Zhifeng Bao

3.9k total citations · 2 hit papers
153 papers, 2.3k citations indexed

About

Zhifeng Bao is a scholar working on Signal Processing, Computer Networks and Communications and Artificial Intelligence. According to data from OpenAlex, Zhifeng Bao has authored 153 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 84 papers in Signal Processing, 64 papers in Computer Networks and Communications and 48 papers in Artificial Intelligence. Recurrent topics in Zhifeng Bao's work include Data Management and Algorithms (81 papers), Advanced Database Systems and Queries (45 papers) and Human Mobility and Location-Based Analysis (27 papers). Zhifeng Bao is often cited by papers focused on Data Management and Algorithms (81 papers), Advanced Database Systems and Queries (45 papers) and Human Mobility and Location-Based Analysis (27 papers). Zhifeng Bao collaborates with scholars based in Australia, China and Singapore. Zhifeng Bao's co-authors include Guoliang Li, J. Shane Culpepper, Gao Cong, Sheng Wang, Farhana Choudhury, Tok Wang Ling, Baihua Zheng, A. K. Qin, Jiaheng Lu and Timos Sellis and has published in prestigious journals such as IEEE Transactions on Image Processing, Expert Systems with Applications and ACM Computing Surveys.

In The Last Decade

Zhifeng Bao

142 papers receiving 2.3k citations

Hit Papers

align trajectories

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.

A Survey on Modern Deep Neural Network for Traffic Prediction: Trends, Methods and Challenges

2020 275 citations Zhifeng Bao, Baihua Zheng et al. IEEE Transactions on Knowledge and Data Engineering profile →
A Survey on Trajectory Data Management, Analytics, and Learning

2021 164 citations Zhifeng Bao, J. Shane Culpepper et al. profile →

Peers

Zhifeng Bao

SP

AI

CNC

TRANS

BC

Wen-Chih Peng Taiwan

Guangzhong Sun China

Kai Zheng China

Baihua Zheng Singapore

Yunjun Gao China

Chi-Yin Chow Hong Kong

Shuo Shang China

Bolong Zheng China

Rui Zhou China

Pengpeng Zhao China

Wen-Chih Peng Taiwan

Zhifeng Bao

790 ×0.8

SP

668 ×0.8

AI

438 ×0.7

CNC

633 ×1.2

TRANS

232 ×0.5

BC

Citations per year, relative to Zhifeng Bao Zhifeng Bao (= 1×) peers Wen-Chih Peng

Countries citing papers authored by Zhifeng Bao

Since Specialization

Citations

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

Fields of papers citing papers by Zhifeng Bao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhifeng Bao

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Bao, Zhifeng, et al.. (2025). S-MGHSTN: Towards An Effective Streaming Traffic Accident Risk Prediction Framework. IEEE Transactions on Knowledge and Data Engineering. 1–13.

2.

Shen, Zhirong, et al.. (2025). MetoHash: A Memory-Efficient and Traffic-Optimized Hashing Index on Hybrid PMem-DRAM Memories. 805–819.

3.

Bao, Zhifeng, et al.. (2024). Towards Effective Long-Term Wind Power Forecasting: A Deep Conditional Generative Spatio-Temporal Approach. IEEE Transactions on Knowledge and Data Engineering. 36(12). 9403–9417. 5 indexed citations

4.

Chen, Lin, Xiaofeng Ding, Zhifeng Bao, Pan Zhou, & Hai Jin. (2024). Differentially Private Federated Learning on Non-iid Data: Convergence Analysis and Adaptive Optimization. IEEE Transactions on Knowledge and Data Engineering. 36(9). 4567–4581. 10 indexed citations

5.

Dong, Hai, et al.. (2024). Optimized Edge Node Allocation Considering User Delay Tolerance for Cost Reduction. IEEE Transactions on Services Computing. 17(6). 4055–4068. 2 indexed citations

6.

Bao, Zhifeng, et al.. (2024). A Fully On-Disk Updatable Learned Index. 4856–4869. 1 indexed citations

7.

Bao, Zhifeng, et al.. (2024). Cost-effective Data Labelling for Graph Neural Networks. Research Online (University of Wollongong). 353–364. 1 indexed citations

8.

Peng, Jian, et al.. (2024). Dynamic Spatial-Temporal Embedding via Neural Conditional Random Field for Multivariate Time Series Forecasting. ACM Transactions on Spatial Algorithms and Systems. 10(4). 1–23.

9.

Wang, Xinye, et al.. (2024). Robust Multi-Kernel Nearest Neighborhood for Outlier Detection. IEEE Transactions on Knowledge and Data Engineering. 36(8). 4220–4231. 5 indexed citations

10.

Bao, Zhifeng, et al.. (2023). Facility Relocation Search For Good: When Facility Exposure Meets User Convenience. 3937–3947. 1 indexed citations

11.

Bao, Zhifeng, et al.. (2023). Updatable Learned Indexes Meet Disk-Resident DBMS - From Evaluations to Design Choices. Proceedings of the ACM on Management of Data. 1(2). 1–22. 12 indexed citations

12.

Xu, Jianqiu, Hua Lu, & Zhifeng Bao. (2022). A Query Optimizer for Range Queries over Multi-Attribute Trajectories. ACM Transactions on Intelligent Systems and Technology. 14(1). 1–28. 1 indexed citations

13.

Ding, Xiaofeng, Huajian Zhou, Xiaodong Zhang, et al.. (2022). Differentially Private Triangle Counting in Large Graphs. IEEE Transactions on Knowledge and Data Engineering. 34(11). 5278–5292. 15 indexed citations

14.

Bao, Zhifeng, et al.. (2021). Let Trajectories Speak Out the Traffic Bottlenecks. ACM Transactions on Intelligent Systems and Technology. 13(1). 1–21. 1 indexed citations

15.

Bao, Zhifeng, et al.. (2020). Towards an Optimal Bus Frequency Scheduling: When the Waiting Time Matters. IEEE Transactions on Knowledge and Data Engineering. 34(9). 4484–4498. 7 indexed citations

16.

Bao, Zhifeng, et al.. (2020). Towards an Optimal Outdoor Advertising Placement. ACM Transactions on Knowledge Discovery from Data. 14(5). 1–32. 8 indexed citations

17.

Wang, Xiaoli, et al.. (2019). Effective Medical Archives Processing Using Knowledge Graphs. 1141–1144. 6 indexed citations

18.

Xie, Qing, et al.. (2019). Interactive resource recommendation with optimization by tag association and significance analysis. Neurocomputing. 391. 210–219. 5 indexed citations

19.

Hu, Huiqi, Yudian Zheng, Zhifeng Bao, et al.. (2016). Crowdsourced POI labelling: Location-aware result inference and Task Assignment. RMIT Research Repository (RMIT University Library). 61–72. 78 indexed citations

20.

Tang, Ruiming, Huayu Wu, Zhifeng Bao, Stéphane Bressan, & Patrick Valduriez. (2013). The price Is right: Models and algorithms for pricing data. eCite Digital Repository (University of Tasmania). 7 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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