Amit Moscovich Eiger

Dr. Amit Moscovich Eiger is a Senior Lecturer (tenure-track Assistant Professor) in the Department of Statistics and Operations Research at the School of Mathematical Sciences, Tel Aviv University, where he has been employed since 2021. Prior to this position, he was a Postdoctoral Research Associate in the Program in Applied and Computational Mathematics (PACM) at Princeton University (2018-2021) and a Postdoctoral Fellow at the School of Mathematical Sciences, Tel Aviv University (2017-2018).

His educational background includes:

• Ph.D. (direct track) in the Department of Computer Science and Applied Mathematics, Weizmann Institute of Science, 2016
• Physics and mathematics studies, the Hebrew University of Jerusalem, 2008
• B.A. in computer science, the Open University of Israel, 2003

Dr. Moscovich Eiger's research focuses on developing methodology for statistics and machine learning, with particular emphasis on tools for mapping and analyzing large volumetric datasets. His work is motivated by key challenges in structural biology, specifically the 3D reconstruction and analysis of flexible proteins and other macromolecules from cryo-electron microscopy data. His research spans geometric estimation problems, manifold learning, computational statistics, and machine learning applications in biological imaging.

Analysis of his recent publications reveals a strong focus on applying manifold learning techniques to structural biology problems, particularly cryo-EM data analysis. His work bridges theoretical statistics and practical computational methods, with significant contributions to handling heterogeneity in biological structures, developing fast algorithms for statistical computations, and creating novel approaches for analyzing protein conformations. A notable trend is the integration of optimal transport theory with manifold learning for biological applications.

His scientific achievements include:

• Joseph Putter Ph.D. dissertation award, awarded by the Israeli Statistical Association, 2017

Dr. Moscovich Eiger is actively involved in mentoring graduate students, currently supervising multiple Ph.D. and M.Sc. students in statistics, data science, and operations research. His research is supported by prestigious funding sources including the Israel Science Foundation (ISF), the United States-Israel Binational Science Foundation (BSF), and the United States National Science Foundation (NSF).

He leads a research group focused on computational methods for structural biology, particularly developing algorithms for cryo-electron microscopy data analysis. His team collaborates with researchers from institutions including Princeton University, Duke University, Hebrew University of Jerusalem, and KTH Royal Institute of Technology, creating a strong interdisciplinary network for advancing computational approaches in structural biology.