Natalie Lang

Natalie Lang is a postdoctoral associate at the University of Maryland Institute for Advanced Computer Studies (UMIACS) working with Dana Dachman-Soled. Lang’s research is centered on the foundational challenge of reconciling high-performance machine learning with robust data privacy. Her work investigates the development of secure computation frameworks that enable the training of complex models over encrypted datasets, effectively decoupling the utility of sensitive information from the risks of data exposure.