Warren Pettine
About Warren Pettine
Warren Pettine is a Postdoctoral Fellow at Yale University and CEO of Mountain Biometrics, a healthtech company. He specializes in developing machine learning algorithms for biometric data and has a background in computational psychiatry and neurophysiology.
Work at Yale University
Warren Pettine has been serving as a Postdoctoral Fellow at Yale University since 2020. In this role, he focuses on advancing research in health technology, particularly in the area of biometric data analysis. His work involves developing machine learning algorithms that analyze data from wearable devices, enabling the detection of health patterns over extended periods.
Education and Expertise
Warren Pettine holds a Doctor of Medicine (MD) degree from the University of Colorado Anschutz Medical Campus, which he completed from 2012 to 2017. He also earned a Bachelor of Arts in History and Philosophy from Colorado College between 2004 and 2008. His educational background supports his expertise in computational psychiatry and machine learning applications in health technology.
Background in Research
Prior to his current position, Warren Pettine worked at several prestigious institutions. He was a Postdoctoral Researcher at New York University from 2017 to 2020, a Research Fellow at Stanford University for one year in 2015-2016, and a Research Assistant at Harvard Medical School from 2010 to 2012. He also gained experience as a Research Assistant at Colorado State University in 2009-2010.
Leadership at Mountain Biometrics
Warren Pettine is the CEO of Mountain Biometrics, a healthtech company dedicated to preparing individuals for mountaineering adventures while monitoring their health in real-time. Under his leadership, the company focuses on integrating biometric data analysis with wearable technology to enhance outdoor experiences.
Research Focus and Techniques
Warren Pettine specializes in building dynamical neural networks and algorithmic reinforcement learning models based on neurophysiological data. He applies techniques from computational psychiatry to investigate altered decision-making processes in conditions such as autism spectrum disorder, contributing to the understanding of these complex issues.