Shi Wu

632 total citations
23 papers, 348 citations indexed

About

Shi Wu is a scholar working on Information Systems, Signal Processing and Artificial Intelligence. According to data from OpenAlex, Shi Wu has authored 23 papers receiving a total of 348 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Information Systems, 9 papers in Signal Processing and 7 papers in Artificial Intelligence. Recurrent topics in Shi Wu's work include Software Engineering Research (10 papers), Advanced Malware Detection Techniques (9 papers) and Software Testing and Debugging Techniques (5 papers). Shi Wu is often cited by papers focused on Software Engineering Research (10 papers), Advanced Malware Detection Techniques (9 papers) and Software Testing and Debugging Techniques (5 papers). Shi Wu collaborates with scholars based in China, Hong Kong and United States. Shi Wu's co-authors include Sen Nie, Qiyi Tang, Rui Cao, Junzhou Huang, Jingwen He, Lean Fu, Kai Chen, Chao Dong, Pingchuan Ma and Jiaqi Wang and has published in prestigious journals such as IEEE Transactions on Software Engineering, Sustainability and Image and Vision Computing.

In The Last Decade

Shi Wu

20 papers receiving 339 citations

Peers

Shi Wu

SOFTW

CNC

Lei Cui China

Konstantin Böttinger Germany

Taher A. Ghaleb Canada

Christian Wressnegger Germany

Ruilian Zhao China

Aala Alkhayer Jordan

Chijin Zhou China

Ahmed Fawzi Otoom Jordan

Mila Dalla Preda Italy

Lei Cui China

Shi Wu

291 ×1.5

174 ×1.0

70 ×0.6

SOFTW

110 ×1.0

270 ×3.9

CNC

Citations per year, relative to Shi Wu Shi Wu (= 1×) peers Lei Cui

Countries citing papers authored by Shi Wu

Since Specialization

Citations

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

Fields of papers citing papers by Shi Wu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shi Wu

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

All Works

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20 of 20 papers shown

Wu, Shi, et al.. (2025). A Study on the Impact of a Community Green Space Built Environment on Physical Activity in Older People from a Health Perspective: A Case Study of Qingshan District, Wuhan. Sustainability. 17(1). 263–263. 2 indexed citations

Liu, Zhijie, Qiyi Tang, Sen Nie, et al.. (2025). KEENHash: Hashing Programs into Function-Aware Embeddings for Large-Scale Binary Code Similarity Analysis. Proceedings of the ACM on software engineering.. 2(ISSTA). 801–824.

Wang, Shuai, et al.. (2025). Preserving Privacy in Software Composition Analysis: A Study of Technical Solutions and Enhancements. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 2329–2341. 1 indexed citations

Wu, Daoyuan, Zongjie Li, Shuai Wang, et al.. (2025). DecLLM: LLM-Augmented Recompilable Decompilation for Enabling Programmatic Use of Decompiled Code. Proceedings of the ACM on software engineering.. 2(ISSTA). 1841–1864.

Liu, Zhibo, Shuai Wang, Ying Wang, et al.. (2024). Are We There Yet? Filling the Gap Between Binary Similarity Analysis and Binary Software Composition Analysis. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 506–523. 2 indexed citations

Jing, Pengfei, Zhiqiang Cai, Le Yu, et al.. (2024). Revisiting Automotive Attack Surfaces: a Practitioners’ Perspective. 2348–2365. 6 indexed citations

Jiang, Ling, et al.. (2024). BinaryAI: Binary Software Composition Analysis via Intelligent Binary Source Code Matching. 1–13. 10 indexed citations

Jiang, Ling, et al.. (2023). Third-Party Library Dependency for Large-Scale SCA in the C/C++ Ecosystem: How Far Are We?. 1383–1395. 12 indexed citations

Song, Qi, et al.. (2023). Degradation Conditioned GAN for Degradation Generalization of Face Restoration Models. 34. 520–524.

10.

Ma, Pingchuan, et al.. (2022). sem2vec : Semantics-aware Assembly Tracelet Embedding. ACM Transactions on Software Engineering and Methodology. 32(4). 1–34. 11 indexed citations

11.

Ma, Pingchuan, Shuai Wang, Mingyue Jiang, et al.. (2022). Deceiving Deep Neural Networks-Based Binary Code Matching with Adversarial Programs. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 117–128. 1 indexed citations

12.

Jiang, Ling, Yuqun Zhang, Guowei Yang, et al.. (2022). Evaluating and improving neural program-smoothing-based fuzzing. 847–858. 15 indexed citations

13.

He, Jingwen, Shi Wu, Kai Chen, Lean Fu, & Chao Dong. (2022). GCFSR: a Generative and Controllable Face Super Resolution Method Without Facial and GAN Priors. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 1879–1888. 48 indexed citations

14.

Li, Zongjie, Pingchuan Ma, Shuai Wang, et al.. (2022). Unleashing the power of compiler intermediate representation to enhance neural program embeddings. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 2253–2265. 16 indexed citations

15.

Fan, Ming, Wuxia Jin, Qiyi Tang, et al.. (2022). 1-to-1 or 1-to-n? Investigating the Effect of Function Inlining on Binary Similarity Analysis. ACM Transactions on Software Engineering and Methodology. 32(4). 1–26. 12 indexed citations

16.

Jing, Pengfei, Qiyi Tang, Yuefeng Du, et al.. (2021). Too good to be safe: Tricking lane detection in autonomous driving with crafted perturbations. USENIX Security Symposium. 3237–3254. 8 indexed citations

17.

Wu, Shi, et al.. (2021). Multi-view self-supervised learning for 3D facial texture reconstruction from single image. Image and Vision Computing. 115. 104311–104311. 6 indexed citations

18.

Zheng, Wenxin, et al.. (2020). CodeCMR: Cross-Modal Retrieval For Function-Level Binary Source Code Matching. Neural Information Processing Systems. 33. 3872–3883. 38 indexed citations

19.

Jiang, Jile, et al.. (2020). Performance test of cantilever transfer standard used for afm tip calibration based on electromagnetic compensation. ACTA IMEKO. 9(5). 129–129. 1 indexed citations

20.

Qin, Feng, Toshiya Ideue, Shi Wu, et al.. (2018). Electric-field Control of Electronic States in WS<sub>2</sub> Nanodevices by Electrolyte Gating. Journal of Visualized Experiments. 1 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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