nicholas m. boffi

I am an assistant professor in the Department of Mathematical Sciences and an affiliated faculty member in the Machine Learning Department at Carnegie Mellon University. I am also a member of the Center for Nonlinear Analysis.

I am broadly interested in machine learning and computational mathematics. My current research interests center on generative models and their application to high-dimensional problems in scientific computing; I am particularly interested in problems that cannot be solved with standard numerical techniques but which can be solved using machine learning. My work draws inspiration from many areas of applied mathematics, including numerical analysis, partial differential equations, dynamical systems and control theory, stochastic processes, probability, and optimization.

Here is my CV, up to date as of 8/20/24.

I am looking for highly-motivated PhD students interested in work at the intersection of applied mathematics and machine learning. If you are a PhD student at CMU in machine learning or in mathematics, or if you are interested in applying to one of these PhD programs, please send me an email with your CV and a short description of your research interests.

I can be reached at nboffi at andrew dot cmu dot edu.

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I was a Courant Instructor at the Courant Institute of Mathematical Sciences from 2021-2024, where I worked primarily with Eric Vanden-Eijnden.

I completed my PhD at Harvard University in applied mathematics, where I was co-advised by Jean-Jacques Slotine and Chris Rycroft. I also collaborated with Ariel Amir. I spent roughly half of my time at Harvard and half of my time at MIT. My thesis work focused on various problems in computational mathematics and machine learning, including adaptive control and learning in nonlinear dynamical systems, numerical method development for partial differential equations, and stochastic simulation of evolutionary dynamics.

During the last year of my PhD, I was also a student researcher at Google Brain, where I had the pleasure of working with Vikas Sindhwani and Stephen Tu.

From 2015-2019, my research was funded by a Department of Energy Computational Science Graduate Fellowship. I spent my practicum at Lawrence Berkeley National Lab.

From 2014-2015, I was a Fulbright Scholar at Tel Aviv University. While there, I focused on the development of numerical methods for quantum chemistry.

Before graduate school, I was an undergraduate at Northwestern University, where I studied mathematics, physics, and integrated science. I spent four wonderful years working on problems in theoretical chemistry with Tamar Seideman.