Department of Psychiatry and Human Behavior

Gabrielle Reimann pursued her clinical science doctorate at Vanderbilt University under the mentorship of Dr. Antonia Kaczkurkin. Here, she developed computational and machine learning tools to capture comorbidity, transdiagnostic symptoms, and other sources of psychiatric complexity at the symptom and neurobiological levels, with the aim of identifying biomarkers to improve mental health diagnosis. Her work has been recognized by the National Science Foundation Graduate Research Fellowship Program, American Psychological Association Junior Scientist Fellowship, and the Data Science For All national fellowship. As a graduate student, Gabrielle was the first clinical psychology Ph.D. student to earn an internship with the NIMH Machine Learning Team, funded through the Ethel M. Wilson Fellowship and the Vanderbilt Award for Doctoral Discovery. In 2025, Gabrielle began her clinical psychology pre-doctoral internship within the Adult Track at The Warren Alpert Medical School of Brown University. During internship, she worked with Dr. Christopher Hughes to build deep learning models to predict post-hospitalization suicide risk. She is thrilled to continue on to Yale University as the 2026 Susan Nolen-Hoeksema Postdoctoral Fellow. Under the mentorship of Dr. Shirley Wang, Gabrielle will continue to leverage computational modeling and emerging technologies to support clinical decision-making. Prior to graduate school, Gabrielle completed her B.S. in psychology at James Madison University and her post-baccalaureate training at the National Institutes of Health. Gabrielle would like to thank her husband, friends, family, colleagues, and mentors for their support throughout this journey.