Andrew Lowy (alowy@wisc.edu, https://sites.google.com/view/andrewlowy) joined the University of Wisconsin-Madison (UW-Madison) in September 2023 as an IFDS postdoc with Stephen J. Wright. Before joining IFDS at UW-Madison, he obtained his PhD in Applied Math at University of Southern California under the supervision of Meisam Razaviyayn, where he was awarded the 2023 Center for Applied Mathematical Sciences (CAMS) Graduate Student Prize for excellence in research with a substantial mathematical component.
Andrew’s research interests lie in trustworthy machine learning and optimization, with a focus on privacy, fairness, and robustness. His main area of expertise is differentially private optimization for machine learning. Andrew’s work characterises the fundamental statistical and computational limits of differentially private optimization problems that arise in modern machine learning. He also develops scalable optimization algorithms that attain these limits.