Weber awarded Leslie Fox Prize in Numerical Analysis

Melanie Weber, Assistant Professor of Applied Mathematics and of Computer Science at the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS), was recently awarded the Leslie Fox Prize from the Institute of Mathematics and its Applications (IMA). The prize honors up-and-coming numerical analysts under the age of 31. Shortlisted candidates present lectures at the IMA Leslie Fox Prize meeting and the award is given based on “mathematical and algorithmic brilliance in tandem with presentational skills.”

At the conference, Weber presented her work on a class of algorithms for constrained optimization on geometric domains and discussed how exploiting geometric structure in data can lead to more efficient algorithms.

Many applications in machine learning and data science include data and models with geometric structure. Often those applications require performing optimization tasks on geometric domains, which creates a need for geometric optimization algorithms.  At SEAS, Weber’s research focuses on utilizing geometric structure in data for the design of efficient machine learning and optimization methods. 

She received her Ph.D. from Princeton University and her undergraduate degree from the University of Leipzig. Prior to joining Harvard, Weber was a Hooke Research Fellow at the University of Oxford. She has held visiting research appointments at MIT, the Max Planck Institute for Mathematics in the Sciences, as well as the Simons Institute in Berkeley.