nicholas m. boffi
I am a Courant Instructor / Assistant Professor of applied mathematics at the Courant Institute of Mathematical Sciences, where I work primarily with Eric Vanden-Eijnden. I completed my PhD at Harvard University in applied mathematics, advised by Jean-Jacques Slotine (MIT) and Chris Rycroft (Harvard). 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 (DOE CSGF); I spent my practicum at Lawrence Berkeley National Lab.
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. From 2014-2015, I was a Fulbright Scholar at Tel Aviv University, focusing on the development of numerical methods for quantum chemistry.
I can be reached at boffi at cims dot nyu dot edu.
research interests
I am an applied and computational mathematician. My current research centers on learning dynamical systems for high-dimensional scientific computing and generative modeling; these fascinating areas are linked by the study of dynamical transport of measure. Previously, I worked on online learning algorithms for real-time (adaptive) control of dynamical systems, as well as numerical method development for the simulation of disordered, biological, and quantum systems.
My research draws on techniques from numerical analysis, dynamical systems, probability, and optimization to design, implement, and analyze new algorithms with provable guarantees.
In September 2024, I will join Carnegie Mellon University as a tenure-track assistant professor in mathematics and as an affiliated faculty member in the machine learning department.
teaching
NYU Courant, Spring 2024: Honors Numerical Analysis
NYU Courant, Fall 2023: Linear and Nonlinear Optimization
NYU Courant, Spring 2023: Linear and Nonlinear Optimization
NYU Courant, Fall 2022: Numerical Analysis
NYU Courant, Spring 2022: Linear and Nonlinear Optimization
NYU Courant, Fall 2021: Numerical Analysis
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