Nick Hawes

2.5k total citations
103 papers, 1.2k citations indexed

About

Nick Hawes is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Networks and Communications. According to data from OpenAlex, Nick Hawes has authored 103 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 60 papers in Artificial Intelligence, 31 papers in Computer Vision and Pattern Recognition and 18 papers in Computer Networks and Communications. Recurrent topics in Nick Hawes's work include AI-based Problem Solving and Planning (31 papers), Reinforcement Learning in Robotics (20 papers) and Robotic Path Planning Algorithms (19 papers). Nick Hawes is often cited by papers focused on AI-based Problem Solving and Planning (31 papers), Reinforcement Learning in Robotics (20 papers) and Robotic Path Planning Algorithms (19 papers). Nick Hawes collaborates with scholars based in United Kingdom, Germany and Sweden. Nick Hawes's co-authors include Bruno Lacerda, Jeremy Wyatt, David Parker, Marc Hanheide, Lars Kunze, Patric Jensfelt, Geert-Jan M. Kruijff, Hendrik Zender, Jay Young and Rustam Stolkin and has published in prestigious journals such as Philosophical Transactions of the Royal Society B Biological Sciences, Journal of Ecology and Artificial Intelligence.

In The Last Decade

Nick Hawes

93 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nick Hawes United Kingdom 21 610 419 234 168 136 103 1.2k
R. Peter Bonasso United States 13 466 0.8× 386 0.9× 247 1.1× 202 1.2× 155 1.1× 49 987
R. James Firby United States 13 925 1.5× 512 1.2× 291 1.2× 167 1.0× 268 2.0× 35 1.4k
Damian M. Lyons United States 14 373 0.6× 416 1.0× 195 0.8× 144 0.9× 145 1.1× 111 964
David Kortenkamp United States 20 624 1.0× 665 1.6× 376 1.6× 549 3.3× 240 1.8× 82 1.7k
Stanislao Lauria United Kingdom 21 485 0.8× 213 0.5× 279 1.2× 53 0.3× 219 1.6× 37 1.2k
Subramanian Ramamoorthy United Kingdom 17 359 0.6× 254 0.6× 233 1.0× 70 0.4× 66 0.5× 104 906
Erann Gat United States 19 984 1.6× 753 1.8× 368 1.6× 327 1.9× 415 3.1× 41 1.8k
Richard Dearden United Kingdom 22 1.2k 2.0× 186 0.4× 369 1.6× 79 0.5× 202 1.5× 53 1.8k
A. Meystel United States 14 432 0.7× 289 0.7× 293 1.3× 139 0.8× 93 0.7× 99 913
Hanna Kurniawati Australia 14 504 0.8× 714 1.7× 315 1.3× 426 2.5× 192 1.4× 38 1.3k

Countries citing papers authored by Nick Hawes

Since Specialization
Citations

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

Fields of papers citing papers by Nick Hawes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Nick Hawes. 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 Nick Hawes. The network helps show where Nick Hawes may publish in the future.

Co-authorship network of co-authors of Nick Hawes

This figure shows the co-authorship network connecting the top 25 collaborators of Nick Hawes. A scholar is included among the top collaborators of Nick Hawes 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 Nick Hawes. Nick Hawes is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Omeiza, Daniel, et al.. (2025). A transparency paradox? Investigating the impact of explanation specificity and autonomous vehicle imperfect detection capabilities on passengers. Transportation Research Part F Traffic Psychology and Behaviour. 109. 1275–1292. 2 indexed citations
2.
Qi, Man, Matthew Gadd, Daniele De Martini, et al.. (2025). Biodiversity research requires more motors in air, water and on land. Methods in Ecology and Evolution. 17(3). 668–682.
3.
Niu, Hanlin, Matthew Gadd, Andrejs Schütz, et al.. (2025). AutoInspect: Toward Long-Term Autonomous Inspection and Monitoring. 2. 529–548.
4.
Xu, Tong, et al.. (2025). Decremental Dynamics Planning for Robot Navigation. 4559–4565.
5.
Lacerda, Bruno, et al.. (2024). A Framework for Simultaneous Task Allocation and Planning under Uncertainty. ACM Transactions on Autonomous and Adaptive Systems. 19(4). 1–30. 1 indexed citations
6.
Lacerda, Bruno, et al.. (2024). Right Place, Right Time: Proactive Multi-Robot Task Allocation Under Spatiotemporal Uncertainty. Journal of Artificial Intelligence Research. 79. 137–171. 2 indexed citations
7.
Duckworth, Paul, et al.. (2024). Planning under uncertainty for safe robot exploration using Gaussian process prediction. Autonomous Robots. 48(7). 18–18. 1 indexed citations
8.
Duckworth, Paul, et al.. (2024). Correction: Planning under uncertainty for safe robot exploration using gaussian process prediction. Autonomous Robots. 48(8). 1 indexed citations
9.
Jovan, Ferdian, et al.. (2023). Correction: Efficiently exploring for human robot interaction: partially observable Poisson processes. Autonomous Robots. 47(8). 1593–1593.
10.
Hawes, Nick, et al.. (2021). Mixed-initiative variable autonomy for remotely operated mobile robots. University of Birmingham Research Portal (University of Birmingham). 29 indexed citations
11.
Mühlig, Manuel, et al.. (2021). Congestion-Aware Policy Synthesis for Multirobot Systems. IEEE Transactions on Robotics. 38(1). 262–280. 14 indexed citations
12.
Azevedo, Carlos Lima, Bruno Lacerda, Nick Hawes, & Pedro U. Lima. (2020). Long-Run Multi-Robot Planning Under Uncertain Task Durations. Adaptive Agents and Multi-Agents Systems. 2168–2170. 1 indexed citations
13.
Lacerda, Bruno, et al.. (2020). Battery charge scheduling in long-life autonomous mobile robots via multi-objective decision making under uncertainty. Robotics and Autonomous Systems. 133. 103629–103629. 18 indexed citations
14.
Lacerda, Bruno, et al.. (2019). Probabilistic planning with formal performance guarantees for mobile service robots. The International Journal of Robotics Research. 38(9). 1098–1123. 42 indexed citations
15.
Hawes, Nick, et al.. (2016). Human-Initiative Variable Autonomy: An Experimental Analysis of the Interactions Between a Human Operator and a Remotely Operated Mobile Robot which also Possesses Autonomous Capabilities.. University of Birmingham Research Portal (University of Birmingham). 5 indexed citations
16.
Lacerda, Bruno, David Parker, & Nick Hawes. (2015). Optimal policy generation for partially satisfiable co-safe LTL specifications. University of Birmingham Research Portal (University of Birmingham). 1587–1593. 24 indexed citations
17.
Kunze, Lars, et al.. (2014). Bootstrapping Probabilistic Models of Qualitative Spatial Relations for Active Visual Object Search.. University of Birmingham Research Portal (University of Birmingham). 10 indexed citations
18.
Young, Jay & Nick Hawes. (2013). Predicting Situated Behaviour Using Sequences of Abstract Spatial Relations.. National Conference on Artificial Intelligence. 6 indexed citations
19.
Young, Jay & Nick Hawes. (2012). Evolutionary Learning of Goal Priorities in a Real-Time Strategy Game. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment. 8(1). 87–92. 14 indexed citations
20.
Hanheide, Marc, Charles Gretton, Richard Dearden, et al.. (2011). Exploiting Probabilistic Knowledge under Uncertain Sensing for Efficient Robot Behaviour. Lincoln Repository (University of Lincoln). 30 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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2026