Ting Cai

704 total citations · 1 hit paper
31 papers, 441 citations indexed

About

Ting Cai is a scholar working on Information Systems, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Ting Cai has authored 31 papers receiving a total of 441 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Information Systems, 12 papers in Artificial Intelligence and 10 papers in Computer Networks and Communications. Recurrent topics in Ting Cai's work include Blockchain Technology Applications and Security (10 papers), IoT and Edge/Fog Computing (8 papers) and Privacy-Preserving Technologies in Data (5 papers). Ting Cai is often cited by papers focused on Blockchain Technology Applications and Security (10 papers), IoT and Edge/Fog Computing (8 papers) and Privacy-Preserving Technologies in Data (5 papers). Ting Cai collaborates with scholars based in China, United States and Hong Kong. Ting Cai's co-authors include Wuhui Chen, Hong‐Ning Dai, Zibin Zheng, Xiaoyu Qiu, Yan Zhang, Peter A. Gloor, Yang Yu, Zibin Zheng, Zhihua Yang and Zhiwei Ye and has published in prestigious journals such as Chemical Communications, Scientific Reports and IEEE Communications Surveys & Tutorials.

In The Last Decade

Ting Cai

24 papers receiving 418 citations

Hit Papers

Deep Reinforcement Learning for Internet of Things: A Com... 2021 2026 2022 2024 2021 50 100 150 200

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ting Cai China 9 214 126 110 103 67 31 441
Pino Caballero‐Gil Spain 13 253 1.2× 135 1.1× 146 1.3× 183 1.8× 25 0.4× 107 581
Konstantin Igorevich Kostromitin Russia 12 219 1.0× 104 0.8× 168 1.5× 179 1.7× 68 1.0× 38 542
Mohammad Hayajneh United Arab Emirates 11 339 1.6× 103 0.8× 176 1.6× 257 2.5× 32 0.5× 52 646
Xihua Liu China 9 318 1.5× 190 1.5× 138 1.3× 134 1.3× 19 0.3× 26 485
Wenjia Niu China 12 210 1.0× 119 0.9× 166 1.5× 54 0.5× 18 0.3× 67 426
Paul Sant United Kingdom 12 125 0.6× 247 2.0× 151 1.4× 145 1.4× 55 0.8× 42 605
Qianqian Pan China 12 279 1.3× 118 0.9× 154 1.4× 234 2.3× 60 0.9× 34 601
Xiaolei Liu China 12 172 0.8× 220 1.7× 235 2.1× 90 0.9× 49 0.7× 63 595
Weichao Gao United States 9 282 1.3× 212 1.7× 144 1.3× 101 1.0× 45 0.7× 21 491
Zhanyang Xu China 11 314 1.5× 178 1.4× 161 1.5× 119 1.2× 15 0.2× 30 539

Countries citing papers authored by Ting Cai

Since Specialization
Citations

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

Fields of papers citing papers by Ting Cai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ting Cai

This figure shows the co-authorship network connecting the top 25 collaborators of Ting Cai. A scholar is included among the top collaborators of Ting Cai 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 Ting Cai. Ting Cai 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.
He, Xiaoming, Huawei Huang, Chun Wang, et al.. (2025). A Fairness-Guaranteed Framework for Semi-Asynchronous Federated Learning. IEEE Transactions on Network Science and Engineering. 12(6). 4462–4479. 2 indexed citations
2.
Cai, Ting, Fan Ma, Zhiwei Ye, et al.. (2025). Dynamic niche technology based hybrid breeding optimization algorithm for multimodal feature selection. Scientific Reports. 15(1). 8001–8001. 2 indexed citations
3.
Cai, Ting, et al.. (2025). Multiagent Deep Reinforcement Learning for Transactive Energy Management of MMGs Incorporating Battery Swapping Stations. IEEE Transactions on Industrial Informatics. 21(7). 5677–5688. 2 indexed citations
4.
Ỹe, Zhiwei, Songsong Zhang, Zhou Wen, et al.. (2025). HBOFFS: Hybrid breeding optimization algorithm inspired federated feature selection for intrusion detection in IIoT. Knowledge-Based Systems. 329. 114419–114419.
5.
Cai, Ting, et al.. (2025). Resilience driven EV coordination in multiple microgrids using distributed deep reinforcement learning. Scientific Reports. 15(1). 27038–27038. 1 indexed citations
6.
Wang, Chun, et al.. (2024). Libra: A Fairness-Guaranteed Framework for Semi-Asynchronous Federated Learning. 797–808. 1 indexed citations
7.
Cai, Ting, Xiang Li, Yifei Wang, et al.. (2024). TEMP: Cost-Aware Two-Stage Energy Management for Electrical Vehicles Empowered by Blockchain. IEEE Internet of Things Journal. 11(23). 38246–38261. 1 indexed citations
8.
Chen, Wuhui, Zicong Hong, Jianting Zhang, et al.. (2024). Sparrow: Expediting Smart Contract Execution for Blockchain Sharding via Inter-Shard Caching. IEEE Transactions on Parallel and Distributed Systems. 36(3). 377–390. 1 indexed citations
9.
Cai, Ting, Zhiwei Ye, Pan Hu, et al.. (2024). Dynamic Niches-Based Hybrid Breeding Optimization Algorithm for Solving Multi-Modal Optimization Problem. Mathematics. 12(17). 2779–2779.
10.
Cai, Ting, Wuhui Chen, Jianting Zhang, & Zibin Zheng. (2024). SmartChain: A Dynamic and Self-Adaptive Sharding Framework for IoT Blockchain. IEEE Transactions on Services Computing. 17(2). 674–688. 13 indexed citations
11.
Cai, Ting, Ying Hu, Xiang Li, et al.. (2024). Incentive Sharing: A Consumer-Data Privacy Trusted Sharing Paradigm via Proximal Policy Optimization in Industry 5.0. IEEE Transactions on Consumer Electronics. 71(2). 3378–3390.
12.
13.
Cai, Ting, et al.. (2024). Multi-Label Feature Selection Based on Improved Ant Colony Optimization Algorithm with Dynamic Redundancy and Label Dependence. Computers, materials & continua/Computers, materials & continua (Print). 81(1). 1157–1175. 1 indexed citations
14.
Cai, Ting, et al.. (2024). The role of blockchain technology in facilitating finance for metal and mining resources. Resources Policy. 99. 105383–105383. 2 indexed citations
15.
He, Qiyi, et al.. (2023). Object Detection Based on Lightweight YOLOX for Autonomous Driving. Sensors. 23(17). 7596–7596. 19 indexed citations
16.
Cai, Ting, et al.. (2023). MDRL-IR: Incentive Routing for Blockchain Scalability With Memory-Based Deep Reinforcement Learning. IEEE Transactions on Services Computing. 16(6). 4375–4388.
17.
Cai, Ting, et al.. (2021). The Effect of Union Practice on Employee Organizational Citizenship Behavior: The Mediator Role of Psychological Contract and The Moderating Role of High-Performance Human Resource Practice. 194–208. 2 indexed citations
18.
Cai, Ting, Zhihua Yang, Wuhui Chen, et al.. (2021). Cooperative Data Sensing and Computation Offloading in UAV-Assisted Crowdsensing With Multi-Agent Deep Reinforcement Learning. IEEE Transactions on Network Science and Engineering. 9(5). 3197–3211. 59 indexed citations
19.
Chen, Wuhui, Xiaoyu Qiu, Ting Cai, et al.. (2021). Deep Reinforcement Learning for Internet of Things: A Comprehensive Survey. IEEE Communications Surveys & Tutorials. 23(3). 1659–1692. 206 indexed citations breakdown →
20.
Cai, Ting, et al.. (2020). A Blockchain-Assisted Trust Access Authentication System for Solid. IEEE Access. 8. 71605–71616. 12 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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