Matthew Matl

1.6k citations
11 papers · 918 indexed · 1 hit paper · h-index 8
Topics
Interconnection Networks and Systems (5 papers)Parallel Computing and Optimization Techniques (5 papers)Embedded Systems Design Techniques (5 papers)
Partner nations
United StatesChina

In The Last Decade

Matthew Matl

11 papers receiving 882 citations

Hit Papers

Learning ambidextrous robot grasping policies20192026202120232019100200300

Peers

Matthew Matl
Comparison fields: 5 of 71
  • Control and Systems Engineering 584
  • Biomedical Engineering 330
  • Computer Vision and Pattern Recognition 221
  • Artificial Intelligence 147
  • Mechanical Engineering 142
Replace Tetsuo Kotoku with:
Tetsuo Kotoku Japan
Torsten Kröger Germany
K. Kitagaki Japan
Marc Freese Japan
Francisco J. Rodríguez Spain
Berthold Bäuml Germany
Hsu‐Chih Huang Taiwan
Jonathan Bohren United States
Eitan Marder-Eppstein United States
José Simó Spain
Matthew Matl relative to Tetsuo Kotoku Japan Tetsuo Kotoku's profile →
Citations per field
00.5×10×20×33.5×
Tetsuo Kotoku · 1×
Citations per year

Countries citing papers authored by Matthew Matl

Since Specialization
Citations

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

Fields of papers citing papers by Matthew Matl

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matthew Matl

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

All Works

11 of 11 papers shown
#WorkIndexed citations
1 120
2
Learning ambidextrous robot grasping policiesbreakdown →
371
3 4
4
Segmenting Unknown 3D Objects from Real Depth Images using Mask R-CNN Trained on Synthetic Point Clouds.
10
5 209
6 26
7 1
8 37
9 6
10 19
11 115

About Matthew Matl

Matthew Matl is a scholar working on Hardware and Architecture, Computer Networks and Communications and Control and Systems Engineering, having authored 11 papers that have together received 918 indexed citations. Recurring topics across this work include Interconnection Networks and Systems (5 papers), Parallel Computing and Optimization Techniques (5 papers) and Embedded Systems Design Techniques (5 papers). The work is most often cited by research in Control and Systems Engineering (584 citations), Hardware and Architecture (134 citations) and Human-Computer Interaction (87 citations). Matthew Matl has collaborated with scholars based in United States and China. Frequent co-authors include Ken Goldberg, Jeffrey Mahler, Michael Danielczuk, Stephen McKinley, Vishal Satish, Xinyu Liu, Albert P. Li, David V. Gealy, Andrew C. Li and Saurabh Gupta. Their work appears in journals such as Communications of the ACM, Science Robotics and ACM SIGPLAN Notices.

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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