Micah Corah

476 total citations
12 papers, 302 citations indexed

About

Micah Corah is a scholar working on Computer Vision and Pattern Recognition, Computer Networks and Communications and Artificial Intelligence. According to data from OpenAlex, Micah Corah has authored 12 papers receiving a total of 302 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Computer Vision and Pattern Recognition, 5 papers in Computer Networks and Communications and 4 papers in Artificial Intelligence. Recurrent topics in Micah Corah's work include Robotic Path Planning Algorithms (5 papers), Optimization and Search Problems (4 papers) and Robotics and Sensor-Based Localization (4 papers). Micah Corah is often cited by papers focused on Robotic Path Planning Algorithms (5 papers), Optimization and Search Problems (4 papers) and Robotics and Sensor-Based Localization (4 papers). Micah Corah collaborates with scholars based in United States and Australia. Micah Corah's co-authors include Nathan Michael, Nilanjan Chakraborty, Katia Sycara, Derek Mitchell, Erik Nelson, Sebastian Scherer, John G. Keller, Graeme Best and Roland Martinꝉ and has published in prestigious journals such as Autonomous Robots, IEEE Robotics and Automation Letters and 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

In The Last Decade

Micah Corah

12 papers receiving 297 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Micah Corah United States 9 164 151 136 75 47 12 302
Jacopo Banfi Italy 12 184 1.1× 227 1.5× 119 0.9× 83 1.1× 101 2.1× 32 384
Yehuda Elmaliach Israel 6 131 0.8× 208 1.4× 68 0.5× 58 0.8× 51 1.1× 8 286
Luigi Nardi United States 11 136 0.8× 102 0.7× 136 1.0× 60 0.8× 35 0.7× 20 372
Suleman Mir Pakistan 10 127 0.8× 60 0.4× 114 0.8× 113 1.5× 29 0.6× 24 302
Guanglei Meng China 11 137 0.8× 51 0.3× 219 1.6× 98 1.3× 23 0.5× 37 364
Yunfei Shi United States 3 171 1.0× 61 0.4× 51 0.4× 120 1.6× 29 0.6× 5 271
Yulong Ding China 10 163 1.0× 113 0.7× 150 1.1× 45 0.6× 14 0.3× 28 300
Jianqiao Yu China 9 226 1.4× 179 1.2× 291 2.1× 59 0.8× 18 0.4× 22 458
Bodi Ma China 6 119 0.7× 76 0.5× 116 0.9× 46 0.6× 10 0.2× 9 282
Mark Mote United States 10 98 0.6× 94 0.6× 105 0.8× 83 1.1× 47 1.0× 16 382

Countries citing papers authored by Micah Corah

Since Specialization
Citations

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

Fields of papers citing papers by Micah Corah

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Micah Corah

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

All Works

12 of 12 papers shown
1.
Martinꝉ, Roland, et al.. (2024). Multi-Robot Planning for Filming Groups of Moving Actors Leveraging Submodularity and Pixel Density. 5401–5408. 1 indexed citations
2.
3.
Corah, Micah, et al.. (2023). Multi-Robot Multi-Room Exploration With Geometric Cue Extraction and Circular Decomposition. IEEE Robotics and Automation Letters. 9(2). 1190–1197. 7 indexed citations
4.
Corah, Micah & Nathan Michael. (2021). Scalable Distributed Planning for Multi-Robot, Multi-Target Tracking. 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 437–444. 10 indexed citations
5.
Corah, Micah, et al.. (2019). Communication-Efficient Planning and Mapping for Multi-Robot Exploration in Large Environments. IEEE Robotics and Automation Letters. 4(2). 1715–1721. 66 indexed citations
6.
Corah, Micah & Nathan Michael. (2018). Distributed matroid-constrained submodular maximization for multi-robot exploration: theory and practice. Autonomous Robots. 43(2). 485–501. 70 indexed citations
7.
Corah, Micah & Nathan Michael. (2018). Distributed Submodular Maximization on Partition Matroids for Planning on Large Sensor Networks. 6792–6799. 25 indexed citations
8.
Corah, Micah & Nathan Michael. (2017). Efficient Online Multi-robot Exploration via Distributed Sequential Greedy Assignment. 36 indexed citations
9.
Corah, Micah & Nathan Michael. (2017). Active estimation of mass properties for safe cooperative lifting. 4582–4587. 8 indexed citations
10.
Nelson, Erik, Micah Corah, & Nathan Michael. (2017). Environment model adaptation for mobile robot exploration. Autonomous Robots. 42(2). 257–272. 14 indexed citations
11.
Corah, Micah, et al.. (2016). Computationally efficient information-theoretic exploration of pits and caves. 3722–3727. 26 indexed citations
12.
Mitchell, Derek, Micah Corah, Nilanjan Chakraborty, Katia Sycara, & Nathan Michael. (2015). Multi-robot long-term persistent coverage with fuel constrained robots. 1093–1099. 37 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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