Sarah Yip, PhD

Sarah Yip applies neuropsychiatric research methods to uncover brain-based computational mechanisms underlying psychiatric disorders, with a focus on processes of risk and recovery. Her work integrates advanced neuroimaging analyses to examine large-scale brain system dynamics, along with machine learning approaches to identify predictive neural markers of clinical outcomes. She also collects neuroimaging data across a range of cognitive states, including those induced by acute drug challenges and within-scanner task manipulations. In collaboration with Christopher Pittenger and Godfrey Pearlson, Yip serves as a multiple principal investigator on a large U01 award at Yale as part of the NIH’s Individually Measured Phenotypes to Advance Computational Translation in Mental Health (IMPACT-MH) initiative. This interdisciplinary project is recruiting and longitudinally phenotyping a transdiagnostic cohort of 2,400 individuals, using computational behavioral tasks, natural language processing, and clinical assessments. Her work aligns with broader efforts to integrate neuroscientific research across multiple levels of analysis.

biomarkers ;  clinical trials ;  computational modeling ;  functional magnetic resonance imaging ;  pharmacology  

cognitive neuroscience ;  computational neuroscience ;  computational psychiatry ;  connectivity ;  development ;  machine learning ;  mental health ;  reward  

Yip received her undergraduate training in Psychology from NYU, a master's in developmental neuroscience from University College London, and a PhD in Psychiatry from the University of Oxford. She joined Yale as a postdoctoral fellow in 2013 and began directing her own independent lab, the Yale Imaging and Psychopharmacology (YIP) lab, in 2016. In her spare time, she enjoys playing with her dog, Kaiya.