Alan G. Millard

441 total citations
18 papers, 211 citations indexed

About

Alan G. Millard is a scholar working on Electrical and Electronic Engineering, Cellular and Molecular Neuroscience and Cognitive Neuroscience. According to data from OpenAlex, Alan G. Millard has authored 18 papers receiving a total of 211 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Electrical and Electronic Engineering, 9 papers in Cellular and Molecular Neuroscience and 9 papers in Cognitive Neuroscience. Recurrent topics in Alan G. Millard's work include Neural dynamics and brain function (9 papers), Advanced Memory and Neural Computing (9 papers) and Neuroscience and Neural Engineering (8 papers). Alan G. Millard is often cited by papers focused on Neural dynamics and brain function (9 papers), Advanced Memory and Neural Computing (9 papers) and Neuroscience and Neural Engineering (8 papers). Alan G. Millard collaborates with scholars based in United Kingdom, United States and Ireland. Alan G. Millard's co-authors include Jon Timmis, David M. Halliday, Liam McDaid, Jim Harkin, Andy M. Tyrrell, Junxiu Liu, Anju P. Johnson, James A. Hilder, Alan Winfield and James O’Keeffe and has published in prestigious journals such as IEEE Transactions on Neural Networks and Learning Systems, Frontiers in Cellular Neuroscience and IEEE Transactions on Circuits and Systems I Regular Papers.

In The Last Decade

Alan G. Millard

18 papers receiving 207 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Alan G. Millard United Kingdom	9	110	84	71	36	36	18	211
Arturo Morgado‐Estévez Spain	8	75 0.7×	41 0.5×	37 0.5×	19 0.5×	35 1.0×	27	243
Chang-Woo Shin South Korea	9	243 2.2×	68 0.8×	124 1.7×	10 0.3×	44 1.2×	20	373
Yaoyuan Wang China	11	261 2.4×	118 1.4×	62 0.9×	16 0.4×	62 1.7×	24	378
Lavi Shpigelman Israel	7	51 0.5×	110 1.3×	138 1.9×	15 0.4×	36 1.0×	12	297
Giovanny Sánchez Mexico	10	152 1.4×	32 0.4×	58 0.8×	12 0.3×	60 1.7×	42	285
Manfred Hild Germany	6	39 0.4×	30 0.4×	39 0.5×	27 0.8×	45 1.3×	19	148
Arfan Ghani United Kingdom	8	226 2.1×	82 1.0×	117 1.6×	18 0.5×	82 2.3×	34	312
Mohsen Rakhshan United States	9	77 0.7×	19 0.2×	66 0.9×	127 3.5×	50 1.4×	18	288
Zunchao Li China	11	284 2.6×	42 0.5×	141 2.0×	30 0.8×	46 1.3×	44	461
Nat Dilokthanakul Thailand	4	54 0.5×	37 0.4×	96 1.4×	29 0.8×	71 2.0×	10	216

Countries citing papers authored by Alan G. Millard

Since Specialization

Citations

This map shows the geographic impact of Alan G. Millard'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 Alan G. Millard with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alan G. Millard more than expected).

Fields of papers citing papers by Alan G. Millard

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Alan G. Millard. 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 Alan G. Millard. The network helps show where Alan G. Millard may publish in the future.

Co-authorship network of co-authors of Alan G. Millard

This figure shows the co-authorship network connecting the top 25 collaborators of Alan G. Millard. A scholar is included among the top collaborators of Alan G. Millard based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Alan G. Millard. Alan G. Millard is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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18 of 18 papers shown

Millard, Alan G., et al.. (2021). Case Studies Key-Findings of a Strategic Complexity Management Framework for Industrial Manufacturing Systems. 55–60. 2 indexed citations

Millard, Alan G., et al.. (2021). Towards the Definition of a Strategic Complexity Management Framework for Complex Industrial Systems. 16. 210–215. 1 indexed citations

Liu, Junxiu, Liam McDaid, Alfonso Araque, et al.. (2019). GABA Regulation of Burst Firing in Hippocampal Astrocyte Neural Circuit: A Biophysical Model. Frontiers in Cellular Neuroscience. 13. 335–335. 7 indexed citations

Millard, Alan G., et al.. (2018). ARDebug: An Augmented Reality Tool for Analysing and Debugging Swarm Robotic Systems. Frontiers in Robotics and AI. 5. 87–87. 14 indexed citations

Millard, Alan G., et al.. (2018). The Need for Combining Implicit and Explicit Communication in Cooperative Robotic Systems. Frontiers in Robotics and AI. 5. 65–65. 21 indexed citations

O’Keeffe, James, Danesh Tarapore, Alan G. Millard, & Jon Timmis. (2018). Adaptive Online Fault Diagnosis in Autonomous Robot Swarms. Frontiers in Robotics and AI. 5. 131–131. 11 indexed citations

Johnson, Anju P., Junxiu Liu, Alan G. Millard, et al.. (2018). Time-multiplexed System-on-Chip using Fault-tolerant Astrocyte-Neuron Networks. 1076–1083. 5 indexed citations

Johnson, Anju P., Junxiu Liu, Alan G. Millard, et al.. (2018). Fault-Tolerant Learning in Spiking Astrocyte-Neural Networks on FPGAs. Ulster University Research Portal (Ulster University). 5 indexed citations

Harkin, Jim, Liam McDaid, Bryan Gardiner, et al.. (2018). FPGA-based Fault-injection and Data Acquisition of Self-repairing Spiking Neural Network Hardware. White Rose Research Online (University of Leeds, The University of Sheffield, University of York). 1–5. 4 indexed citations

10.

Liu, Junxiu, Jim Harkin, Liam McDaid, et al.. (2018). Bio-inspired Anomaly Detection for Low-cost Gas Sensors. 65. 1–4. 1 indexed citations

11.

Liu, Junxiu, Liam McDaid, Jim Harkin, et al.. (2018). Exploring Self-Repair in a Coupled Spiking Astrocyte Neural Network. IEEE Transactions on Neural Networks and Learning Systems. 30(3). 865–875. 36 indexed citations

12.

Millard, Alan G., et al.. (2017). The Pi-puck extension board: A raspberry Pi interface for the e-puck robot platform. Lincoln Repository (University of Lincoln). 741–748. 13 indexed citations

13.

Johnson, Anju P., Junxiu Liu, Alan G. Millard, et al.. (2017). Homeostatic Fault Tolerance in Spiking Neural Networks: A Dynamic Hardware Perspective. IEEE Transactions on Circuits and Systems I Regular Papers. 65(2). 687–699. 37 indexed citations

14.

Harkin, Jim, Liam McDaid, Bryan Gardiner, et al.. (2017). Assessing Self-Repair on FPGAs with Biologically Realistic Astrocyte-Neuron Networks. Ulster University Research Portal (Ulster University). 421–426. 10 indexed citations

15.

O’Keeffe, James, Danesh Tarapore, Alan G. Millard, & Jon Timmis. (2017). Fault diagnosis in robot swarms: An adaptive online behaviour characterisation approach. ePrints Soton (University of Southampton). 1–8. 4 indexed citations

16.

Johnson, Anju P., Junxiu Liu, Alan G. Millard, et al.. (2017). Homeostatic fault tolerance in spiking neural networks utilizing dynamic partial reconfiguration of FPGAs. Ulster University Research Portal (Ulster University). 195–198. 4 indexed citations

17.

Johnson, Anju P., David M. Halliday, Alan G. Millard, et al.. (2016). An FPGA-based hardware-efficient fault-tolerant astrocyte-neuron network. Ulster University Research Portal (Ulster University). 1–8. 17 indexed citations

18.

Millard, Alan G., Jon Timmis, & Alan Winfield. (2014). Run-time detection of faults in autonomous mobile robots based on the comparison of simulated and real robot behaviour. Lincoln Repository (University of Lincoln). 3720–3725. 19 indexed citations

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.

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