The 2026 Dr. Robert Gillies Machine Learning Workshop in Cancer will be held on October. 15 and 16. It will be the fourth annual conference held in memory of notable Moffitt researcher, Dr. Robert Gillies.
The meeting will cover the latest advances in AI/ML and their application in cancer. This year’s work will also host outstanding keynotes and invited speakers in the areas of medical imaging (radiomics), pathology (pathomics), basic science, drug discovery, clinical informatics/operations, natural language processing, generative AI, foundational models, federated learning, as well as ethics and biases, and interpretable and trustworthy AI.
Dr. Robert Gillies
Please register by October 9, 2026
Abstract Submission Deadline:
September 18, 2026
Summaries of new, ongoing, and updated research related to Machine Learning/AI in Cancer will be acceptable for submission and presentation (oral or poster).
An Abstract should address scientific questions, detail Machine Learning/AI use in cancer-related clinical operations or research, and/or contain primary scientific data.
Workshop Venue:
Vincent Stabile Research Building at Magnolia Campus
12902 USF Magnolia Drive, Tampa, FL 33612
Accommodations:
1. Embassy Suites by Hilton Tampa USF Near Busch Gardens
2. Home2 Suites by Hilton Tampa USF Near Busch Gardens
3. Hilton Garden Inn Holiday Inn Express
Ruijiang Li
Stanford University
Associate Professor of Radiation Oncology (Radiation Physics)
Radiation Oncology - Radiation Physics
Veeraraghavan Harini
Memorial Sloan Kettering Cancer Center
Associate Member of Medical Physics
Tina Hernandez-Boussard
Stanford University
Professor of Medicine (Biomedical Informatics), of Biomedical Data Science, of Surgery and, by courtesy, of Epidemiology and Population Health
Despina Kontos PhD
Vice Chair A and Data Science Research - Radiology
Columbia University Irving Medical Center
Umit Topaloglu PhD
Chief of Clinical & Translational Research Informatics Branch
National Institute of Health
Judy Wawira Gichoya MD, MS
Interventional Radiology for Cancer Prevention and Control
Emory University - Winship Cancer Institute
Please visit the archives for highlights from our previous workshops:
Please note this is a separate registration.
Hackathon is designed for AI researchers, students and developers to explore computeintensive multimodal learning approaches for medical imaging and clinical text analysis.
Overview:
Participants will develop models to classify brain cancer subtypes (e.g., glioblastoma vs. lower-grade gliomas) by combining:
