Zhijie Gu

981 total citations
10 papers, 725 citations indexed

About

Zhijie Gu is a scholar working on Molecular Biology, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Zhijie Gu has authored 10 papers receiving a total of 725 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Molecular Biology, 3 papers in Artificial Intelligence and 2 papers in Computer Vision and Pattern Recognition. Recurrent topics in Zhijie Gu's work include Genomics and Phylogenetic Studies (3 papers), Advanced Multi-Objective Optimization Algorithms (2 papers) and Metaheuristic Optimization Algorithms Research (2 papers). Zhijie Gu is often cited by papers focused on Genomics and Phylogenetic Studies (3 papers), Advanced Multi-Objective Optimization Algorithms (2 papers) and Metaheuristic Optimization Algorithms Research (2 papers). Zhijie Gu collaborates with scholars based in China, United States and Hong Kong. Zhijie Gu's co-authors include Pui–Yan Kwok, Nathan O. Stitziel, Gábor Marth, Warren Gish, Mark Yandell, Ian Korf, Hamideh Zakeri, LaDeana Hillier, Patricia Taillon‐Miller and Hongchun Lu and has published in prestigious journals such as Nature Genetics, Genome Research and IEEE Transactions on Medical Imaging.

In The Last Decade

Zhijie Gu

8 papers receiving 692 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Zhijie Gu China	5	453	268	133	51	40	10	725
Hamideh Zakeri United States	8	404 0.9×	242 0.9×	166 1.2×	51 1.0×	54 1.4×	12	771
Giulio Formenti United States	10	301 0.7×	136 0.5×	137 1.0×	57 1.1×	27 0.7×	24	446
Pawan Pandoh Canada	11	396 0.9×	137 0.5×	90 0.7×	117 2.3×	59 1.5×	23	584
Rafik Neme United States	10	532 1.2×	182 0.7×	183 1.4×	66 1.3×	28 0.7×	18	686
Francisco M. De La Vega United States	14	401 0.9×	437 1.6×	73 0.5×	35 0.7×	15 0.4×	21	828
Yaron S.N. Butterfield Canada	13	443 1.0×	102 0.4×	224 1.7×	105 2.1×	51 1.3×	17	733
I.M. Aparicio Spain	23	265 0.6×	236 0.9×	72 0.5×	22 0.4×	24 0.6×	36	1.4k
Valeria Merico Italy	20	568 1.3×	210 0.8×	134 1.0×	41 0.8×	22 0.6×	47	1.0k
Shameek Biswas United States	8	169 0.4×	282 1.1×	75 0.6×	36 0.7×	31 0.8×	11	533

Countries citing papers authored by Zhijie Gu

Since Specialization

Citations

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

Fields of papers citing papers by Zhijie Gu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhijie Gu

This figure shows the co-authorship network connecting the top 25 collaborators of Zhijie Gu. A scholar is included among the top collaborators of Zhijie Gu 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 Zhijie Gu. Zhijie Gu 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:

10 of 10 papers shown

1.

Gu, Zhijie, et al.. (2025). FoANet: Focus of Attention Prediction for Foveated Pre-rendering to Enable High-quality Edge VR. ACM Transactions on Sensor Networks.

2.

Gu, Zhijie, et al.. (2025). An effective combination of mechanisms for particle swarm optimization-based ensemble strategy. Swarm and Evolutionary Computation. 99. 102154–102154.

3.

Gu, Zhijie, et al.. (2025). An ensemble velocity learning strategy for particle swarm optimization integrating multiple local search mechanisms. Engineering Applications of Artificial Intelligence. 156. 111117–111117. 1 indexed citations

4.

Che, Haoxuan, Haibo Jin, Zhijie Gu, et al.. (2025). LLM-Driven Medical Report Generation via Communication-Efficient Heterogeneous Federated Learning. IEEE Transactions on Medical Imaging. 45(1). 28–39. 1 indexed citations

5.

Cui, Jia, et al.. (2021). PortraitNET: Photo-realistic portrait cartoon style transfer with self-supervised semantic supervision. Neurocomputing. 465. 114–127. 8 indexed citations

6.

Marth, Gábor, Ian Korf, Mark Yandell, et al.. (2000). Marth, G.T. et al. A general approach to single-nucleotide polymorphism discovery. Nat. Genet. 23, 452-456. 1 indexed citations

7.

Marth, Gábor, Ian Korf, Mark Yandell, et al.. (1999). A general approach to single-nucleotide polymorphism discovery. Nature Genetics. 23(4). 452–456. 433 indexed citations

8.

Kwok, Pui–Yan, Pui–Yan Kwok, & Zhijie Gu. (1999). Single nucleotide polymorphism libraries: why and how are we building them?. Molecular Medicine Today. 5(12). 538–543. 106 indexed citations

9.

Taillon‐Miller, Patricia, et al.. (1998). Overlapping Genomic Sequences: A Treasure Trove of Single-Nucleotide Polymorphisms. Genome Research. 8(7). 748–754. 131 indexed citations

10.

Gu, Zhijie, LaDeana Hillier, & Pui–Yan Kwok. (1998). Single nucleotide polymorphism hunting in cyberspace. Human Mutation. 12(4). 221–225. 44 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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