Ph.D., Principal Product Manager, Amazon Web Services
Biography
Aaron Friedman is the principal product manager for Amazon Omics. In this role, he is responsible for listening to customers, defining requirements, and ensuring that Amazon Web Services (AWS) helps customers advance scientific discovery and precision medicine. Prior to this role, Friedman spent over five years in AWS healthcare and life sciences solutions (HCLS) architecture leadership roles, spending four years as the HCLS tech lead for the AWS Partner Network and then a year and a half as the HCLS tech lead for startups. In those roles, he also built many of the original architectures and patterns for genomics on AWS. Prior to AWS, Friedman was the first technical employee at Human Longevity, a biotech startup delivering omics-guided healthcare solutions. He received his Ph.D. in Biomedical Sciences at UCSD and graduated summa cum laude with a BS in Biomedical Engineering at Washington University in St. Louis.
AI and Data Sciences Showcase:
Amazon Web Services (AWS)
AWS is the trusted technology and innovation partner to the global healthcare and life sciences industry, providing unmatched reliability, security, and data privacy. To help organizations achieve business and technical goals, AWS provides cloud services and Partner solutions, used by thousands of customers globally.
Introducing Amazon Omics
Learn how Amazon Omics helps healthcare and life science organizations and their software partners advance precision medicine.
Session Abstract – PMWC 2023 Silicon Valley
Showcase Track S1 - January 25 9.00 A.M.-1.15 P.M.,Showcase Track S1 - January 26 11.30 A.M.-1.15 P.M.,Showcase Track S1 - January 27 11.00 A.M.-1.15 P.M.
The PMWC 2023 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.
