How can we use modern AI architectures to detect generalizable health patterns in physiological data? We perform basic algorithmic research on time series models.
How are attention, learning and memory impacted in autism, ADHD, and with aging or dementia? We investigate this through modeling, behavioral tasks and analysis of wearable device data.
How do we use computational tools to improve healthcare? We translate our findings into usable tools, and work with industry to bring AI/ML methods to real-world problems.
<aside> <img src="https://prod-files-secure.s3.us-west-2.amazonaws.com/9e458944-47ec-4bc8-abcf-686bf94400ad/f4791443-1978-444e-b14c-365faa6718da/Rectangle_2.png" alt="https://prod-files-secure.s3.us-west-2.amazonaws.com/9e458944-47ec-4bc8-abcf-686bf94400ad/f4791443-1978-444e-b14c-365faa6718da/Rectangle_2.png" width="40px" /> A message from the Principal Investigator
It’s about being curious, it’s about working hard and having fun. We use modern machine learning algorithms, classical statistical analyses, computational simulations and digital health tools to advance our fundamental understanding of neuropsychiatric disease. We let the questions and findings dictate where we go.
Warren Woodrich Pettine, M.D.
Assistant Professor Huntsman Mental Health Institute Scientific Computing and Imaging Institute University of Utah
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Warren, an Assistant Professor at the University of Utah and Co-Founder/CEO of MTN, leads a highly collaborative research program focused on the development of advanced computational methods to aid those with neuropsychiatric disease. His cognitive neuroscience work explores how attention shapes decisions during learning and metacognitive monitoring, employing a diverse array of methods including cognitive simulations, online games, algorithmic reinforcement learning, and various behavioral analyses. Warren is also heavily involved in advancing medical AI, particularly in developing algorithms to detect complex health patterns in physiological data.
At the core of Warren's research is a commitment to interdisciplinary collaboration, working closely with clinicians and experimentalists to advance understanding in this complex field. His approach is characterized by wide-ranging explorations that push the boundaries of current knowledge. Beyond his scientific pursuits, Dr. Pettine is deeply committed to mentorship and fostering a positive research environment, reflecting his dedication to nurturing the next generation of researchers.
A list of his publications can be found here.
Tweets @warrenwpettine.
Ioanna is co-chief Resident of the Research Track Psychiatry Residency Program. She is working with Dr. Pettine to investigate the relationship between reaction times and cognitive strategy, as well as on investigating the use of Computational Psychiatry tools in the clinic.
Eun Tack is a Ph.D. student in the Dartmouth College department of Neurobiology. He is working with Dr. Pettine on developing theoretical models of how attention and memory are represented in the brain
Rahat is a Ph.D. student in the computer science department at the University of Utah. He is working with Dr. Pettine to develop an online game for detailed computational phenotyping of attention and learning.
Braedon is a high school student at Golden High School in Colorado. He is working with Dr. Pettine to develop a computational phenotyping tool, as well as methods for algorithmic reinforcement learning.
