Dongrui Fan

2.6k total citations · 1 hit paper
167 papers, 1.6k citations indexed

About

Dongrui Fan is a scholar working on Hardware and Architecture, Computer Networks and Communications and Electrical and Electronic Engineering. According to data from OpenAlex, Dongrui Fan has authored 167 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 91 papers in Hardware and Architecture, 78 papers in Computer Networks and Communications and 54 papers in Electrical and Electronic Engineering. Recurrent topics in Dongrui Fan's work include Parallel Computing and Optimization Techniques (80 papers), Interconnection Networks and Systems (39 papers) and Embedded Systems Design Techniques (33 papers). Dongrui Fan is often cited by papers focused on Parallel Computing and Optimization Techniques (80 papers), Interconnection Networks and Systems (39 papers) and Embedded Systems Design Techniques (33 papers). Dongrui Fan collaborates with scholars based in China, United States and Australia. Dongrui Fan's co-authors include Xiaochun Ye, Mingyu Yan, Lei Deng, Zhimin Zhang, Yuan Xie, Yujing Feng, Ishfaq Ahmad, Xing Hu, Ling Liang and Xiaocheng Yang and has published in prestigious journals such as Applied Physics Letters, Proceedings of the IEEE and Journal of Medicinal Chemistry.

In The Last Decade

Dongrui Fan

144 papers receiving 1.5k 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.

HyGCN: A GCN Accelerator with Hybrid Architecture

2020 216 citations Mingyu Yan, Lei Deng et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Dongrui Fan China	21	570	540	497	493	435	167	1.6k
Mark Anders United States	29	552 1.0×	364 0.7×	1.3k 2.5×	1.9k 3.9×	408 0.9×	143	3.0k
Tong Yang China	30	1.2k 2.1×	2.0k 3.7×	436 0.9×	568 1.2×	403 0.9×	224	3.6k
Behrooz Parhami United States	18	215 0.4×	833 1.5×	268 0.5×	471 1.0×	135 0.3×	125	1.3k
Lei Jiang United States	25	311 0.5×	665 1.2×	696 1.4×	899 1.8×	175 0.4×	86	1.9k
George Almási United States	25	272 0.5×	949 1.8×	800 1.6×	330 0.7×	145 0.3×	78	1.8k
Zhezhi He United States	26	857 1.5×	235 0.4×	302 0.6×	1.3k 2.5×	531 1.2×	94	2.1k
Deliang Fan United States	33	1.2k 2.0×	342 0.6×	498 1.0×	2.3k 4.7×	538 1.2×	179	3.2k
Yinhe Han China	24	392 0.7×	829 1.5×	890 1.8×	1.6k 3.2×	635 1.5×	188	2.4k
Ajay Joshi United States	25	641 1.1×	695 1.3×	654 1.3×	1.6k 3.3×	183 0.4×	124	2.4k

Countries citing papers authored by Dongrui Fan

Since Specialization

Citations

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

Fields of papers citing papers by Dongrui Fan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dongrui Fan

This figure shows the co-authorship network connecting the top 25 collaborators of Dongrui Fan. A scholar is included among the top collaborators of Dongrui Fan 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 Dongrui Fan. Dongrui Fan 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.

Li, Wenming, et al.. (2025). Accelerating tensor multiplication by exploring hybrid product with hardware and software co-design. Journal of Systems Architecture. 159. 103333–103333.

2.

Luo, Tianxiang, et al.. (2025). A RISC-V Extended Infrastructure for CNNs Through Pipelined Computing and Data Dependence Optimization. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 44(11). 4141–4154. 1 indexed citations

3.

Yang, Renchi, et al.. (2025). Leveraging Large Language Models for Effective Label-free Node Classification in Text-Attributed Graphs. 698–708.

4.

Wu, Meng, Mingyu Yan, Wenming Li, et al.. (2025). Survey on Characterizing and Understanding GNNs From a Computer Architecture Perspective. IEEE Transactions on Parallel and Distributed Systems. 36(3). 537–552. 3 indexed citations

5.

Fan, Dongrui, et al.. (2024). Progress and challenges of zinc‑iodine flow batteries: From energy storage mechanism to key components. Journal of Energy Storage. 92. 112215–112215. 13 indexed citations

6.

Wang, Zhongyu, Zhongyu Wang, Can Huang, et al.. (2024). Donor–Acceptor–Donor Strategy Rouses the Photodynamic Therapy Anticancer Activity of a Bis-terpyridyl Ru(II) Complex. Journal of Medicinal Chemistry. 67(15). 13435–13445. 5 indexed citations

7.

Chen, Siyan, et al.. (2024). JPlace: A Clock-Aware Length-Matching Placement for Rapid Single-Flux-Quantum Circuits. 1–6. 1 indexed citations

8.

Yan, Mingyu, et al.. (2024). GDR-HGNN: A Heterogeneous Graph Neural Networks Accelerator Frontend with Graph Decoupling and Recoupling. 1–6. 2 indexed citations

9.

Yan, Mingyu, Shirui Pan, Songwen Pei, et al.. (2024). DropNaE: Alleviating irregularity for large-scale graph representation learning. Neural Networks. 183. 106930–106930.

10.

Yan, Mingyu, et al.. (2023). A Comprehensive Survey on Distributed Training of Graph Neural Networks. Proceedings of the IEEE. 111(12). 1572–1606. 22 indexed citations

11.

Wang, Duo, et al.. (2023). MoDSE: A High-Accurate Multiobjective Design Space Exploration Framework for CPU Microarchitectures. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 43(5). 1525–1537. 1 indexed citations

12.

Yan, Mingyu, Duo Wang, Wenming Li, et al.. (2022). Multi-node Acceleration for Large-scale GCNs. IEEE Transactions on Computers. 1–12. 5 indexed citations

13.

Hao, Qinfen, N. D. Qi, Haiyun Xue, et al.. (2021). A Chip-Level Optical Interconnect for CPU. IEEE Photonics Technology Letters. 33(16). 852–855. 4 indexed citations

14.

Yan, Mingyu, Zhaodong Chen, Lei Deng, et al.. (2020). Characterizing and Understanding GCNs on GPU. IEEE Computer Architecture Letters. 19(1). 22–25. 43 indexed citations

15.

Ye, Xiaochun, et al.. (2020). Distributed Self-Clock: A Suitable Architecture for SFQ Circuits. IEEE Transactions on Applied Superconductivity. 30(7). 1–7. 2 indexed citations

16.

Ye, Xiaochun, et al.. (2020). Design of an 8-bit Bit-Parallel RSFQ Microprocessor. IEEE Transactions on Applied Superconductivity. 30(7). 1–6. 8 indexed citations

17.

Fan, Dongrui, et al.. (2019). Independent Research and Development of High Throughput Computer in China. Bulletin of Chinese Academy of Sciences (Chinese Version). 34(6). 648–656. 1 indexed citations

18.

Ye, Xiaochun, et al.. (2019). Bit-Slice Butterfly Processing Units for 64-Point RSFQ FFT Processors. IEEE Transactions on Applied Superconductivity. 30(1). 1–6. 8 indexed citations

19.

Gao, Yan, et al.. (2019). Utilizing the Instability in Weakly Supervised Object Detection. arXiv (Cornell University). 11–20. 1 indexed citations

20.

Cui, Huimin, Jingling Xue, Lei Wang, et al.. (2011). Extendable pattern-oriented optimization directives. 107–118. 10 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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