Pratik Shah Invited as Discussion Leader for the NCI ITCR Multimodal AI and Molecular Data for Cancer Research Panel
July 16, 2026 - July 16, 2026
2:30pm - 3:15pm ET
Cold Spring Harbor Laboratory, NY
Pratik Shah to Lead Panel on Multimodal AI at 2026 ITCR Annual Meeting hosted by the National Cancer Institute
Panel: Thursday, July 16, 2026; 2:30pm - 3:15pm ET
Venue: ITCR 2026 Annual Meeting,Cold Spring Harbor Laboratory, 1 Bungtown Road, Cold Spring Harbor, NY 11724
Meeting website:
Panel Topics
- Multimodal AI for imaging, genomics, and spatial biology
- Real use cases in cancer research
- Current limits of these tools
- Responsible AI and reproducibility
- Standards and data-sharing needs for the field
Dr. Pratik Shah leads a panel titled “Multi-Modal Synthesis: Bridging Deep Learning in Imaging, Genomics, and Spatial Transcriptomics.” The panel brings together leading researchers in cancer genomics and computational oncology. They will discuss how generative and multimodal AI can connect tissue architecture, molecular data, and translational cancer research. Multimodal generative deep learning is a fast-growing area of cancer informatics. New models can now fuse imaging, genomic, and spatial data at scale, directly advancing ITCR’s mission to build and share informatics tools for cancer research.
Panelists
- Dr. Mike Wigler, Cold Spring Harbor Laboratory. Cancer genomics. Single-cell genomics. Blood-based cancer detection. Whole-genome sequencing interpretation.
- Dr. Obi Griffith, Washington University. Deep learning for precision oncology. Variant and neoantigen prioritization. Software development. Clinical translation.
- Dr. Han Liang, MD Anderson Cancer Center. Cancer omics. Deep learning-driven bioinformatics tools. Single-cell and spatial studies. Precision oncology.
- Dr. Rachel Karchin, Johns Hopkins University. OpenCRAVAT. Genomic interpretation. LLMs. Community software resources for responsible translation.
- Dr. Pratik Shah, University of California, Irvine. Discussion lead. Generative deep learning. Imaging. Pathology. Multimodal synthesis. Clinical validation.
