Eric Nalisnick is an assistant professor at Johns Hopkins University. His research interests span statistical machine learning and probabilistic modeling, with an emphasis on quantifying uncertainty in deep learning, human-AI collaboration, specifying prior knowledge, and detecting distribution shift. He previously was an assistant professor at the University of Amsterdam, a postdoctoral researcher at the University of Cambridge and a PhD student at the University of California, Irvine. Eric has also held research positions at DeepMind, Microsoft, Twitter, and Amazon. His work has received funding from both industrial (Google, Amazon, Bosch) and government (Dutch Research Council) entities, and his papers have been recognized with selective oral presentations (ECCV 2024) and awards (AIStats 2023, AIStats 2024).