Daniel Harabor

2.3k total citations
86 papers, 1.5k citations indexed

About

Daniel Harabor is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Signal Processing. According to data from OpenAlex, Daniel Harabor has authored 86 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 65 papers in Computer Vision and Pattern Recognition, 53 papers in Artificial Intelligence and 32 papers in Signal Processing. Recurrent topics in Daniel Harabor's work include Robotic Path Planning Algorithms (61 papers), Data Management and Algorithms (32 papers) and Artificial Intelligence in Games (23 papers). Daniel Harabor is often cited by papers focused on Robotic Path Planning Algorithms (61 papers), Data Management and Algorithms (32 papers) and Artificial Intelligence in Games (23 papers). Daniel Harabor collaborates with scholars based in Australia, United States and Canada. Daniel Harabor's co-authors include Alban Grastien, Peter J. Stuckey, Sven Koenig, Jiaoyang Li, Hang Ma, Adi Botea, Graeme Gange, Zhe Chen, Xiaoshan Bai and Javier Alonso–Mora and has published in prestigious journals such as Expert Systems with Applications, Artificial Intelligence and Computers & Operations Research.

In The Last Decade

Daniel Harabor

82 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel Harabor Australia 20 1.1k 439 334 334 250 86 1.5k
T. K. Satish Kumar United States 19 1.2k 1.1× 627 1.4× 301 0.9× 590 1.8× 266 1.1× 131 1.9k
Guni Sharon United States 18 1.3k 1.1× 633 1.4× 270 0.8× 504 1.5× 89 0.4× 44 1.7k
Hang Ma United States 23 1.3k 1.2× 571 1.3× 227 0.7× 534 1.6× 96 0.4× 57 1.6k
Glenn Wagner United States 11 805 0.7× 367 0.8× 179 0.5× 315 0.9× 34 0.1× 25 1.0k
Zheng Sun China 18 571 0.5× 141 0.3× 345 1.0× 117 0.4× 58 0.2× 70 1.2k
Nora Ayanian United States 18 909 0.8× 282 0.6× 443 1.3× 599 1.8× 27 0.1× 50 1.4k
Alban Grastien Australia 13 340 0.3× 193 0.4× 171 0.5× 113 0.3× 69 0.3× 49 821
Eric Schkufza United States 15 387 0.3× 274 0.6× 82 0.2× 145 0.4× 113 0.5× 24 1.3k
Hanna Kurniawati Australia 14 714 0.6× 504 1.1× 426 1.3× 192 0.6× 34 0.1× 38 1.3k
Yuan Zhou China 22 229 0.2× 316 0.7× 206 0.6× 383 1.1× 117 0.5× 137 1.5k

Countries citing papers authored by Daniel Harabor

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Harabor

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Harabor

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Harabor. A scholar is included among the top collaborators of Daniel Harabor 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 Daniel Harabor. Daniel Harabor 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.
Chen, Zhe, Daniel Harabor, Jiaoyang Li, & Peter J. Stuckey. (2024). Traffic Flow Optimisation for Lifelong Multi-Agent Path Finding. Proceedings of the AAAI Conference on Artificial Intelligence. 38(18). 20674–20682. 6 indexed citations
2.
Harabor, Daniel, et al.. (2024). Avoiding Node Re-Expansions Can Break Symmetry Breaking. Proceedings of the International Symposium on Combinatorial Search. 17. 20–27.
3.
Zhang, Yue, Zhe Chen, Daniel Harabor, Pierre Le Bodic, & Peter J. Stuckey. (2024). Planning and Execution in Multi-Agent Path Finding: Models and Algorithms. Proceedings of the International Conference on Automated Planning and Scheduling. 34. 707–715. 1 indexed citations
4.
Ebrahimi, Morteza, et al.. (2024). Guards: Benchmarks for weighted grid-based pathfinding. Expert Systems with Applications. 249. 123719–123719. 2 indexed citations
5.
Tack, Guido, et al.. (2024). Enhanced methods for the weight constrained shortest path problem. Networks. 84(1). 3–30. 1 indexed citations
6.
Harabor, Daniel, et al.. (2023). Reducing Redundant Work in Jump Point Search. Proceedings of the International Symposium on Combinatorial Search. 16(1). 128–136. 1 indexed citations
7.
Harabor, Daniel, et al.. (2023). Voxel Benchmarks for 3D Pathfinding: Sandstone, Descent, and Industrial Plants. Proceedings of the International Symposium on Combinatorial Search. 16(1). 56–64. 1 indexed citations
8.
Chen, Zhe, et al.. (2023). Beyond Pairwise Reasoning in Multi-Agent Path Finding. Proceedings of the International Conference on Automated Planning and Scheduling. 33(1). 384–392. 1 indexed citations
9.
Harabor, Daniel, et al.. (2023). Exact Anytime Multi-Agent Path Finding Using Branch-and-Cut-and-Price and Large Neighborhood Search. Proceedings of the International Conference on Automated Planning and Scheduling. 33(1). 254–258. 1 indexed citations
10.
Chen, Zhe, Javier Alonso–Mora, Xiaoshan Bai, Daniel Harabor, & Peter J. Stuckey. (2021). Integrated Task Assignment and Path Planning for Capacitated Multi-Agent Pickup and Delivery. IEEE Robotics and Automation Letters. 6(3). 5816–5823. 124 indexed citations
11.
Li, Jiaoyang, Daniel Harabor, Peter J. Stuckey, et al.. (2021). Pairwise symmetry reasoning for multi-agent path finding search. Artificial Intelligence. 301. 103574–103574. 62 indexed citations
12.
Boyarski, Eli, Ariel Felner, Pierre Le Bodic, et al.. (2021). f-Aware Conflict Prioritization & Improved Heuristics For Conflict-Based Search. National Conference on Artificial Intelligence. 35(14). 12241–12248. 4 indexed citations
13.
Harabor, Daniel & Alban Grastien. (2021). The JPS Pathfinding System. Proceedings of the International Symposium on Combinatorial Search. 3(1). 207–208. 7 indexed citations
14.
Boyarski, Eli, Ariel Felner, Daniel Harabor, et al.. (2020). Iterative-Deepening Conflict-Based Search. Monash University Research Portal (Monash University). 4084–4090. 15 indexed citations
15.
Ma, Hang, Daniel Harabor, Peter J. Stuckey, Jiaoyang Li, & Sven Koenig. (2019). Searching with consistent prioritization for multi-agent path finding. Monash University Research Portal (Monash University). 188–189. 4 indexed citations
16.
Li, Jiaoyang, Daniel Harabor, Peter J. Stuckey, et al.. (2019). Disjoint splitting for conflict-based search for Multi-Agent Path Finding. International Conference on Automated Planning and Scheduling. 279–283. 5 indexed citations
17.
Hu, Yue, et al.. (2019). Improving the Combination of JPS and Geometric Containers. Proceedings of the International Conference on Automated Planning and Scheduling. 29. 209–213. 1 indexed citations
18.
Harabor, Daniel, et al.. (2012). TRANSIT Routing on Video Game Maps. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment. 8(1). 2–7. 15 indexed citations
19.
Harabor, Daniel. (2011). Graph pruning and symmetry breaking on grid maps. International Joint Conference on Artificial Intelligence. 2816–2817. 1 indexed citations
20.
Harabor, Daniel, Adi Botea, & Philip Kilby. (2011). Path Symmetries in Undirected Uniform-Cost Grids. ANU Open Research (Australian National University). 58–61. 3 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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