About me

Noah Jones is a second year Ph.D Student advised by Dr. Rosalind Picard. His research interests are causal modeling, risk forecasting, conformal prediction, and transfer learning to support consequential decision making and machine learning for healthcare applications. Noah is also passionate about meta science for improving the replicability, generalizability and predictive power of clinical science.

Noah received an S.M in Computational Social Science at MIT. In the past, he worked as a lead machine learning engineer for Rallypoint, research assistant for Neurolex.AI and lab manager in the Department of Psychiatry at Wake Forest School of Medicine.

Featured Publications

Jones N., Healey E., Zhai S., Shih M., Khalilal S., Sontag D., Treatment Efficacy and Adverse Effect Profile of First-line Treatments versus Alternative Antibiotics in Patients with Uncomplicated Urinary Tract Infection: A Retrospective Cohort Study Using Machine Learning with Causal Inference (2022), Journal of the American Medical Association, (Submitted for Review July 2022)