Bin Guo

11.9k total citations · 2 hit papers
437 papers, 7.5k citations indexed

About

Bin Guo is a scholar working on Transportation, Computer Science Applications and Artificial Intelligence. According to data from OpenAlex, Bin Guo has authored 437 papers receiving a total of 7.5k indexed citations (citations by other indexed papers that have themselves been cited), including 124 papers in Transportation, 113 papers in Computer Science Applications and 107 papers in Artificial Intelligence. Recurrent topics in Bin Guo's work include Human Mobility and Location-Based Analysis (118 papers), Mobile Crowdsensing and Crowdsourcing (112 papers) and Indoor and Outdoor Localization Technologies (54 papers). Bin Guo is often cited by papers focused on Human Mobility and Location-Based Analysis (118 papers), Mobile Crowdsensing and Crowdsourcing (112 papers) and Indoor and Outdoor Localization Technologies (54 papers). Bin Guo collaborates with scholars based in China, United States and France. Bin Guo's co-authors include Zhiwen Yu, Zhu Wang, Xingshe Zhou, Daqing Zhang, Qi Han, Daqing Zhang, Yunji Liang, Leye Wang, Shasha Zhou and Huihui Chen and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Communications of the ACM.

In The Last Decade

Bin Guo

387 papers receiving 7.3k citations

Hit Papers

Mobile Crowd Sensing and Computing 2013 2026 2017 2021 2015 2013 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Bin Guo China 41 2.4k 2.2k 1.8k 1.6k 1.5k 437 7.5k
Zhiwen Yu China 44 2.3k 0.9× 2.1k 1.0× 2.3k 1.3× 1.9k 1.2× 2.2k 1.5× 520 9.2k
Cyrus Shahabi United States 50 2.2k 0.9× 2.1k 1.0× 3.3k 1.8× 1.0k 0.7× 2.5k 1.7× 360 10.1k
Yongxin Tong China 36 2.0k 0.8× 962 0.4× 4.2k 2.3× 838 0.5× 1.4k 0.9× 121 7.0k
Jian Tang United States 47 2.0k 0.8× 791 0.4× 2.3k 1.3× 3.0k 1.9× 4.3k 2.9× 336 9.4k
Zhibo Wang China 42 1.3k 0.5× 708 0.3× 2.7k 1.5× 1.8k 1.1× 1.7k 1.2× 274 6.7k
Burak Kantarcı Canada 39 1.2k 0.5× 707 0.3× 1.8k 1.0× 1.8k 1.2× 2.8k 1.8× 295 6.1k
Salil S. Kanhere Australia 52 1.7k 0.7× 894 0.4× 2.5k 1.4× 3.0k 1.9× 5.2k 3.5× 318 10.8k
Kai Zheng China 46 661 0.3× 1.8k 0.8× 2.2k 1.2× 521 0.3× 1.8k 1.2× 357 7.0k
Luca Foschini Italy 33 1.0k 0.4× 816 0.4× 722 0.4× 1.1k 0.7× 2.6k 1.8× 281 4.9k
Chunyan Miao Singapore 57 1.3k 0.5× 603 0.3× 7.0k 3.9× 2.0k 1.3× 3.1k 2.1× 482 14.3k

Countries citing papers authored by Bin Guo

Since Specialization
Citations

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

Fields of papers citing papers by Bin Guo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bin Guo

This figure shows the co-authorship network connecting the top 25 collaborators of Bin Guo. A scholar is included among the top collaborators of Bin Guo 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 Bin Guo. Bin Guo 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.
Gao, Wen, Zhiwen Yu, Liang Wang, et al.. (2025). GNN-based deep reinforcement learning for computation task scheduling in autonomous multi-robot systems. Journal of Systems Architecture. 168. 103534–103534.
2.
Zhao, Kai, et al.. (2024). Limits of predictability in top-N recommendation. Information Processing & Management. 61(4). 103731–103731. 7 indexed citations
3.
Guo, Bin, Hao Wang, Haoyu Li, et al.. (2024). The future of cognitive strategy-enhanced persuasive dialogue agents: new perspectives and trends. Frontiers of Computer Science. 19(5). 1 indexed citations
4.
Guo, Bin, et al.. (2024). EvolveDetector: Towards an evolving fake news detector for emerging events with continual knowledge accumulation and transfer. Information Processing & Management. 62(1). 103878–103878. 4 indexed citations
5.
Wang, Liang, Yaru Wang, Zhiwen Yu, et al.. (2024). Similarity Caching in Dynamic Cooperative Edge Networks: An Adversarial Bandit Approach. IEEE Transactions on Mobile Computing. 24(4). 2769–2782. 1 indexed citations
6.
Guo, Bin, et al.. (2024). Pioneering Cooperative Air-Ground Instant Delivery Using UAVs and Crowdsourced Couriers. Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies. 8(4). 1–26. 1 indexed citations
7.
Wang, Zhu, Zhuo Sun, Chao Chen, et al.. (2024). FinerSense: A Fine-Grained Respiration Sensing System Based on Precise Separation of Wi-Fi Signals. IEEE Transactions on Mobile Computing. 24(5). 3703–3718. 1 indexed citations
8.
Liu, Yan, et al.. (2024). CrowdTransfer: Enabling Crowd Knowledge Transfer in AIoT Community. IEEE Communications Surveys & Tutorials. 27(2). 1191–1237. 1 indexed citations
9.
Liu, Sicong, et al.. (2024). CrowdLearning: A Decentralized Distributed Training Framework Based on Collectives of Trusted AIoT Devices. IEEE Transactions on Mobile Computing. 23(12). 13420–13437. 2 indexed citations
12.
Yu, Zhiwen, Yao Zhang, Yanfei Wang, et al.. (2024). hmOS: An Extensible Platform for Task-Oriented Human–Machine Computing. IEEE Transactions on Human-Machine Systems. 54(5). 536–545. 1 indexed citations
13.
Wang, Zhu, et al.. (2024). Size Matters: Characterizing the Effect of Target Size on Wi-Fi Sensing Based on the Fresnel Zone Model. Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies. 8(4). 1–22.
14.
Guo, Bin, et al.. (2023). CoupledGT: Coupled Geospatial-temporal Data Modeling for Air Quality Prediction. ACM Transactions on Knowledge Discovery from Data. 17(9). 1–21. 5 indexed citations
15.
Lv, Xiaolei, et al.. (2022). Building Change Detection Based on 3D Co-Segmentation Using Satellite Stereo Imagery. Remote Sensing. 14(3). 628–628. 8 indexed citations
16.
Liu, Sicong, et al.. (2022). AdaEnlight. Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies. 6(4). 1–26. 5 indexed citations
17.
Guo, Bin, Yan Liu, Liang Wang, et al.. (2019). CrowDNet: Enabling a Crowdsourced Object Delivery Network Based on Modern Portfolio Theory. IEEE Internet of Things Journal. 6(5). 9030–9041. 15 indexed citations
18.
Chen, Huihui, Bin Guo, Zhiwen Yu, & Qi Han. (2019). CrowdTracking: Real-Time Vehicle Tracking Through Mobile Crowdsensing. IEEE Internet of Things Journal. 6(5). 7570–7583. 44 indexed citations
19.
Ouyang, Yi, et al.. (2018). CompetitiveBike: Competitive Analysis and Popularity Prediction of Bike-Sharing Apps Using Multi-Source Data. IEEE Transactions on Mobile Computing. 18(8). 1760–1773. 20 indexed citations
20.
Wang, Liang, Zhiwen Yu, Daqing Zhang, Bin Guo, & Chi Harold Liu. (2018). Heterogeneous Multi-Task Assignment in Mobile Crowdsensing Using Spatiotemporal Correlation. IEEE Transactions on Mobile Computing. 18(1). 84–97. 115 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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