Center Affiliated Investigators

This page includes investigators who are affliated with NYU Silver's Constance and Martin Silver Center on Data Science and Social Equity (C+M Silver Center). 

Katharina Schultebraucks headshotKatharina Schultebraucks

Co-Director, Computational Psychiatry Program and Associate Professor, Department of Psychiatry and Population Health, NYU Grossmann School of Medicine

Since early in her dissertation project, Katharina Schultebraucks’ research has focused on studying mental disorders from a translational point of view by examining primary behavioral functions and dysfunction of various neuroendocrine, molecular, cellular, and genetic pathways from an integrative, multi-systems point of view. 

Dr. Schultebraucks completed her PhD in the Department of Psychiatry and Psychotherapy at the Charité – Universitätsmedizin Berlin in Germany and the Department of Psychology at the Free University, Berlin (degree: summa cum laude – graduate with honors). She did her postdoctoral fellowship in the Department of Psychiatry at NYU Grossman School of Medicine and was the Florence Irving Assistant Professor and Director of Computational Medicine and Artificial Intelligence in the Department of Emergency Medicine and Psychiatry at Columbia University before joining NYU in January 2023. She is currently Co-Director of the Computational Psychiatry Program and Associate Professor in the Department of Psychiatry and in the Division of Healthcare Delivery Science, Department of Population Health at NYU Grossmann School of Medicine.

Dr. Schultebraucks investigates longitudinal and prospective studies to identify complex sets of early predictors. Her primary research focus is centered on precision psychiatry by applying advanced computational methods to improve individualized risk stratification and individualized treatment allocation, leading to publications in Nature Medicine, JAMA Psychiatry, and Molecular Psychiatry as the first and corresponding author. It is important to ensure the accuracy and generalizability of machine learning algorithms, in particular, whether the algorithm provide fair and equitable risk stratification and treatment assignment. Dr. Schultebraucks has been awarded several awards and national and international grants, e.g., she is currently the PI of two R01s funded by the National Institutes of Health (NIH) and PI of a multicenter grant funded by the Swiss National Science Foundation.