M. Judd

542 citations
24 papers · 399 · h-index 13

Impact in

Papers in

M. Judd

23 papers receiving 359 citations

Peers

M. Judd
Comparison fields: 5 of 61
  • Astronomy and Astrophysics 134
  • Computer Vision and Pattern Recognition 152
  • Aerospace Engineering 131
  • Artificial Intelligence 137
  • Computer Networks and Communications 57
Replace Gregg Rabideau with:
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Benjamin Cichy United States
M. L. Rilee United States
Dave Barnes United Kingdom
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Fang‐Cheng Chan United States
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Citations per field
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Citations per year

Countries citing papers authored by M. Judd

Since Specialization
Citations

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

Fields of papers citing papers by M. Judd

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 24 scholars most cited alongside M. Judd, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with M. Judd Line = papers co-authored together M. Judd links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201275
2 200760
3 200537
4 200435
5 200733
6 200722
7 200621
8
Learning and planning for Mars Rover science
200317
9 200516
10
Intensity-based Rock Detection for Acquiring Onboard Rover Science
200413
11
Machine learning challenges in Mars rover traverse science
200313
12
AEGIS automated targeting for MER opportunity rover
201213
13 200912
14 200511
15
Supporting Increased Autonomy for a Mars Rover
20086
16
Techniques for Onboard Prioritization of Science Data for Transmission
20033
17 20093
18
Maximizing Rover Science Return Through Autonomous Onboard Data Analysis
20032
19
Opportunistic Planning and Execution for Planetary Exploration
20062
20 20082

About M. Judd

M. Judd is a scholar working on Astronomy and Astrophysics, Mechanical Engineering, Computer Vision and Pattern Recognition, Artificial Intelligence and Aerospace Engineering, having authored 24 papers that have together received 399 indexed citations. Recurring topics across this work include Planetary Science and Exploration (8 papers), Modular Robots and Swarm Intelligence (7 papers), Robotics and Sensor-Based Localization (6 papers), Astro and Planetary Science (6 papers), Distributed systems and fault tolerance (5 papers), AI-based Problem Solving and Planning (4 papers), Robotic Path Planning Algorithms (4 papers) and Scientific Computing and Data Management (2 papers). The work is most often cited by research in Astronomy and Astrophysics (134 citations), Computer Vision and Pattern Recognition (152 citations), Aerospace Engineering (131 citations), Artificial Intelligence (137 citations) and Computer Networks and Communications (57 citations). M. Judd has collaborated with scholars based in United States. Frequent co-authors include Tara Estlin, Robert C. Anderson, Daniel Gaines, Rebecca Castaño, Benjamin Bornstein, David R. Thompson, Michael C. Burl, Andrés Castaño, Forest Fisher and B. Bornstein. Their work appears in journals such as Journal of Field Robotics, ACM Transactions on Intelligent Systems and Technology, International Conference on Automated Planning and Scheduling, Lunar and Planetary Science Conference and 37th Annual Lunar and Planetary Science Conference.

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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