Chris Diehl, Ph.D., is the Co-founder and Chief Science Officer at Unlearn.AI, a company at the forefront of developing AI-powered solutions to accelerate clinical trials. He leads the company's scientific vision and research efforts, focusing on the creation and application of 'digital twins' – prognostic, computationally generated models of individuals – to enable smaller, faster, and more patient-centric clinical studies. Dr. Diehl holds a Ph.D. in Neuroscience from Columbia University, where his research involved computational modeling of neural systems. Prior to co-founding Unlearn.AI, he was a Postdoctoral Scholar at the University of California, San Francisco (UCSF), further honing his expertise in machine learning, biostatistics, and computational biology. His work is driven by the goal of leveraging cutting-edge AI to bring new medicines to patients more efficiently and effectively.
Chris Diehl's work history includes a series of influential roles in various companies. Here is a detailed list of his professional journey:
Co-founded Unlearn.AI in 2017, a pioneering company focused on using generative AI models (Digital Twins) to optimize and accelerate clinical trials for new therapeutics. As CSO, he directs the scientific strategy and research for the company.
Spearheaded the conceptualization and development of prognostic Digital Twins for clinical trials, which can reduce trial sizes, shorten timelines, and increase statistical power, ultimately aiming to get effective treatments to patients faster.
Played an instrumental role in securing substantial venture capital funding for Unlearn.AI, including a notable $50M Series B round, enabling the company's growth and expansion of its AI platform.
Completed doctoral research focusing on computational neuroscience, providing a strong foundation in quantitative modeling and complex data analysis, which is directly applied to his work in AI for healthcare.
Authored and co-authored numerous peer-reviewed publications and has presented at key industry and academic conferences on the application of AI and machine learning in drug development and clinical research.
Carnegie Mellon University - Year 1997
Carnegie Mellon University - Year 1996
Carnegie Mellon University - Year 1991
Thomas Jefferson High School for Science and Technology - Year 1989
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