Visiting Speaker ~ Johannes Eichstaedt, PhD, Stanford University

Guest Speaker ~ Johannes Eichstaedt Assistant Professor in Psychology, Stanford University

Title: Measuring and Improving Mental Health through Digital Text and Large Language Models.

Abstract: Language shared online—through social media or messaging—reflects people's thoughts and emotions. Processing this data with Natural Language Processing (NLP) and machine learning can reveal mental health and psychological traits. For example, analyzing Facebook posts enables me to predict depression before it is clinically diagnosed and pinpoint particular symptoms. At the population level, billions of geo-tagged Tweets can be used to monitor health risk patterns, including depression and anxiety trends across communities. Beyond assessment, I'm leveraging Large Language Models (LLMs) to improve mental health care, including training therapists and assisting with Cognitive Behavioral Therapy. These applications of NLP and AI may lead to earlier and more effective interventions and improved access for underserved populations.

Bio: Johannes Eichstaedt is an Assistant Professor in Psychology at Stanford and a Shriram Faculty Fellow at the Institute for Human-Centered A.I. He uses Natural Language Processing and social media data to assess and study mental health. His lab builds Large Language Model interventions to deliver mental health care, from training therapists to assisting patients. In 2011, he co-founded the World Well-Being Project, now a consortium of psychology and computer science labs across five universities. Originally trained as a physicist, Johannes received his Ph.D. and clinical training at the University of Pennsylvania. Johannes was elected a rising star and emerging leader by three scientific organizations, has published 85+ articles, and has served as an expert for the United Nations and several governments.