Seminar: • Leveraging Digital Behavioral Signals for AI-powered Mental Health Assessment, Prediction, and Intervention
Subigya Nepal
Postdoctoral Fellow
Stanford Institute for Human-Centered AI
Monday, March 17
9:30 - 10:30AM
1100 Torgersen Hall
Abstract
Mental health conditions affect millions globally, yet traditional assessment methods rely on sporadic clinical visits that may miss important behavioral changes. This talk presents a technological approach to mental wellness through three components: behavioral understanding, prediction, and intervention. I will discuss findings from a longitudinal mobile sensing study that tracked college students' behaviors through the COVID-19 pandemic, and present MoodCapture, a system for studying naturalistic facial expressions during phone use. The talk will conclude by demonstrating two intervention platforms: mSITE, designed for enhancing social interaction in serious mental illness, and MindScape, a context-aware journaling tool that combines behavioral sensing with AI. These studies collectively illustrate the potential of ubiquitous computing and AI in creating scalable, privacy-conscious solutions for mental healthcare.
Biography
Dr. Subigya Nepal is a Postdoctoral Fellow at Stanford Institute for Human-Centered AI working at the intersection of AI, ubiquitous computing and mental health. His research focuses on developing technologies that understand and enhance mental wellbeing through everyday devices. He has led several foundational studies in mobile sensing - including the longest-running study of its kind - to uncover patterns in mental health and behavior, while developing tools for passive sensing and context-aware interventions. His work, published in top venues like ACM UbiComp, CHI, and CSCW, has received distinguished paper awards and been featured in The Washington Post, Bloomberg, and The Times UK. His research aims to bridge the gap between technological innovation and accessible mental healthcare through evidence-based, human-centered approaches. He completed his PhD in Computer Science from Dartmouth College in 2024 and has spent two summers as a research intern at Microsoft Research working on workplace wellbeing.