Daniel Harabor
Impact in
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- Robotic Path Planning Algorithms
Papers in
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- Robotic Path Planning Algorithms 62
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- Artificial Intelligence in Games 23
- Algorithms and Data Compression 11
- AI-based Problem Solving and Planning 9
- Co-authors
- Alban Grastien (6 shared papers)Peter J. Stuckey (51 shared papers)Sven Koenig (22 shared papers)Jiaoyang Li (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 (3 papers)Artificial Intelligence (2 papers)IEEE Robotics and Automation Letters (1 paper)Autonomous Agents and Multi-Agent Systems (1 paper)Expert Systems with Applications (1 paper)
- Partner nations
- AustraliaUnited StatesCanada
In The Last Decade
Daniel Harabor
85 papers receiving 1.5k citations
Peers
Comparison fields: 5 of 56
- Computer Vision and Pattern Recognition 1.2k
- Computer Graphics and Computer-Aided Design 103
- Signal Processing 280
- Industrial and Manufacturing Engineering 256
- Software 76
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 90 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 278 | |
| 2 | 2019 | 157 | |
| 3 | 2021 | 136 | |
| 4 | 2014 | 81 | |
| 5 | 2021 | 65 | |
| 6 | 2019 | 52 | |
| 7 | 2019 | 50 | |
| 8 | 2022 | 48 | |
| 9 | 2019 | 44 | |
| 10 | 2019 | 41 | |
| 11 | 2020 | 38 | |
| 12 | 2008 | 38 | |
| 13 | 2022 | 34 | |
| 14 | 2013 | 32 | |
| 15 | 2016 | 30 | |
| 16 | 2021 | 27 | |
| 17 | 2021 | 23 | |
| 18 | 2010 | 21 | |
| 19 | 2017 | 21 | |
| 20 | 2015 | 20 |
About Daniel Harabor
Daniel Harabor is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Signal Processing, Computer Networks and Communications and Industrial and Manufacturing Engineering, having authored 90 papers that have together received 1.6k indexed citations. Recurring topics across this work include Robotic Path Planning Algorithms (62 papers), Data Management and Algorithms (33 papers), Artificial Intelligence in Games (23 papers), Algorithms and Data Compression (11 papers), Computational Geometry and Mesh Generation (10 papers), Vehicle Routing Optimization Methods (10 papers), AI-based Problem Solving and Planning (9 papers) and Optimization and Search Problems (7 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.2k citations), Computer Graphics and Computer-Aided Design (103 citations), Signal Processing (280 citations), Industrial and Manufacturing Engineering (256 citations) and Software (76 citations). Daniel Harabor has collaborated with scholars based in Australia, United States and Canada. Frequent 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. Their work appears in journals such as Journal of Artificial Intelligence Research, Artificial Intelligence, IEEE Robotics and Automation Letters, Autonomous Agents and Multi-Agent Systems and Expert Systems with Applications.
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.