Mohammad Biglarbegian

2.2k citations
81 papers · 1.8k · h-index 20

Impact in

Papers in

Mohammad Biglarbegian

79 papers receiving 1.8k citations

Peers

Mohammad Biglarbegian
Comparison fields: 5 of 113
  • Automotive Engineering 351
  • Control and Systems Engineering 650
  • Statistics and Probability 140
  • Artificial Intelligence 561
  • Mechanical Engineering 362
Replace Wei‐Yen Wang with:
Wei‐Yen Wang Taiwan
Tao Zhao China
Chun‐Fei Hsu Taiwan
Sung‐Soo Kim South Korea
Jing Chen China
Mohammad Farrokhi Iran
Biao Wang China
A.B. Rad Hong Kong
Zhen Liu China
Jin S. Lee South Korea
Mohammad Biglarbegian relative to Wei‐Yen Wang Taiwan Wei‐Yen Wang's profile →
Citations per field
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Citations per year

Countries citing papers authored by Mohammad Biglarbegian

Since Specialization
Citations

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

Fields of papers citing papers by Mohammad Biglarbegian

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 81 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019290
2 2009269
3 2016178
4 2010127
5 2010110
6 201678
7 200852
8 201635
9 201833
10 202033
11 201532
12 201324
13 200723
14 201822
15 201321
16 201621
17 202221
18 200621
19 201220
20 201819

About Mohammad Biglarbegian

Mohammad Biglarbegian is a scholar working on Control and Systems Engineering, Mechanical Engineering, Computer Vision and Pattern Recognition, Artificial Intelligence and Aerospace Engineering, having authored 81 papers that have together received 1.8k indexed citations. Recurring topics across this work include Robotic Path Planning Algorithms (15 papers), Fuzzy Logic and Control Systems (12 papers), Control and Dynamics of Mobile Robots (10 papers), Adaptive Control of Nonlinear Systems (9 papers), Neural Networks and Applications (8 papers), Fault Detection and Control Systems (8 papers), Vehicle Dynamics and Control Systems (7 papers) and Modular Robots and Swarm Intelligence (7 papers). The work is most often cited by research in Automotive Engineering (351 citations), Control and Systems Engineering (650 citations), Statistics and Probability (140 citations), Artificial Intelligence (561 citations) and Mechanical Engineering (362 citations). Mohammad Biglarbegian has collaborated with scholars based in Canada, United States and Iran. Frequent co-authors include William Melek, Jerry M. Mendel, Shohel Mahmud, S. Andrew Gadsden, Abdulrahman M. El‐Sayed, Kevin Tai, Shaikh Hasibul Majid, Abu Raihan Mohammad Siddique, Simon X. Yang and Farid Golnaraghi. Their work appears in journals such as Robotics, Vehicle System Dynamics, Journal of Intelligent & Robotic Systems, IEEE/ASME Transactions on Mechatronics and Information Sciences.

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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