Speaker Profile

Ph.D., Strategic Partner Manager, ROSALIND

Ryan has always stayed at the forefront of technology throughout his 15+ year career in genomics. Focused on uncovering the genetic basis of cardiovascular disease, his work began at UCSD utilizing various gene expression, genotyping, and sequencing methodologies to develop novel small molecule therapeutics for essential hypertension. After leaving academia for the biotech industry, Ryan switched to developing NGS-based molecular diagnostics for hereditary cancer through a collaboration with IBM, using their Watson Artificial Intelligence system, to develop a personalized medicine app for patients. More recently at NanoString, Ryan harnessed his expertise in spatial transcriptomic assays and data analysis pipelines to support the Pharma, Biotech, and the Academic community in southern California with their drug development, clinical trial, and biomarker studies. Ryan is now at the forefront of cloud computing and is excited to help researchers across the globe discover novel insights in their data with ROSALIND.

AI and Data Sciences Showcase:

ROSALIND is the leading collaborative research platform for knowledge management and multi-omic data analysis. As a secure unified data hub for sequencing and multiplex technologies, ROSALIND combines deep interpretation and interactive visualization for spatial, single-cell, RNA, NanoString, and clinical data.

Advancing Precision Medicine through Spatial and Multi-Omic Data Analysis
Learn how the ROSALIND collaborative analysis platform brings together biomedical, multi-vendor, multi-omic data with leading-edge machine learning.

 Session Abstract – PMWC 2022 Silicon Valley

Track 7, June 28-30

The PMWC 2022 AI Company Showcase will provide a 15-minute time slot for selected AI companies to present their latest technologies to an audience of leading investors, potential clients, and partners. We will hear from companies building technologies that expedite the pre-clinical and clinical drug discovery and development process, accelerate patient diagnosis and treatment, or develop scalable systems framework to make AI and deep/machine learning a reality.