Personal information
Biography
Amit Singer is a Professor of Mathematics, the Director of the Program in Applied and Computational Mathematics (PACM), and a member of the Executive Committee for the Center for Statistics and Machine Learning (CSML) at Princeton University.
Singer received both the undergraduate degree in Physics and Mathematics (1997) and the PhD degree (2005) in Applied Mathematics from Tel Aviv University. He was a Gibbs Assistant Professor in Applied Mathematics at Yale University (2005-2008) before joining Princeton University as an Assistant Professor in 2008.
Singer works on a broad range of problems in applied mathematics, focusing on theoretical and computational aspects of data science, and on developing computational methods for structural biology. Among the areas to which he has contributed are cryo-electron microscopy (cryo-EM), computer vision, image analysis, diffusion maps, random graph theory, sensor networks, graph Laplacians, and diffusion processes. He works with a widely varied group of collaborators and graduate students in several disciplines, and his work is increasing the range of applicable mathematics.
Singer leads a research group that develops the mathematical foundation, algorithms, and open-source software for visualizing three-dimensional biological macromolecules using cryo-EM, an entirely general imaging method that unlike X-ray crystallography does not require crystallization, can capture molecules in their native states, and even map their conformational changes and flexible motions.
Singer’s list of prizes and honors includes SIAM Fellow (2022), the Simons Math+X Investigator Award (2017), a National Finalist for Blavatnik Awards for Young Scientists (2016), Moore Investigator in Data-Driven Discovery (2014), Simons Investigator Award (2012), Presidential Early Career Award for Scientists and Engineers (2010), the Alfred P. Sloan Research Fellowship (2010), and the Haim Nessyahu Prize for Best PhD in Mathematics in Israel (2007).