Careers in Data Sciences: Startups

Panelists

Chit-Kwan Lin, Ph.D.

Chit-Kwan (CK) is the founder and CEO of an early-stage natural language processing startup in the fintech space. He is also a machine learning consultant, specializing in technical due diligence and ML strategy, talent, and operationalization.  His wide-ranging deeptech expertise — drawn from over twenty years in both academic and industry settings — spans machine learning, computer architecture, distributed computing, cyberphysical systems, wireless networking, software engineering, and healthcare. Trained as a computer scientist, with dozens of peer-reviewed publications and patents, he now focuses on research commercialization and most enjoys building teams that turn lab innovations into useful products. CK holds A.B., S.M., and Ph.D. degrees, all from Harvard.

Patrick Howie

Founder and CEO Patrick Howie created MediFind after watching his brother struggle to navigate the healthcare system to treat his rare cancer. Mr. Howie was most recently head of global analytics at Merck and has also held senior leadership positions in multiple healthcare startups. He is the author of the book The Evolution of Revolutions, and his work has been cited in numerous professional publications including Forbes, Business Week, and The Wall Street Journal.

Tuan Dinh, Ph.D.

Tuan Dinh, Ph.D., is an entrepreneur and senior technology executive with 15 years of progressive leadership in starting, building, and growing teams to deliver data science and AI as a service for a wide range of life science, healthcare and consumer applications. Currently, Dr. Dinh is the chief data science officer and co-founder at Cogitativo. Based in Berkeley, California, Cogitativo provides data science as a service (DSaaS) for healthcare organizations to extract value from public and proprietary data sources to address the U.S. healthcare cost and quality of care crisis. Cogitativo helps clients reduce their levels of epistemic opacity while improving efficiency and include detection of anomalistic, suboptimal and low-value care, optimization of patient journeys to improve care quality and reduce costs, payment integrity, and prediction of high cost patients and recommendation engines for next-best actions.