Pin‐Yu Chen

13.4k total citations · 1 hit paper
230 papers, 4.0k citations indexed

About

Pin‐Yu Chen is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computer Networks and Communications. According to data from OpenAlex, Pin‐Yu Chen has authored 230 papers receiving a total of 4.0k indexed citations (citations by other indexed papers that have themselves been cited), including 130 papers in Artificial Intelligence, 36 papers in Computer Vision and Pattern Recognition and 33 papers in Computer Networks and Communications. Recurrent topics in Pin‐Yu Chen's work include Adversarial Robustness in Machine Learning (64 papers), Complex Network Analysis Techniques (27 papers) and Anomaly Detection Techniques and Applications (25 papers). Pin‐Yu Chen is often cited by papers focused on Adversarial Robustness in Machine Learning (64 papers), Complex Network Analysis Techniques (27 papers) and Anomaly Detection Techniques and Applications (25 papers). Pin‐Yu Chen collaborates with scholars based in United States, Taiwan and China. Pin‐Yu Chen's co-authors include Shin‐Ming Cheng, Kwang‐Cheng Chen, Cho‐Jui Hsieh, Alfred O. Hero, Jinfeng Yi, Huan Zhang, Sijia Liu, Sijia Liu, Chao-Han Huck Yang and Yash Sharma and has published in prestigious journals such as Nature Communications, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Pin‐Yu Chen

216 papers receiving 3.9k 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.

EAD: Elastic-Net Attacks to Deep Neural Networks via Adversarial Examples

2018 283 citations Pin‐Yu Chen et al. Proceedings of the AAAI Conference on Artificial Intelligence profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Pin‐Yu Chen United States	32	2.4k	754	546	479	453	230	4.0k
Jie Yin Australia	28	1.7k 0.7×	788 1.0×	603 1.1×	639 1.3×	713 1.6×	98	3.6k
Quanquan Gu United States	32	2.3k 1.0×	530 0.7×	900 1.6×	399 0.8×	318 0.7×	142	3.8k
Dongjin Song United States	20	1.6k 0.7×	425 0.6×	522 1.0×	388 0.8×	142 0.3×	67	2.6k
Irina Rish United States	22	1.5k 0.7×	899 1.2×	399 0.7×	175 0.4×	209 0.5×	84	3.5k
Wei Cheng United States	20	1.9k 0.8×	728 1.0×	331 0.6×	396 0.8×	105 0.2×	88	2.4k
Lifang He China	33	2.2k 0.9×	285 0.4×	1.0k 1.9×	563 1.2×	163 0.4×	175	4.2k
Ivan Zelinka Czechia	26	1.4k 0.6×	568 0.8×	284 0.5×	486 1.0×	292 0.6×	235	2.7k
Gonzalo Mateos United States	25	1.1k 0.5×	1.2k 1.5×	393 0.7×	337 0.7×	445 1.0×	97	3.0k
Vincent W. Zheng Singapore	31	2.7k 1.2×	667 0.9×	1.1k 2.0×	1.0k 2.1×	418 0.9×	79	5.1k
Marco Gori Italy	31	3.2k 1.3×	562 0.7×	1.6k 2.9×	535 1.1×	342 0.8×	185	5.5k

Countries citing papers authored by Pin‐Yu Chen

Since Specialization

Citations

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

Fields of papers citing papers by Pin‐Yu Chen

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Pin‐Yu Chen. 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 Pin‐Yu Chen. The network helps show where Pin‐Yu Chen may publish in the future.

Co-authorship network of co-authors of Pin‐Yu Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Pin‐Yu Chen. A scholar is included among the top collaborators of Pin‐Yu Chen 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 Pin‐Yu Chen. Pin‐Yu Chen 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

Pedapati, Tejaswini, et al.. (2024). Network properties determine neural network performance. Nature Communications. 15(1). 5718–5718. 7 indexed citations

Lee, Ni‐Chung, et al.. (2024). The role of genetic testing in adult patients with unexplained epilepsy. Epileptic Disorders. 26(6). 814–826.

Wan, Zishen, Nandhini Chandramoorthy, Karthik Swaminathan, et al.. (2024). MulBERRY: Enabling Bit-Error Robustness for Energy-Efficient Multi-Agent Autonomous Systems. 746–762. 7 indexed citations

Idé, Tsuyoshi, et al.. (2023). Diagnostic spatio-temporal transformer with faithful encoding. Knowledge-Based Systems. 274. 110639–110639. 1 indexed citations

Zhang, Jiajin, Hanqing Chao, Amit Dhurandhar, et al.. (2023). When Neural Networks Fail to Generalize? A Model Sensitivity Perspective. Proceedings of the AAAI Conference on Artificial Intelligence. 37(9). 11219–11227. 2 indexed citations

Yang, Chao-Han Huck, et al.. (2023). Neural Model Reprogramming with Similarity Based Mapping for Low-Resource Spoken Command Recognition. Nova Science Publishers (Nova Science Publishers, Inc.). 3 indexed citations

Hooker, Sara, et al.. (2023). Locally Differentially Private Document Generation Using Zero Shot Prompting. 8442–8457. 6 indexed citations

Xie, Chulin, Yunhui Long, Pin‐Yu Chen, et al.. (2023). Unraveling the Connections between Privacy and Certified Robustness in Federated Learning Against Poisoning Attacks. 1511–1525. 6 indexed citations

Chen, Pin‐Yu, et al.. (2023). How to Backdoor Diffusion Models?. 4015–4024. 31 indexed citations

10.

Yang, Chao-Han Huck, Jun Qi, Samuel Yen-Chi Chen, Yu Tsao, & Pin‐Yu Chen. (2022). When BERT Meets Quantum Temporal Convolution Learning for Text Classification in Heterogeneous Computing. ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 8602–8606. 44 indexed citations

11.

Li, Zichong, Pin‐Yu Chen, Sijia Liu, Songtao Lu, & Yangyang Xu. (2021). Rate-improved inexact augmented Lagrangian method for constrained nonconvex optimization. International Conference on Artificial Intelligence and Statistics. 2170–2178. 3 indexed citations

12.

Tsai, Yu‐Lin, et al.. (2021). Formalizing Generalization and Adversarial Robustness of Neural Networks to Weight Perturbations. Neural Information Processing Systems. 34. 9 indexed citations

13.

Kailkhura, Bhavya, et al.. (2021). On the Effectiveness of Poisoning against Unsupervised Domain Adaptation. International Conference on Machine Learning. 1 indexed citations

14.

Qin, Zhao, Lingfei Wu, Hui Sun, et al.. (2020). Artificial intelligence method to design and fold alpha-helical structural proteins from the primary amino acid sequence. Extreme Mechanics Letters. 36. 100652–100652. 31 indexed citations

15.

Arya, Vijay, Rachel Bellamy, Pin‐Yu Chen, et al.. (2020). AI Explainability 360: An Extensible Toolkit for Understanding Data and Machine Learning Models. Journal of Machine Learning Research. 21(130). 1–6. 37 indexed citations

16.

Xu, Kaidi, Sijia Liu, Pin‐Yu Chen, et al.. (2020). Towards an Efficient and General Framework of Robust Training for Graph Neural Networks. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 8479–8483. 4 indexed citations

17.

Liu, Weiyi, et al.. (2019). hpGAT: High-Order Proximity Informed Graph Attention Network. IEEE Access. 7. 123002–123012. 4 indexed citations

18.

Liu, Weiyi, et al.. (2019). A scalable attribute-aware network embedding system. Neurocomputing. 339. 279–291. 10 indexed citations

19.

Yang, Zhuolin, Bo Li, Pin‐Yu Chen, & Dawn Song. (2018). Characterizing audio adversarial examples using temporal dependency. arXiv (Cornell University). 11 indexed citations

20.

Cheng, Shin‐Ming, Vasileios Karyotis, Pin‐Yu Chen, Kwang‐Cheng Chen, & Symeon Papavassiliou. (2013). Diffusion Models for Information Dissemination Dynamics in Wireless Complex Communication Networks. 2013. 1–13. 15 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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