1). Addictive screen use and youth suicide
2). Social determinants of youth mental health
3). NLP-based suicide risk detection
4). Policy impacts on child suicide trends
The X_PLORE Lab leverages machine learning, NLP, and causal inference to investigate youth mental health, suicide prevention, and social determinants of health using large-scale population and digital data.
Dr. Xiao's research program centers on understanding and preventing youth mental health crises through innovative computational and epidemiological approaches. Her work spans three interconnected areas: (1) identifying how social determinants of health, including structural racism, economic deprivation, and digital environments, shape mental health trajectories in young people; (2) developing and applying machine learning and natural language processing methods to detect risk patterns in large-scale clinical, survey, and digital datasets; and (3) leveraging causal inference frameworks to evaluate the impact of policies and interventions on youth suicide and related outcomes.
A major line of her work examines the role of digital technology, particularly addictive patterns of screen use, in adolescent suicidal behavior. Her landmark JAMA 2025 study identified distinct trajectories of addictive screen use and their associations with suicidal outcomes using nationally representative longitudinal data from the ABCD Study. She has also advanced methods for analyzing social determinants at both individual and community levels, with publications in Nature Mental Health characterizing county-level clusters of social vulnerability linked to suicide mortality, and in JAMA Pediatrics examining individual-level patterns of social disadvantage and child health.
Dr. Xiao's research is supported by the NIH, the Google Research Scholar Program, and the Bill & Melinda Gates Foundation. She has authored over 90 peer-reviewed publications and collaborates across disciplines with investigators in psychiatry, epidemiology, computer science, and social work.
Figure 1.
Biography
Yunyu Xiao, PhD, is an Assistant Professor in the Departments of Population Health Sciences and Psychiatry at Weill Cornell Medicine and Director of the X_PLORE Lab. Her research integrates computational methods, including machine learning and natural language processing, with causal inference to study youth mental health, suicide prevention, and social determinants of health. Her work has been published in JAMA, JAMA Psychiatry, Nature Mental Health, and other leading journals, and is supported by NIH, the Google Research Scholar Program, and the Bill & Melinda Gates Foundation. She teaches graduate courses in health informatics.
Distinctions:
Elected Associate Member, American College of Neuropsychopharmacology (ACNP)
Google Research Scholar Award
NIH R01 Principal Investigator
Bill & Melinda Gates Foundation Grant Recipient
Invited panelist, UN General Assembly luncheon on youth digital wellbeing
Invited panelist, WPA World Congress of Psychiatry 2026
Founded and directs the X_PLORE Lab at Weill Cornell Medicine
90+ peer-reviewed publications in JAMA, JAMA Psychiatry, Nature Mental Health
