Data Science Seminar Series

Pathology AI Foundation Models Across Modalities and Spatial Scales

September 30, 2026 | 11:00 a.m. – 12:00 p.m., ET
Andrew Song, Ph.D., UT MD Anderson Cancer Center
Explore how AI foundation models are expanding the possibilities of computational pathology. 

• AI-Driven Spatial Proteomics to Better Understand Prostate Cancer Tumors | June 3, 2026
  Discover how a team structures prostate cancer data sets to be suitable for AI and foundational models.
• Validating AI in Digital Pathology for Clinical Use Beyond the Algorithm | April 15, 2026
  Discover the challenges and successes of developing standardized artificial intelligence models in digital pathology for cancer diagnostics.
• Multi-modal Modeling in Precision Medicine: From Data Imputation to Synthetic Data | March 18, 2026
  Learn about “cross-modal data modeling”—a methodology that uses foundation models (i.e., large, pre-trained, artificial intelligence models) to ascribe missing biomedical research data and generate realistic synthetic samples.
• Robotics, Agents, and World (RAW) Models to Target Cancer | February 18, 2026
  Discover how artificial intelligence (AI), robotics, and predictive models could transform cancer drug development.
• Theranostics Digital Twins: A Path to Personalized Medicine | January 14, 2026 
  Explore the intersection of digital twins and theranostics and how these two critical data science concepts work in practice in liver, prostate, and metastatic cancer.
• Developing Safe AI Models for Clinical and Multi-institutional Research Studies | September 3, 2025 
  Explore approaches and use cases for developing safe AI in clinical and multi-institutional research studies.
• Ctrl+Alt+Cure: Driving Smarter Cancer Care | June 11, 2025
  Discover how AI transforms cancer care, covering key terminology, history, clinical developments, diagnostics, and drug discovery in oncology.
• AI in Cancer: Bridging Context from Design to Delivery | April 2, 2025
  Learn how AI will revolutionize healthcare by enhancing diagnostic precision, optimizing treatment plans, and improving patient outcomes.
• AI-Augmented Pathology: Enhancing Real-Time Cancer Diagnosis and Discovery | March 5, 2025
  Explore how AI is impacting cancer research and clinical diagnosis by transforming the field of pathology.
• Integrating AI and Generative AI in Operations and Research: From Creating the Team and Infrastructure to Supporting 2,000+ Users | November 13, 2024
  Hear from a team of multidisciplinary experts who bridge the gap between big tech, operations, and research by leveraging cutting-edge AI technologies to enhance cancer research.
• Biomedical Data Fusion Lab | July 17, 2024
  Learn how to leverage various data types in medicine, including computational methods for improving decision-supported models for personalized diagnosis, prognosis, and therapy.
• Docker Tech Talk | June 26, 2024
  Discover how Docker simplifies and accelerates the app lifecycle workflow, providing freedom to innovate your choice of tools, application stacks, and deployment environments for projects.
• The Current State of Transparency for AI Models and Datasets | June 12, 2024
  Find out about tools improving AI model transparency, the provision of data set metadata, and recent initiatives to implement these tools in NIH's Bridge2AI program.
• Machine Learning Dynamics in the Tumor Microenvironment | May 22, 2024
  Learn about a set of statistical machine learning methods developed to infer the temporal and spatial dynamics of cells in the tumor microenvironment.
• Data Quality for LLMs: Building a Reliable Data Foundation | April 24, 2024
  Discover how data qualify affects the performance of large language models.
• Identifying Recurrent Non-Hodgkin Lymphoma in Structured and Unstructured Electronic Health Data | April 3, 2024
  Explore algorithms to better identifying patients experiencing non-Hodgkin lymphoma recurrence.