Amit Singer is a Professor of Mathematics at Princeton University. Singer is also a member of the Executive Committee of the Program in Applied and Computational Mathematics (PACM) and of the Executive Committee for the Center for Statistics and Machine Learning (CSML) at Princeton University. Singer’s current research is focused on developing algorithms for three-dimensional structuring of macromolecules using cryo-electron microscopy. Singer’s mathematical interests include mathematical methods for data analysis, specifically, linear and non-linear dimensionality reduction of high dimensional data, signal and image processing, spectral methods, convex optimization and semidefinite programming. Singer has also contributed to the applications of cryo-EM, NMR spectroscopy, structure from motion problem in computer vision, and permeation of ions through protein channels. He has been awarded the Moore Investigator in Data-Driven Discovery Award, the Simons Investigator Award, the Presidential Early Career Award for Scientists and Engineers, the Alfred P. Sloan Research Fellowship and the Haim Nessyahu Prize in Mathematics. Singer holds a Ph.D. in Applied Mathematics and a B.Sc. In Physics and Mathematics from Tel Aviv University.