AI-Driven Spatial Proteomics to Better Understand Prostate Cancer Tumors
Attend this data science seminar and learn how NIH-funded researchers are addressing emerging challenges in cancer data integration, multimodal artificial intelligence (AI), interpretability, and scalable foundation-model development for precision oncology for prostate cancer.
Dr. Raghu Machiraju from The Ohio State University will:
- discuss methods for transforming heterogeneous, prostate cancer data sets (which are from multiplexed spatial proteomics platforms containing all kinds of variables) into structured representations for AI and foundation models. This includes ways that bring clinical outcome information earlier into the workflow, not later.
- describe his team’s TOPAZ framework for constructing tissue maps and tumor-immune interaction zones from spatial proteomics data.
- share his team’s ongoing work with multimodal, vision-language foundation models. By aligning histopathology images with molecular and spatial descriptors, these models can generate tissue analysis and tumor recurrence predictions.
By better understanding how immune and stromal systems interact with tumor architecture, Dr. Machiraju and his team can better support the study of prostate tumor maintenance, progression, recurrence, and treatment response.
About the Speaker
Raghu Machiraju, Ph.D.
Dr. Machiraju is a professor of computer science and engineering at The Ohio State University, with joint appointments in biomedical informatics and pathology in the College of Medicine. He is a co-principal investigator of the National Science Foundation-funded ICICLE AI Institute and serves as a visiting professor at the Kotak-IIT Bombay. His research focuses on data science and AI for translational medicine, emphasizing the integration of multimodal data—including imaging, genomics, epigenetics, and electronic health records—to drive mechanistic insight and clinical impact.
About the Data Science Seminar Series
CBIIT’s Data Science Seminar Series is dedicating its 2026 events to spotlighting the use of AI in cancer research and care. Brought to you by CBIIT and NCI’s Division of Cancer Treatment and Diagnosis AI working group, the upcoming webinars will explore a variety of questions, such as the following:
- How can AI be used for diagnosis, treatment, or omics research?
- What are the related laws and ethical considerations for AI?
- How can we empower an AI-ready cancer research community through workforce development, collaborations, and funding?
To view upcoming speakers or recordings of past presentations, visit the Data Science Seminar Series page.