Regular biography
Amit Singer is a Professor in the Department of Mathematics at Princeton University. His research interests include areas such as geometry, topology, and data science. Professor Singer's work focuses on the mathematical foundations of shape analysis, manifold learning, and spectral geometry. He is affiliated with Fine Hall and can be contacted at amits@math.princeton.edu. His profile page provides additional information about his academic contributions and research activities.
Scholar-generated biography
Amit Singer is a researcher at Princeton University with expertise in Applied Mathematics and Cryo-Electron Microscopy. His work focuses on mathematical methods for structure determination, particularly in the context of cryo-EM. He has contributed to the development of algorithms for angular synchronization, eigenvector-based methods, and semidefinite programming. His research also addresses problems in graph theory, manifold learning, and diffusion maps. Singer's publications explore topics such as motion estimation, sensor network localization, and the analysis of stochastic dynamical systems. His work bridges theoretical mathematics with practical applications in imaging and data analysis.