Abstract: At Foundation Medicine, we have the world's largest and unique clinicogenomics database that unites comprehensive genomic profiles to clinical outcomes. This talk will discuss the promise and power of this data as we continue to push the boundaries of harnessing AI to transform cancer care. We'll begin with a tour of the history of next-generation sequencing technology and how this has transformed oncology from single-gene and single-therapy analysis to comprehensive genomic profiling that require large-scale computation, analysis, and machine learning. Next, we'll cover the history of and conventional statistical modeling in the field of clinicogenomics and how we are complementing and extending these methods with machine learning models to empower patients, doctors, and biopharma companies to fight cancer.
Bio: John is the Head of Data Science – Data Products at Foundation Medicine, Inc.
He has nearly 20 years of experience at the intersection of software engineering, product, data science and machine learning in a variety of industries building predictive models, apps, and platforms that empower people.
John started his career as the Founder/CEO of a software company in college that helped tens of thousands of students. Throughout his career in data science, he’s held many hands-on senior leadership roles in data science and machine learning as well as consulting, advisory, and interim roles helping startups and larger companies harness data science and machine learning to create value – leading to significant growth, successful pivots, additional rounds of funding and acquisition. He was also a senior computational and technology lead at the Broad Institute of MIT & Harvard where he invented and developed a multiple-award winning and patented web platform for biological pathway analysis.
John has a B.A. in Economics (magna cum laude), M.S. in Statistics (magna cum laude), a Graduate level Certificate in Data Science from Harvard, both Deep Learning and Artificial Intelligence Nanodegrees, and has done graduate level work in Management Science and Applied Mathematics.