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Nicholas Higham
PeerJ Editor & Author
1,440 Points

Contributions by role

Author 405
Editor 1,035

Contributions by subject area

Algorithms and Analysis of Algorithms
Data Science
Scientific Computing and Simulation
Computer Architecture
Distributed and Parallel Computing
Databases
Optimization Theory and Computation
Programming Languages
Software Engineering
Bioinformatics
Data Mining and Machine Learning
Digital Libraries
Computer Aided Design
Computer Vision
Theory and Formal Methods

Nicholas J Higham

PeerJ Editor & Author

Summary

My research is largely concerned with the development and analysis of algorithms in numerical linear algebra. The second edition of my monograph on this topic was published by the Society for Industrial and Applied Mathematics (SIAM) in 2002. My other books include Functions of Matrices: Theory and Computation (SIAM, 2008) and The Princeton Companion to Applied Mathematics (2015), of which I am editor. I am a Fellow of the Royal Society, a SIAM Fellow, and a Member of Academia Europaea. I blog at https://nhigham.com

Algorithms & Analysis of Algorithms Data Science Optimization Theory & Computation Scientific Computing & Simulation Software Engineering

Editorial Board Member

PeerJ Computer Science

Past or current institution affiliations

The University of Manchester

Work details

Royal Society Research Professor and Richardson Professor of Applied Mathematics

The University of Manchester.
School of Mathematics

Websites

  • Google Scholar
  • GitHub
  • Nick Higham's blog
  • ResearcherID
  • ORCID
  • Numerical Linear Algebra Group
  • Personal website

PeerJ Contributions

  • Articles 3
  • Edited 7
January 17, 2022
Performance impact of precision reduction in sparse linear systems solvers
Mawussi Zounon, Nicholas J. Higham, Craig Lucas, Françoise Tisseur
https://doi.org/10.7717/peerj-cs.778
February 10, 2021
Numerical behavior of NVIDIA tensor cores
Massimiliano Fasi, Nicholas J. Higham, Mantas Mikaitis, Srikara Pranesh
https://doi.org/10.7717/peerj-cs.330
April 6, 2016
Matrix Depot: an extensible test matrix collection for Julia
Weijian Zhang, Nicholas J. Higham
https://doi.org/10.7717/peerj-cs.58

Academic Editor on

March 29, 2023
Automatic differentiation of uncertainties: an interval computational differentiation for first and higher derivatives with implementation
Hend Dawood, Nefertiti Megahed
https://doi.org/10.7717/peerj-cs.1301
January 20, 2022
A hyper-matheuristic approach for solving mixed integer linear optimization models in the context of data envelopment analysis
Martin Gonzalez, Jose J. López-Espín, Juan Aparicio, El-Ghazali Talbi
https://doi.org/10.7717/peerj-cs.828
May 18, 2020
Influence of tweets and diversification on serendipitous research paper recommender systems
Chifumi Nishioka, Jörn Hauke, Ansgar Scherp
https://doi.org/10.7717/peerj-cs.273
April 30, 2018
Computing the sparse matrix vector product using block-based kernels without zero padding on processors with AVX-512 instructions
Bérenger Bramas, Pavel Kus
https://doi.org/10.7717/peerj-cs.151
April 2, 2018
AutoWIG: automatic generation of python bindings for C++ libraries
Pierre Fernique, Christophe Pradal
https://doi.org/10.7717/peerj-cs.149
January 2, 2017
SymPy: symbolic computing in Python
Aaron Meurer, Christopher P. Smith, Mateusz Paprocki, Ondřej Čertík, Sergey B. Kirpichev, Matthew Rocklin, AMiT Kumar, Sergiu Ivanov, Jason K. Moore, Sartaj Singh, Thilina Rathnayake, Sean Vig, Brian E. Granger, Richard P. Muller, Francesco Bonazzi, Harsh Gupta, Shivam Vats, Fredrik Johansson, Fabian Pedregosa, Matthew J. Curry, Andy R. Terrel, Štěpán Roučka, Ashutosh Saboo, Isuru Fernando, Sumith Kulal, Robert Cimrman, Anthony Scopatz
https://doi.org/10.7717/peerj-cs.103
August 8, 2016
Clawpack: building an open source ecosystem for solving hyperbolic PDEs
Kyle T. Mandli, Aron J. Ahmadia, Marsha Berger, Donna Calhoun, David L. George, Yiannis Hadjimichael, David I. Ketcheson, Grady I. Lemoine, Randall J. LeVeque
https://doi.org/10.7717/peerj-cs.68