Bomin Mao

6.2k total citations · 7 hit papers
66 papers, 4.5k citations indexed

About

Bomin Mao is a scholar working on Computer Networks and Communications, Electrical and Electronic Engineering and Aerospace Engineering. According to data from OpenAlex, Bomin Mao has authored 66 papers receiving a total of 4.5k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Computer Networks and Communications, 33 papers in Electrical and Electronic Engineering and 15 papers in Aerospace Engineering. Recurrent topics in Bomin Mao's work include Advanced Wireless Communication Technologies (14 papers), Software-Defined Networks and 5G (11 papers) and Network Security and Intrusion Detection (10 papers). Bomin Mao is often cited by papers focused on Advanced Wireless Communication Technologies (14 papers), Software-Defined Networks and 5G (11 papers) and Network Security and Intrusion Detection (10 papers). Bomin Mao collaborates with scholars based in Japan, China and Canada. Bomin Mao's co-authors include Nei Kato, Fengxiao Tang, Zubair Md. Fadlullah, Yuichi Kawamoto, Osamu Akashi, Takeru Inoue, Kimihiro Mizutani, Jiajia Liu, Shigenori Tani and Atsushi Okamura and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Communications Surveys & Tutorials and IEEE Access.

In The Last Decade

Bomin Mao

64 papers receiving 4.4k citations

Hit Papers

State-of-the-Art Deep Learning: Evolving Machine Intellig... 2016 2026 2019 2022 2017 2019 2016 2017 2020 200 400 600
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. State-of-the-Art Deep Learning: Evolving Machine Intelligence Toward Tomorrow’s Intelligent Network Traffic Control Systems
    2017 606 citations Zubair Md. Fadlullah, Fengxiao Tang et al. IEEE Communications Surveys & Tutorials profile →
  2. Optimizing Space-Air-Ground Integrated Networks by Artificial Intelligence
    2019 326 citations Nei Kato, Zubair Md. Fadlullah et al. profile →
  3. The Deep Learning Vision for Heterogeneous Network Traffic Control: Proposal, Challenges, and Future Perspective
    2016 324 citations Nei Kato, Zubair Md. Fadlullah et al. profile →
  4. Routing or Computing? The Paradigm Shift Towards Intelligent Computer Network Packet Transmission Based on Deep Learning
    2017 292 citations Bomin Mao, Zubair Md. Fadlullah et al. IEEE Transactions on Computers profile →
  5. Ten Challenges in Advancing Machine Learning Technologies toward 6G
    2020 292 citations Nei Kato, Bomin Mao et al. profile →
  6. Security and Privacy on 6G Network Edge: A Survey
    2023 159 citations Bomin Mao, Jiajia Liu et al. IEEE Communications Surveys & Tutorials profile →
  7. A Survey on Intelligent Network Operations and Performance Optimization Based on Large Language Models
    2025 22 citations Bomin Mao, Fengxiao Tang et al. IEEE Communications Surveys & Tutorials profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Bomin Mao Japan 28 2.4k 2.3k 1.0k 1.0k 354 66 4.5k
Feng Lyu China 34 2.8k 1.2× 2.3k 1.0× 1.1k 1.1× 1.4k 1.3× 528 1.5× 133 5.0k
Lingjia Liu United States 40 2.4k 1.0× 3.9k 1.7× 1.0k 1.0× 1.0k 1.0× 201 0.6× 254 5.2k
Lian Zhao Canada 43 3.3k 1.4× 3.1k 1.3× 613 0.6× 1.2k 1.1× 413 1.2× 241 5.3k
Dingde Jiang China 34 2.0k 0.8× 1.3k 0.6× 637 0.6× 377 0.4× 336 0.9× 148 3.5k
Ahmed Al‐Dubai United Kingdom 30 1.9k 0.8× 1.7k 0.7× 430 0.4× 464 0.5× 363 1.0× 160 3.4k
Changchuan Yin China 30 2.9k 1.2× 3.0k 1.3× 1.5k 1.5× 1.1k 1.1× 475 1.3× 185 5.1k
Eli De Poorter Belgium 34 1.9k 0.8× 3.1k 1.4× 513 0.5× 929 0.9× 358 1.0× 208 4.5k
Yuan Wu China 36 2.1k 0.9× 1.7k 0.7× 841 0.8× 1.2k 1.2× 551 1.6× 220 4.1k
Abderrahim Benslimane France 35 2.6k 1.1× 2.0k 0.9× 832 0.8× 585 0.6× 358 1.0× 189 4.1k
Haipeng Dai China 39 2.0k 0.8× 2.4k 1.0× 612 0.6× 649 0.6× 376 1.1× 249 4.3k

Countries citing papers authored by Bomin Mao

Since Specialization
Citations

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

Fields of papers citing papers by Bomin Mao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bomin Mao

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

All Works

20 of 20 papers shown
1.
2.
3.
Mao, Bomin, Yingying Wu, Jiajia Liu, et al.. (2024). Optimizing Secrecy Rate for Federated Learning Model Aggregation With Intelligent Reflecting Surface Toward 6G Ubiquitous Intelligence. IEEE Transactions on Cognitive Communications and Networking. 11(2). 1258–1267. 14 indexed citations
4.
Mao, Bomin, Xueming Zhou, Jiajia Liu, & Nei Kato. (2024). On an Intelligent Hierarchical Routing Strategy for Ultra-Dense Free Space Optical Low Earth Orbit Satellite Networks. IEEE Journal on Selected Areas in Communications. 42(5). 1219–1230. 48 indexed citations
5.
Mao, Bomin, et al.. (2024). An Intelligent Path Loss Prediction Approach Based on Integrated Sensing and Communications for Future Vehicular Networks. SHILAP Revista de lepidopterología. 5. 170–180. 7 indexed citations
6.
Mao, Bomin, Xueming Zhou, Jiajia Liu, & Nei Kato. (2023). Digital Twin Satellite Networks Toward 6G: Motivations, Challenges, and Future Perspectives. IEEE Network. 38(1). 54–60. 23 indexed citations
7.
Mao, Bomin, Jian Qiu, & Nei Kato. (2023). On an Intelligent Task Offloading Model to Jointly Optimize Latency and Energy for Electric Connected Vehicles. IEEE Transactions on Vehicular Technology. 73(4). 6024–6028. 20 indexed citations
8.
Liu, Jiajia, et al.. (2023). A Spatiotemporal Backdoor Attack Against Behavior-Oriented Decision Makers in Metaverse: From Perspective of Autonomous Driving. IEEE Journal on Selected Areas in Communications. 42(4). 948–962. 7 indexed citations
9.
Mao, Bomin, et al.. (2023). IRS-Aided High-Accuracy Positioning for Autonomous Driving Toward 6G: A Tutorial. IEEE Vehicular Technology Magazine. 19(1). 85–92. 27 indexed citations
10.
Mao, Bomin, et al.. (2022). A Dynamic Task Scheduling Strategy for Multi-Access Edge Computing in IRS-Aided Vehicular Networks. IEEE Transactions on Emerging Topics in Computing. 10(4). 1761–1771. 71 indexed citations
11.
Mao, Bomin, et al.. (2022). Intelligent Reflecting Surface in 6G Vehicular Communications: A Survey. IEEE Open Journal of Vehicular Technology. 3. 266–277. 83 indexed citations
12.
Mao, Bomin, Fengxiao Tang, Yuichi Kawamoto, & Nei Kato. (2021). AI Models for Green Communications Towards 6G. IEEE Communications Surveys & Tutorials. 24(1). 210–247. 177 indexed citations
13.
Tang, Fengxiao, Bomin Mao, Nei Kato, & Guan Gui. (2021). Comprehensive Survey on Machine Learning in Vehicular Network: Technology, Applications and Challenges. IEEE Communications Surveys & Tutorials. 23(3). 2027–2057. 163 indexed citations
14.
Kawamoto, Yuichi, et al.. (2019). Multilayer Virtual Cell-Based Resource Allocation in Low-Power Wide-Area Networks. IEEE Internet of Things Journal. 6(6). 10665–10674. 12 indexed citations
15.
Tang, Fengxiao, Bomin Mao, Zubair Md. Fadlullah, Jiajia Liu, & Nei Kato. (2019). ST-DeLTA: A Novel Spatial-Temporal Value Network Aided Deep Learning Based Intelligent Network Traffic Control System. IEEE Transactions on Sustainable Computing. 5(4). 568–580. 21 indexed citations
16.
Mao, Bomin, Fengxiao Tang, Zubair Md. Fadlullah, & Nei Kato. (2019). An Intelligent Route Computation Approach Based on Real-Time Deep Learning Strategy for Software Defined Communication Systems. IEEE Transactions on Emerging Topics in Computing. 9(3). 1554–1565. 107 indexed citations
17.
Fadlullah, Zubair Md., Bomin Mao, Fengxiao Tang, & Nei Kato. (2018). Value Iteration Architecture Based Deep Learning for Intelligent Routing Exploiting Heterogeneous Computing Platforms. IEEE Transactions on Computers. 68(6). 939–950. 40 indexed citations
18.
Tang, Fengxiao, Zubair Md. Fadlullah, Bomin Mao, et al.. (2018). On A Novel Adaptive UAV-Mounted Cloudlet-Aided Recommendation System for LBSNs. IEEE Transactions on Emerging Topics in Computing. 7(4). 565–577. 72 indexed citations
19.
Fadlullah, Zubair Md., Fengxiao Tang, Bomin Mao, Jiajia Liu, & Nei Kato. (2018). On Intelligent Traffic Control for Large-Scale Heterogeneous Networks: A Value Matrix-Based Deep Learning Approach. IEEE Communications Letters. 22(12). 2479–2482. 39 indexed citations
20.
Fadlullah, Zubair Md., Fengxiao Tang, Bomin Mao, et al.. (2017). State-of-the-Art Deep Learning: Evolving Machine Intelligence Toward Tomorrow’s Intelligent Network Traffic Control Systems. IEEE Communications Surveys & Tutorials. 19(4). 2432–2455. 606 indexed citations breakdown →

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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