Haokun Mao

615 total citations · 1 hit paper
32 papers, 327 citations indexed

About

Haokun Mao is a scholar working on Artificial Intelligence, Atomic and Molecular Physics, and Optics and Computational Theory and Mathematics. According to data from OpenAlex, Haokun Mao has authored 32 papers receiving a total of 327 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Artificial Intelligence, 9 papers in Atomic and Molecular Physics, and Optics and 8 papers in Computational Theory and Mathematics. Recurrent topics in Haokun Mao's work include Quantum Computing Algorithms and Architecture (22 papers), Quantum Information and Cryptography (22 papers) and Quantum-Dot Cellular Automata (8 papers). Haokun Mao is often cited by papers focused on Quantum Computing Algorithms and Architecture (22 papers), Quantum Information and Cryptography (22 papers) and Quantum-Dot Cellular Automata (8 papers). Haokun Mao collaborates with scholars based in China, Saudi Arabia and Egypt. Haokun Mao's co-authors include Qiong Li, Han Qi, Jia Huang, Yang Liu, Hong Guo, Yichen Lu, Hao Li, Qiang Zhang, Lixing You and Cheng-Zhi Peng and has published in prestigious journals such as Nature Photonics, Optics Express and Expert Systems with Applications.

In The Last Decade

Haokun Mao

30 papers receiving 310 citations

Hit Papers

High-rate quantum key distribution exceeding 110 Mb s–1 2023 2026 2024 2023 50 100 150
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. High-rate quantum key distribution exceeding 110 Mb s–1
    2023 152 citations Wei Li, Hao Tan et al. Nature Photonics profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Haokun Mao China 9 255 140 77 46 36 32 327
Marco Avesani Italy 10 265 1.0× 251 1.8× 48 0.6× 16 0.3× 25 0.7× 26 330
Andrea Stanco Italy 10 224 0.9× 208 1.5× 56 0.7× 11 0.2× 14 0.4× 20 291
Jake Kennard United Kingdom 7 318 1.2× 249 1.8× 202 2.6× 14 0.3× 39 1.1× 12 424
Philip Sibson United Kingdom 7 392 1.5× 296 2.1× 245 3.2× 20 0.4× 41 1.1× 19 497
Xiaomin Guo China 12 205 0.8× 156 1.1× 107 1.4× 17 0.4× 76 2.1× 37 353
Matej Pivoluska Slovakia 11 317 1.2× 272 1.9× 31 0.4× 33 0.7× 34 0.9× 24 352
Yanqiang Guo China 12 228 0.9× 204 1.5× 91 1.2× 18 0.4× 81 2.3× 54 400
Wenyuan Wang Canada 11 355 1.4× 264 1.9× 62 0.8× 19 0.4× 15 0.4× 21 411
Anastase Nakassis United States 10 243 1.0× 172 1.2× 52 0.7× 43 0.9× 12 0.3× 33 338

Countries citing papers authored by Haokun Mao

Since Specialization
Citations

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

Fields of papers citing papers by Haokun Mao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Haokun Mao

This figure shows the co-authorship network connecting the top 25 collaborators of Haokun Mao. A scholar is included among the top collaborators of Haokun 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 Haokun Mao. Haokun 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.
Mao, Haokun, et al.. (2025). Clustered federated learning enhanced by DAG-based blockchain with adaptive tip selection algorithm. Internet of Things. 31. 101573–101573. 1 indexed citations
3.
Li, Qiong, et al.. (2025). Federated semi-supervised learning via globally guided pseudo-labeling: A robust approach for label-scarce scenarios. Expert Systems with Applications. 294. 128667–128667.
4.
Li, Qiong, et al.. (2024). Magnetoencephalography Decoding Transfer Approach: From Deep Learning Models to Intrinsically Interpretable Models. IEEE Journal of Biomedical and Health Informatics. 28(5). 2818–2829. 1 indexed citations
5.
Li, Qiong, et al.. (2024). A Practical Multiprotocol Collaborative Quantum Key Distribution Networking Scheme for Consumer Electronics Devices. IEEE Transactions on Consumer Electronics. 71(1). 1190–1200. 5 indexed citations
6.
Li, Qiong, et al.. (2024). A Multi-Scenario Authenticated Key Exchange Scheme With Forward Secrecy for Fog-Enabled VANETs. IEEE Transactions on Vehicular Technology. 74(1). 831–846. 3 indexed citations
7.
Luo, Yi, Xi Cheng, Haokun Mao, & Qiong Li. (2024). An Overview of Postprocessing in Quantum Key Distribution. Mathematics. 12(14). 2243–2243. 4 indexed citations
8.
Mao, Haokun, et al.. (2023). A Model-Agnostic Feature Attribution Approach to Magnetoencephalography Predictions Based on Shapley Value. IEEE Journal of Biomedical and Health Informatics. 27(5). 2524–2535. 6 indexed citations
9.
Li, Wei, Hao Tan, Yichen Lu, et al.. (2023). High-rate quantum key distribution exceeding 110 Mb s–1. Nature Photonics. 17(5). 416–421. 152 indexed citations breakdown →
10.
Yamni, Mohamed, Achraf Daoui, Paweł Pławiak, et al.. (2023). A Novel 3D Reversible Data Hiding Scheme Based on Integer–Reversible Krawtchouk Transform for IoMT. Sensors. 23(18). 7914–7914. 5 indexed citations
11.
Daoui, Achraf, Haokun Mao, Mohamed Yamni, et al.. (2023). Novel Integer Shmaliy Transform and New Multiparametric Piecewise Linear Chaotic Map for Joint Lossless Compression and Encryption of Medical Images in IoMTs. Mathematics. 11(16). 3619–3619. 10 indexed citations
12.
Mao, Haokun, et al.. (2023). A Remote Quantum Error-Correcting Code Preparation Protocol on Cluster States. Mathematics. 11(14). 3035–3035. 1 indexed citations
13.
Mao, Haokun, et al.. (2022). An Energy Efficient Specializing DAG Federated Learning Based on Event-Triggered Communication. Mathematics. 10(22). 4388–4388. 3 indexed citations
14.
Li, Qiong, et al.. (2022). An Efficient Routing Protocol for Quantum Key Distribution Networks. Entropy. 24(7). 911–911. 11 indexed citations
15.
Li, Qiong, et al.. (2022). Large-Scale and High-Speed FPGA-Based Privacy Amplification for Quantum Key Distribution. Journal of Lightwave Technology. 41(1). 169–175. 4 indexed citations
16.
Mao, Haokun, et al.. (2021). High-Efficient Syndrome-Based LDPC Reconciliation for Quantum Key Distribution. Entropy. 23(11). 1440–1440. 8 indexed citations
17.
Li, Qiong, et al.. (2021). An Improved Slice Reconciliation Protocol for Continuous-Variable Quantum Key Distribution. Entropy. 23(10). 1317–1317. 4 indexed citations
18.
Li, Qiong, et al.. (2020). Novel reconciliation protocol based on spinal code for continuous-variable quantum key distribution. Quantum Information Processing. 19(10). 10 indexed citations
19.
Wang, Yaxing, et al.. (2020). Topological optimization of hybrid quantum key distribution networks. Optics Express. 28(18). 26348–26348. 8 indexed citations
20.
Li, Qiong, et al.. (2014). An FPGA-Based Communication Scheme of Classical Channel in High-Speed QKD System. 11. 227–230. 3 indexed citations

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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