 6-12 | Seoul, South Korea | icml.cc
AAAI: Feb 16-23 | Montréal, Canada | aaai.org
CVPR: Jun 3-7 | Colorado, USA | cvpr.thecvf.com
ICLR: Apr 23-27 | Rio de Janeiro, Brazil | iclr.cc
NeurIPS: Dec 6-12 | Sydney, Australia | neurips.cc
ECCV: Sep 8-13 | Malmö, Sweden | eccv.ecva.net
ICCV: October 2-8, 2027 | Hong Kong, CN | iccv.thecvf.com
🧬 Medical and Healthcare AI Conferences
🧬 Medical and Healthcare AI Conferences
MICCAI: Sept 27-Oct 1 | Strasbourg, France | miccai.org
MIDL: Jul 8-10 | Taipei, Taiwan | midl.io
ISBI: May 25-28 | Lausanne, Switzerland | biomedicalimaging.org
AACR: Apr 2-7 | Orlando, FL, USA | aacr.org
RSNA: Nov 29-Dec 3 | Chicago, Illinois, USA | rsna.org
MLHC: Aug 13-14 | Baltimore, MD, USA | mlforhc.org
CHIL: Jun 28-30 | Seattle, WA, USA | chil.ahli.cc
Ways to Connect
You are welcome to meet with me during my weekly office hours across both UCF campuses. To ensure I can give you my full attention, please email to schedule an appointment before your visit.
Mondays (8:00 AM - 4:00 PM) - Institute for Artificial Intelligence (IAI), UCF SPRK Office 319A, 4356 Scorpius St., Orlando, FL 32816.
Fridays (8:00 AM - 4:00 PM) - College of Medicine (Lake Nona), UCF COM Office 410B, 6850 Lake Nona Blvd., Orlando, FL 32827.
For virtual or ongoing professional connection, LinkedIn is my sole online presence. You are welcome to connect with me.
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