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Department of Applied Mathematics and Theoretical Physics

I am a Research Fellow in Numerical Analysis.

My research interests lie at the intersection between numerical analysis and deep learning. I primarily focus on the mathematical foundations of deep learning to discover mathematical models (partial differential equations) from data, and the development of novel and theoretically justified numerical techniques.

I am a member of the Scientific Artificial Intelligence (SciAI) Center supported by the Office of Naval Research (ONR).

Publications

Control of Bifurcation Structures using Shape Optimization
N Boullé, PE Farrell, A Paganini
– SIAM Journal on Scientific Computing
(2022)
44,
A57
Accurate numerical simulation of electrodiffusion and water movement in brain tissue.
AJ Ellingsrud, N Boullé, PE Farrell, ME Rognes
– Mathematical Medicine and Biology
(2021)
38,
516
Control of bifurcation structures using shape optimization
N Boullé, PE Farrell, A Paganini
(2021)
A generalization of the randomized singular value decomposition
N Boullé, A Townsend
(2021)
Data-driven discovery of Green's functions with human-understandable deep learning
N Boullé, CJ Earls, A Townsend
(2021)
An optimal complexity spectral method for Navier--Stokes simulations in the ball
N Boullé, J Słomka, A Townsend
(2021)
Bifurcation analysis of two-dimensional Rayleigh--Bénard convection using deflation
N Boullé, V Dallas, PE Farrell
(2021)
Accurate numerical simulation of electrodiffusion and water movement in brain tissue
AJ Ellingsrud, N Boullé, PE Farrell, ME Rognes
(2021)
Learning elliptic partial differential equations with randomized linear algebra
N Boullé, A Townsend
(2021)
Deflation-based identification of nonlinear excitations of the three-dimensional Gross-Pitaevskii equation
N Boullé, EG Charalampidis, PE Farrell, PG Kevrekidis
– Physical Review A
(2020)
102,
053307
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Research Group

Cambridge Image Analysis

Room

F2.05

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