World's Best Scientists 2026 revealed!
Sangman Moh

Sangman Moh

D-Index & Metrics

Engineering and Technology

D-Index
38
Citations
5029
World Ranking
8140
National Ranking
218

Sangman Moh publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Sangman Moh sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38 publications 804+

This scientist: 204 publications — 50th percentile

50% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

Sangman Moh D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Sangman Moh sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 38 D-Index — 20th percentile

20% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

Overview

Sangman Moh is affiliated with Chosun University in South Korea. Their research predominantly spans the fields of Computer Science and Engineering with a significant focus on Computer Networks and Communications, Aerospace Engineering, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering, and Automotive Engineering.

The scholar's main topics of study address challenges and advancements in UAV Applications and Optimization, IoT and Edge/Fog Computing, Distributed Control Multi-Agent Systems, Opportunistic and Delay-Tolerant Networks, Energy Efficient Wireless Sensor Networks, Robotic Path Planning Algorithms, and Mobile Ad Hoc Networks.

Recent publication venues for Sangman Moh include Sensors, IEEE Access, IEEE Internet of Things Journal, Journal of Network and Computer Applications, and Vehicular Communications. Notably, Sensors and IEEE Access have hosted nine and eight of their publications respectively.

  • Vision-Based Navigation Techniques for Unmanned Aerial Vehicles: Review and Challenges, 2023, Drones
  • Survey on computation offloading in UAV-Enabled mobile edge computing, 2022, Journal of Network and Computer Applications
  • A Q-Learning-Based Topology-Aware Routing Protocol for Flying Ad Hoc Networks, 2021, IEEE Internet of Things Journal
  • Routing Protocols for Unmanned Aerial Vehicle-Aided Vehicular Ad Hoc Networks: A Survey, 2020, IEEE Access
  • Bio-Inspired Approaches for Energy-Efficient Localization and Clustering in UAV Networks for Monitoring Wildfires in Remote Areas, 2021, IEEE Access

Sangman Moh has collaborated frequently with a number of co-authors, including Muhammad Yeasir Arafat, Muhammad Morshed Alam, Sabitri Poudel, S. M. Asiful Huda, and Rezoan Ahmed Nazib.

Best Publications

  • Localization and Clustering Based on Swarm Intelligence in UAV Networks for Emergency Communications

    Muhammad Yeasir Arafat;Sangman Moh

  • Spectrum mobility in cognitive radio networks

    I. Christian;Sangman Moh;Ilyong Chung;Jinyi Lee

  • Vision-Based Navigation Techniques for Unmanned Aerial Vehicles: Review and Challenges

    Unknown

  • Routing Protocols for Unmanned Aerial Vehicle Networks: A Survey

    Muhammad Yeasir Arafat;Sangman Moh

  • Survey on computation offloading in UAV-Enabled mobile edge computing

    Unknown

  • A Survey on Cluster-Based Routing Protocols for Unmanned Aerial Vehicle Networks

    Muhammad Yeasir Arafat;Sangman Moh

  • A Q-Learning-Based Topology-Aware Routing Protocol for Flying Ad Hoc Networks

    Muhammad Yeasir Arafat;Sangman Moh

  • CD-MAC: Cooperative Diversity MAC for Robust Communication in Wireless Ad Hoc Networks

    Sangman Moh;Chansu Yu;Seung-Min Park;Heung-Nam Kim

  • Routing Protocols for Unmanned Aerial Vehicle-Aided Vehicular Ad Hoc Networks: A Survey

    Rezoan Ahmed Nazib;Sangman Moh

  • Location-Aided Delay Tolerant Routing Protocol in UAV Networks for Post-Disaster Operation

    Muhammad Yeasir Arafat;Sangman Moh

  • A Priority-Based Adaptive MAC Protocol for Wireless Body Area Networks.

    Sabin Bhandari;Sangman Moh

  • Enhanced secure sensor association and key management in wireless body area networks

    Jian Shen;Haowen Tan;Sangman Moh;Ilyong Chung

  • Topology control algorithms in multi-unmanned aerial vehicle networks: An extensive survey

    Unknown

  • Bio-Inspired Approaches for Energy-Efficient Localization and Clustering in UAV Networks for Monitoring Wildfires in Remote Areas

    Muhammad Yeasir Arafat;Sangman Moh

  • Task assignment algorithms for unmanned aerial vehicle networks: A comprehensive survey

    Unknown

  • Reinforcement Learning-Based Routing Protocols for Vehicular Ad Hoc Networks: A Comparative Survey

    Rezoan Ahmed Nazib;Sangman Moh

  • A Cooperative Diversity-Based Robust MAC Protocol in Wireless Ad Hoc Networks

    Sangman Moh;Chansu Yu

  • Bio-Inspired Optimization-Based Path Planning Algorithms in Unmanned Aerial Vehicles: A Survey

    Unknown

  • Wireless Power Transfer in Wirelessly Powered Sensor Networks: A Review of Recent Progress

    Unknown

  • Survey on Recent Advancements in Energy-Efficient Routing Protocols for Underwater Wireless Sensor Networks

    Shreya Khisa;Sangman Moh

  • A survey on temperature-aware routing protocols in wireless body sensor networks.

    Christian Henry Wijaya Oey;Sangman Moh

  • Comprehensive Survey of Radio Resource Allocation Schemes for 5G V2X Communications

    Thien Thi Thanh Le;Sangman Moh

  • Interference Mitigation Schemes for Wireless Body Area Sensor Networks: A Comparative Survey

    Thien T.T. Le;Sangman Moh

  • Organized topology based routing protocol in incompletely predictable ad-hoc networks

    Jian Shen;Chen Wang;Anxi Wang;Xingming Sun

  • A Survey of MAC Protocols for Cognitive Radio Body Area Networks

    Sabin Bhandari;Sangman Moh

  • An Efficient RFID Authentication Protocol Providing Strong Privacy and Security

    Jian Shen;Haowen Tan;Sangman Moh;Ilyong Chung

  • An Energy-Efficient Game-Theory-Based Spectrum Decision Scheme for Cognitive Radio Sensor Networks

    Shelly Salim;Sangman Moh

  • An Interference-Aware Traffic-Priority-Based Link Scheduling Algorithm for Interference Mitigation in Multiple Wireless Body Area Networks

    Thien T. T. Le;Sangman Moh

  • Secure and Efficient Data Sharing in Dynamic Vehicular Networks

    Jian Shen;Tianqi Zhou;Jinfeng Lai;Pan Li

  • Residual energy-based clustering in UAV-aided wireless sensor networks for surveillance and monitoring applications

    Sabitri Poudel;Sangman Moh;Jian Shen

  • An Energy-Efficient and Compact Clustering Scheme with Temporary Support Nodes for Cognitive Radio Sensor Networks

    Shelly Salim;Sangman Moh;Dongmin Choi;Ilyong Chung

  • A Spectrum-Aware Priority-Based Link Scheduling Algorithm for Cognitive Radio Body Area Networks.

    Thien Thi Thanh Le;Sangman Moh

  • A Robust and Energy-Efficient Transport Protocol for Cognitive Radio Sensor Networks

    Shelly Salim;Sangman Moh

  • A Low-Interference Channel Status Prediction Algorithm for Instantaneous Spectrum Access in Cognitive Radio Networks

    Ivan Christian;Sangman Moh

  • Energy-Efficient Protocol of Link Scheduling in Cognitive Radio Body Area Networks for Medical and Healthcare Applications.

    Thien Thi Thanh Le;Sangman Moh

  • Data prediction Strategy for Sensor Network Clustering Scheme

    Dong-Min Choi;Jian Shen;Sang-Man Moh;Il-Yong Chung

Frequent Co-Authors

Jian Shen
Jian Shen Nanjing University of Information Science and Technology
Xingming Sun
Xingming Sun Nanjing University of Information Science and Technology
Pan Li
Pan Li Case Western Reserve University
Theodoros Salonidis
Theodoros Salonidis IBM (United States)
Victor C. M. Leung
Victor C. M. Leung Shenzhen University
Leandros Tassiulas
Leandros Tassiulas Yale University
Ali C. Begen
Ali C. Begen Özyeğin University
Iordanis Koutsopoulos
Iordanis Koutsopoulos Athens University of Economics and Business
Patrick C. K. Hung
Patrick C. K. Hung University of Ontario Institute of Technology

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