{"id":3146,"date":"2024-11-04T17:33:50","date_gmt":"2024-11-04T22:33:50","guid":{"rendered":"https:\/\/engineering.jhu.edu\/doctor-of-engineering\/faculty\/eric-nalisnick\/"},"modified":"2026-03-04T15:08:59","modified_gmt":"2026-03-04T20:08:59","slug":"eric-nalisnick","status":"publish","type":"people","link":"https:\/\/engineering.jhu.edu\/doctor-of-engineering\/faculty\/eric-nalisnick\/","title":{"rendered":"Eric Nalisnick"},"content":{"rendered":"

Eric Nalisnick is an assistant professor of computer science at the Johns Hopkins University. He is also a member of the Data Science and AI Institute. In his work, he aims to build safe and robust intelligent systems. To this end, Nalisnick develops statistical machine learning methods that allow such systems to quantify their uncertainty and to interact with human experts. His research also applies these methodological innovations to problems in health care, computer vision, and sign language processing.<\/p>\n

Nalisnick received a PhD from the University of California, Irvine (2018) and MS and BS degrees from Lehigh University in 2012 and 2013, respectively. Before joining Johns Hopkins, he was an assistant professor at the University of Amsterdam and a postdoctoral researcher at the University of Cambridge; he has also worked in research roles at Google DeepMind, Microsoft, Amazon, and Twitter.<\/p>\n

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