The chart shows the distribution of publications by all Research.com ranked scientists in the field of Mathematics in 2026. The highlighted bar marks where Nicholas I. M. Gould sits on this spectrum.
This scientist: 176 publications — 52nd percentile
52% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 537 publications or more.
The chart shows the D-index (discipline H-index) distribution of Mathematics scientists ranked by Research.com in 2026. The highlighted bar marks where Nicholas I. M. Gould sits on this spectrum.
This scientist: 58 D-Index — 83rd percentile
83% of scientists in this discipline score the same or lower.
The last bar groups every scientist with 86 D-Index or more.
Nicholas I. M. Gould is affiliated with the Rutherford Appleton Laboratory in the United Kingdom. Their research spans multiple fields, primarily focusing on Computer Science, Engineering, and Mathematics. Within these areas, Gould's work covers several subfields, including Numerical Analysis, Computational Mechanics, Computational Theory and Mathematics, Artificial Intelligence, and Control and Systems Engineering.
Their main topics of research include Advanced Optimization Algorithms Research, Sparse and Compressive Sensing Techniques, Stochastic Gradient Optimization Techniques, Optimization and Variational Analysis, Matrix Theory and Algorithms, Polynomial and Algebraic Computation, and Machine Learning and Algorithms.
Among Gould's selected recent publications are:
Frequent publication venues where Gould's work appears include:
Gould has collaborated frequently with several co-authors. The most frequent collaborators are Philippe L. Toint, Coralia Cartis, Jaroslav Fowkes, J. A. Scott, and Olivia Liang.
Gould has authored a book published by the Society for Industrial and Applied Mathematics titled Evaluation Complexity of Algorithms for Nonconvex Optimization: Theory, Computation and Perspectives (2022).
Gould received recognition as a SIAM Fellow in 2009 for contributions to numerical continuous optimization.
Andrew R. Conn;Nicholas I. M. Gould;Philippe L. Toint
I. Bongartz;A. R. Conn;Nick Gould;Ph. L. Toint
Andrew R. Conn;Nicholas I. M. Gould;Philippe L. Toint
A. R. Conn;N. I. M. Gould;Ph L. Toint
Nicholas I. M. Gould;Dominique Orban;Philippe L. Toint
Roger Fletcher;Nicholas I. M. Gould;Sven Leyffer;Philippe L. Toint
A. R. Conn;Nick Gould;Ph. L. Toint
Carsten Keller;Nicholas I. M. Gould;Andrew J. Wathen
Coralia Cartis;Nicholas I. Gould;Philippe L. Toint
Nicholas I. Gould;Dominique Orban;Philippe L. Toint
Nicholas I. M. Gould;Stefano Lucidi;Massimo Roma;Philippe L. Toint
Nicholas I. M. Gould;Mary E. Hribar;Jorge Nocedal
Andrew R. Conn;Nicholas I. M. Gould;Philippe L. Toint
Nicholas I. M. Gould;Jennifer A. Scott;Yifan Hu
Coralia Cartis;Nicholas I. M. Gould;Philippe L. Toint
A. R. Conn;N. I. M. Gould;Ph. L. Toint
Nicholas I. M. Gould;Dominique Orban;Philippe L. Toint
C. Cartis;N. I. M. Gould;Ph. L. Toint
Nick Gould;Dominique Orban;Philippe Toint
C Audet;H H Bauschke;L T Biegler;P L Combettes
Nicholas I. M. Gould;Stefano Lucidi;Massimo Roma;Philippe L. Toint
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