Daniel Harabor
Impact in
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- Robotic Path Planning Algorithms
- Graph Theory and Algorithms
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- Advanced Manufacturing and Logistics Optimization
Papers in
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- Robotic Path Planning Algorithms 83
- Graph Theory and Algorithms 4
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- Complexity and Algorithms in Graphs 12
- Advanced Multi-Objective Optimization Algorithms 3
- Co-authors
- Alban Grastien (6 shared papers)Peter J. Stuckey (52 shared papers)Jiaoyang Li (23 shared papers)Sven Koenig (22 shared papers)Hang Ma (11 shared papers)Adi Botea (13 shared papers)Graeme Gange (8 shared papers)Zhe Chen (3 shared papers)
- Journals
- Journal of Artificial Intelligence Research (4 papers)Artificial Intelligence (2 papers)IEEE Robotics and Automation Letters (2 papers)Expert Systems with Applications (1 paper)Transportation Science (1 paper)
- Partner nations
- AustraliaUnited StatesCanada
In The Last Decade
Daniel Harabor
87 papers receiving 1.7k citations
Peers
Comparison fields: 5 of 44
- Computer Vision and Pattern Recognition 1.5k
- Industrial and Manufacturing Engineering 99
- Computer Graphics and Computer-Aided Design 35
- Artificial Intelligence 235
- Computational Theory and Mathematics 80
Countries citing papers authored by Daniel Harabor
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
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-authors
The 25 scholars most cited alongside Daniel Harabor, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 97 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 299 | |
| 2 | 2019 | 173 | |
| 3 | 2021 | 153 | |
| 4 | 2014 | 84 | |
| 5 | 2021 | 75 | |
| 6 | 2022 | 60 | |
| 7 | 2019 | 56 | |
| 8 | 2019 | 54 | |
| 9 | 2021 | 49 | |
| 10 | 2019 | 48 | |
| 11 | 2019 | 45 | |
| 12 | 2016 | 39 | |
| 13 | 2020 | 39 | |
| 14 | 2008 | 37 | |
| 15 | 2022 | 35 | |
| 16 | 2013 | 34 | |
| 17 | 2021 | 31 | |
| 18 | 2017 | 23 | |
| 19 | 2021 | 23 | |
| 20 | 2021 | 23 |
About Daniel Harabor
Daniel Harabor is a scholar working on Computer Vision and Pattern Recognition, Computational Theory and Mathematics, Artificial Intelligence, Transportation and Industrial and Manufacturing Engineering, having authored 97 papers that have together received 1.8k indexed citations. Recurring topics across this work include Robotic Path Planning Algorithms (83 papers), Complexity and Algorithms in Graphs (12 papers), Artificial Intelligence in Games (11 papers), Transportation Planning and Optimization (5 papers), Graph Theory and Algorithms (4 papers), Advanced Multi-Objective Optimization Algorithms (3 papers), Constraint Satisfaction and Optimization (3 papers) and Vehicle Routing Optimization Methods (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.5k citations), Industrial and Manufacturing Engineering (99 citations), Computer Graphics and Computer-Aided Design (35 citations), Artificial Intelligence (235 citations) and Computational Theory and Mathematics (80 citations). Daniel Harabor has collaborated with scholars based in Australia, United States and Canada. Frequent co-authors include Alban Grastien, Peter J. Stuckey, Jiaoyang Li, Sven Koenig, Hang Ma, Adi Botea, Graeme Gange, Zhe Chen, Javier Alonso–Mora and Xiaoshan Bai. Their work appears in journals such as Journal of Artificial Intelligence Research, Artificial Intelligence, IEEE Robotics and Automation Letters, Expert Systems with Applications and Transportation Science.
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.