Hang Ma

3.2k citations
58 papers · 1.7k · h-index 24

Impact in

Papers in

Hang Ma

56 papers receiving 1.6k citations

Peers

Hang Ma
Comparison fields: 5 of 59
  • Computer Vision and Pattern Recognition 1.3k
  • Industrial and Manufacturing Engineering 373
  • Computer Networks and Communications 550
  • Software 89
  • Artificial Intelligence 590
Replace Guni Sharon with:
Guni Sharon United States
Jiaoyang Li United States
Daniel Harabor Australia
Glenn Wagner United States
Roman Barták Czechia
Alban Grastien Australia
William Yeoh United States
Takuya Azumi Japan
Dmitri Dolgov United States
Haluk Rahmi Topcuoglu Türkiye
Hang Ma relative to Guni Sharon United States Guni Sharon's profile →
Citations per field
00.5×1.5×
Guni Sharon · 1×
Citations per year

Countries citing papers authored by Hang Ma

Since Specialization
Citations

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

Fields of papers citing papers by Hang Ma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Hang Ma, 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 Hang Ma Line = papers co-authored together Hang Ma links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 58 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019147
2 2017113
3 2016101
4 201699
5 201895
6 201776
7 201976
8
Planning, Scheduling and Monitoring for Airport Surface Operations.
201672
9 202165
10 201963
11 202163
12 201662
13 201959
14 201949
15 201949
16 201937
17 202036
18 201833
19 202126
20 201826

About Hang Ma

Hang Ma is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Computer Networks and Communications, Industrial and Manufacturing Engineering and Aerospace Engineering, having authored 58 papers that have together received 1.7k indexed citations. Recurring topics across this work include Robotic Path Planning Algorithms (45 papers), Multi-Agent Systems and Negotiation (12 papers), Optimization and Search Problems (11 papers), AI-based Problem Solving and Planning (11 papers), Logic, Reasoning, and Knowledge (8 papers), Constraint Satisfaction and Optimization (8 papers), Robotics and Sensor-Based Localization (7 papers) and Advanced Manufacturing and Logistics Optimization (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.3k citations), Industrial and Manufacturing Engineering (373 citations), Computer Networks and Communications (550 citations), Software (89 citations) and Artificial Intelligence (590 citations). Hang Ma has collaborated with scholars based in United States, Canada and Australia. Frequent co-authors include Sven Koenig, T. K. Satish Kumar, Jiaoyang Li, Daniel Harabor, Peter J. Stuckey, Ariel Felner, Liron Cohen, Nora Ayanian, Eli Boyarski and Jiaoyang Li. Their work appears in journals such as IEEE Robotics and Automation Letters, Reliability Engineering & System Safety, Frontiers in Public Health, IEEE Transactions on Robotics and AI Magazine.

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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