-------------------------------- --- james ashton nichols ------- -------------------------------- --- mathematics ---------------- --- music, ibis ---------------- --------------------------------
twitter: @james_nichols email: firstname dot lastname at anu.edu.au
--- moi --- ----------- I'm a at the Australian National University. I'm interested in approximation, numerical analysis, high dimensional problems, fractional & stochastic partial differential equations, stochastic processes, and statistical learning. Before my doctoral studies I was a quantative analyst at Macquarie Bank, Sydney Australia. I completed my Ph.D in 2014 with Ian Sloan and Frances Kuo, at UNSW, Sydney, Australia. I did my postdoc at the Laboratoire Jacques-Louis Lions, Sorbonnes Université, with Albert Cohen. I play some banjo and a bit of piano. I try to code elegantly. I love riding and tinkering with bikes. See my GitHub (although a lot of my code has gone to GitLab lately) Google Scholar --- teaching --- ---------------- o Semester 2 2021 I am teaching MATH 3349/4349 Computational Optimal Transport. This is a "special topics" advanced/graduate course that I am writing based largely on Peyré and Cuturi's book. Some online materials will be available shortly. o Semester 1 2021 I am teaching MATH 3062/6116 Fractal Geometry and Chaotic Dynamics --- recent publications --- --------------------------- o A General Framework for Fractional Order Compartment Models CN Angstmann, AM Erickson, BI Henry, AV McGann, JM Murray, JA Nichols SIAM Review, 2021 o Coarse reduced model selection for nonlinear state estimation JA Nichols Submitted, 2021 o Nonlinear reduced models for state and parameter estimation A Cohen, W Dahmen, O Mula, JA Nichols Submitted, 2020 o Reduced basis greedy selection using random training sets A Cohen, W Dahmen, R DeVore, JA Nichols ESAIM: M2AN, 2020 o Optimal reduced model algorithms for data-based state estimation (arXiv) A Cohen, W Dahmen, R DeVore, J Fadili, O Mula, JA Nichols SIAM Numer. Anal., 2020 o Greedy algorithms for optimal measurements selection in state estimation using reduced models (pdf) P Binev, A Cohen, O Mula, JA Nichols SIAM/ASA Journal of Uncertainty Quantification, 2018 o Subdiffusive discrete time random walks via Monte Carlo and subordination (arXiv) JA Nichols, BI Henry, CN Angstmann Journal of Computational Physics, 2018 o Ph.D Thesis --- music --- ------------- Svelt Infosthetic Orchestra Brackets (RIP) The Henchmen (RIP) --- projects --- ---------------- Malcolm Turnbot The Dubtable Pattern Machine Book-Bike-Machine Pia van Gelder's Psychic Synth