Mo Jamshidi

232 papers receiving 3.3k citations

Peers

Mo Jamshidi
Comparison fields: 5 of 147
  • Control and Systems Engineering 1.2k
  • Computer Vision and Pattern Recognition 888
  • Computer Networks and Communications 903
  • Management Science and Operations Research 284
  • Artificial Intelligence 674
Replace Alaa Khamis with:
Alaa Khamis Canada
Otman Basir Canada
Lucian Buşoniu Romania
Marco Wiering Netherlands
Frank Hoffmann Germany
Luca Iocchi Italy
Meiqin Liu China
Anthony R. Cassandra United States
J. Zico Kolter United States
Milos Manic United States
Mo Jamshidi relative to Alaa Khamis Canada Alaa Khamis's profile →
Citations per field
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Alaa Khamis · 1×
Citations per year

Countries citing papers authored by Mo Jamshidi

Since Specialization
Citations

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

Fields of papers citing papers by Mo Jamshidi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 247 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2001161
2 2011134
3 201187
4 201186
5 201985
6 200783
7 201777
8 200774
9 201072
10 202070
11 201468
12 201467
13 199761
14 201359
15 202151
16 200350
17 200850
18 201850
19 201447
20 200344

About Mo Jamshidi

Mo Jamshidi is a scholar working on Control and Systems Engineering, Computer Vision and Pattern Recognition, Computer Networks and Communications, Artificial Intelligence and Electrical and Electronic Engineering, having authored 247 papers that have together received 3.5k indexed citations. Recurring topics across this work include Robotic Path Planning Algorithms (37 papers), Distributed Control Multi-Agent Systems (29 papers), Modular Robots and Swarm Intelligence (26 papers), Robotics and Sensor-Based Localization (18 papers), Underwater Vehicles and Communication Systems (16 papers), Cloud Computing and Resource Management (16 papers), Systems Engineering Methodologies and Applications (16 papers) and Energy Efficient Wireless Sensor Networks (13 papers). The work is most often cited by research in Control and Systems Engineering (1.2k citations), Computer Vision and Pattern Recognition (888 citations), Computer Networks and Communications (903 citations), Management Science and Operations Research (284 citations) and Artificial Intelligence (674 citations). Mo Jamshidi has collaborated with scholars based in United States, India and Australia. Frequent co-authors include Patrick Benavidez, Paul Rad, Laxmidhar Behera, Brian Kelley, John J. Prevost, Matthew Joordens, Prasanna Sridhar, Berat A. Erol, Edward Tunstel and Asad M. Madni. Their work appears in journals such as IEEE Systems Journal, Journal of Intelligent & Robotic Systems, Computers & Electrical Engineering, IEEE Transactions on Robotics and Automation and Journal of Industrial Information Integration.

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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