Computational Psychology — AI for Mental Health and Well-Being
I am a computational social scientist developing AI systems that support mental health and well-being, and studying the impact of AI on society. In fall 2026, I am joining UCLA Anderson as an Assistant Professor of Behavioral Decision Making. Since 2020, I have been an Assistant Professor of Psychology at Stanford and the Shriram Faculty Fellow at the Institute for Human-Centered Artificial Intelligence.
I co-direct the $11M Stanford-UCLA CREATE Center for AI therapy and lead the Computational Psychology and Well-Being Lab. We are studying how LLMs can safely support therapist training and patients between sessions, and are evaluating these systems in clinical trials. We also study how LLMs may shape society, including their capacity for political persuasion.
In 2011, I co-founded the World Well-Being Project at the University of Pennsylvania, which has since become a big-data psychology consortium. We have pioneered methods of psychological text analysis. Specifically, we use social media (Facebook, Twitter, Reddit, …) to measure the psychological states of populations and individuals. This lets us understand the thoughts and behaviors that shape physical illness (like heart disease) and depression, or support psychological well-being. Recently, we’ve used social media as an early warning system for the opioid epidemic to help health officials allocate overdose medications.
Large-scale text analysis can complement surveys by providing frequent, geographically detailed estimates of population psychology. These methods can track the effects of economic and social disruptions and support real-time population-health monitoring. For this reason, scientists need continued access to these “digital commons” — they should not be locked up by tech companies.