Speaker Profile
Ph.D., Vice President, Data Analytics, Rancho BioSciences
Biography
Dan Rozelle leads Data Analytics at Rancho BioSciences, guiding the Bioinformatics and Data Science teams and shaping Rancho’s scientific innovation agenda. Since joining Rancho in 2016, he has grown a diverse organization of computational scientists and launched industry-defining initiatives including the Single Cell Data Science Consortium and the Spatial Innovation Initiative.
Dan focuses on advancing analytical excellence across oncology, immunology, neuroscience, and other therapeutic areas while accelerating Rancho’s investment in next generation technologies and data products. His teams consistently deliver high impact scientific results and contribute to leading peer reviewed publications.
Dan holds a PhD in Cell and Developmental Biology from the University of California at Davis and has more than twelve years of experience in biomedical research, data science, and scientific leadership."
Talk
Quality & Quantity: Lessons from Building 100M+ AI-Ready Single Cells
AI in single-cell biology requires data that's both abundant and reliable. Through our 11-pharma consortium, we validated 100M+ cells with consistent quality standards across diverse tissue types and disease states. In this talk I'll share what makes single-cell data truly "AI-ready" at scale.
Session Abstract – PMWC 2026 Silicon Valley
Track Chair:
Christina Curtis, Stanford
PMWC Award Ceremony
• W.E. Moerner, Stanford
• Serge Saxonov, 10x Genomics
• Priscilla Chan, Biohub
Honoree Fireside
• Christina Curtis, Stanford
• Priscilla Chan, Biohub
Honoree Fireside: From Measurement to Meaning: What Data AI Still Needs in Biology
• Christina Curtis, Stanford
• W.E. Moerner, Stanford
• Serge Saxonov, 10x Genomics
• Anne Wojcicki, 23AndMe
Unraveling Tissue Architecture with Single-Cell & Spatial Multi-Omics
• Chair: Garry P. Nolan, Stanford
• Joakim Lundeberg, SciLifeLab
• Tae Hyun Hwang, Vanderbilt University Medical Center
• Michael Angelo, Stanford
Spatial Sequencing for Next Generation Pathology
• Eli Glezer, Singular Genomics
Precision Profiling of Cells: Insights from Imaging-Spectral Flow Cytometry and Single-Cell Multiomics
• Aruna Ayer, BD
Single-Cell Genotype and Targeted Gene Expression Assay
• Zivjena Vucetic, Mission Bio
Resolving Cellular Lineage and State in Tumors with High-Resolution Single-Cell Genomics
• Gary Schroth, Cellanome
Quality and Quantity: Lesson from building 100M+ AI-Ready Single Cells
• Dan Rozelle, Rancho Biosciences
Tumor Evolution & Clonal Dynamics: From Models to Monitoring
• Christina Curtis, Stanford
Personal Omics at Scale: What Longitudinal Profiles Add to Early Detection
• Michael Snyder, Stanford
Multi-Omics-Driven Early Detection: Beyond Liquid Biopsy
• Chair: Alex Aravanis, Moonwalk Biosciences
• Ash Alizadeh, Stanford
• Sara Ahadi, OmicsEra
Scaling Data Generation for Foundational Biology Models with Single Cell Sequencing
• Alex Rosenberg, Parse Bioscience
AI in Molecular Diagnostics: Integrating Multi-Omics & Clinical Data
• Chair: Marina Sirota, UCSF
• Olivier Gevaert, Stanford
• Rebecca Critchley-Thorne, Castle Biosciences
• Lihua Jiang, Stanford
• Yunguan Wang, Cincinnati Children's
