Shirley Wang, PhD

ental health disorders are incredibly complex and dynamic phenomena that vary within people, between people, and across time. Shirley Wang's research program aims to develop and harness novel methods that can capture and model this complexity, with a focus on suicide, nonsuicidal self-injury, and eating disorders. The Computational Clinical Science (CCS) Lab integrates methods from across the clinical and computational sciences, including machine learning, mathematical modeling, and digital phenotyping (e.g., via smartphones and wearables). A central focus of this work is on formalizing theories of psychopathology, and modeling the real-time dynamics of symptoms (and their contexts) as they unfold in people’s daily lives. Ultimately, they aim to use these models to inform the development of scalable, effective, and personalized interventions.

behavioral testing ;  computational modeling ;  network analysis ;  simulation ;  statistical methods ;  wearable devices ;  language models  

computational psychiatry ;  decision-making ;  emotion ;  machine learning ;  mental health ;  natural language processing ;  stress  

Shirley Wang received her BA in Psychology from The College of New Jersey (2017), her Ph.D. in Clinical Psychology and Computational Science and Engineering from Harvard University (2024), and completed her clinical internship at Massachusetts General Hospital/Harvard Medical School (2024). She started her lab in 2024 in the Department of Psychology at Yale University. Outside of the lab, Shirley enjoys running, figure skating, dramatic TV shows, and trying to keep her plants alive.