Nigel Goddard

5.8k citations
58 papers · 3.4k indexed · 2 hit papers · h-index 20

Nigel Goddard

55 papers receiving 3.3k citations

Hit Papers

Sequence-to-Point Learning With Neural Networks for Non-I...35720142026201820224008001.2k

Peers

Nigel Goddard
Comparison fields: 5 of 187
  • Cognitive Neuroscience 1.0k
  • Computer Vision and Pattern Recognition 586
  • Artificial Intelligence 818
  • Cellular and Molecular Neuroscience 381
  • Biophysics 92
Replace Tom Heskes with:
Tom Heskes Netherlands
Hava T. Siegelmann United States
Yuanjie Zheng China
Aamir Saeed Malik Malaysia
Shin Ishii Japan
Nathan Intrator Israel
Paul Schrater United States
Stephen Marsland New Zealand
Ning Qian United States
Alexander Kraskov United Kingdom
Nigel Goddard relative to Tom Heskes Netherlands Tom Heskes's profile →
Citations per field
00.5×1.5×2.3×
Tom Heskes · 1×
Citations per year

Countries citing papers authored by Nigel Goddard

Since Specialization
Citations

This map shows the geographic impact of Nigel Goddard's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Nigel Goddard with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nigel Goddard more than expected).

Fields of papers citing papers by Nigel Goddard

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nigel Goddard. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Nigel Goddard. The network helps show where Nigel Goddard may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Nigel Goddard, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Nigel Goddard Line = papers co-authored together Nigel Goddard links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 202140
2 20212
3 201811
4 20165
5
The 4th European Conference on Behaviour and Energy Efficiency (Behave 2016)
20166
6 201514
7
Signal Aggregate Constraints in Additive Factorial HMMs, with Application to Energy Disaggregation
201447
8 200910
9 200676
10 200636
11 2005111
12 200443
13 20042
14 20034
15 20031
16 20035
17 20024
18 1996189
19 1996168
20
The Perception of Articulated Motion: Recognizing Moving Light Displays
199237

About Nigel Goddard

Nigel Goddard is a scholar working on Cognitive Neuroscience, Information Systems and Management and Biophysics, having authored 58 papers that have together received 3.4k indexed citations. Recurring topics across this work include Functional Brain Connectivity Studies (10 papers), Energy, Environment, and Transportation Policies (5 papers), Scientific Computing and Data Management (5 papers), Neural dynamics and brain function (5 papers), Memory and Neural Mechanisms (5 papers), Neural Networks and Applications (5 papers), Building Energy and Comfort Optimization (4 papers) and Environmental Impact and Sustainability (4 papers). The work is most often cited by research in Cognitive Neuroscience (1.0k citations), Computer Vision and Pattern Recognition (586 citations) and Artificial Intelligence (818 citations). Nigel Goddard has collaborated with scholars based in United Kingdom, United States and Belgium. Frequent co-authors include Mingjun Zhong, Charles Sutton, James L. McClelland, Chaoyun Zhang, Enrico Simonotto, Ian Marshall, Joanna M. Wardlaw, Eve C. Johnstone, Ian J. Deary and Heather C. Whalley. Their work appears in journals such as Neurocomputing, Network Computation in Neural Systems, Applied Energy, Artificial Intelligence and Hippocampus.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact

Rankless by CCL
2026