Hang Su

6.2k total citations · 1 hit paper
44 papers, 1.4k citations indexed

About

Hang Su is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Electrical and Electronic Engineering. According to data from OpenAlex, Hang Su has authored 44 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Artificial Intelligence, 8 papers in Computer Vision and Pattern Recognition and 5 papers in Electrical and Electronic Engineering. Recurrent topics in Hang Su's work include Adversarial Robustness in Machine Learning (25 papers), Anomaly Detection Techniques and Applications (16 papers) and Domain Adaptation and Few-Shot Learning (7 papers). Hang Su is often cited by papers focused on Adversarial Robustness in Machine Learning (25 papers), Anomaly Detection Techniques and Applications (16 papers) and Domain Adaptation and Few-Shot Learning (7 papers). Hang Su collaborates with scholars based in China, United States and United Kingdom. Hang Su's co-authors include Jun Zhu, Yinpeng Dong, Tianyu Pang, Zhifeng Li, Wei Liu, Baoyuan Wu, Tong Zhang, Xiaolin Hu, Yulong Wang and Zihao Xiao and has published in prestigious journals such as Nano Letters, IEEE Transactions on Image Processing and Advanced Science.

In The Last Decade

Hang Su

42 papers receiving 1.3k 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.

Evading Defenses to Transferable Adversarial Examples by Translation-Invariant Attacks

2019 488 citations Yinpeng Dong, Tianyu Pang et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Hang Su China	14	1.1k	496	233	149	137	44	1.4k
Ivan Evtimov United States	4	853 0.8×	205 0.4×	263 1.1×	123 0.8×	123 0.9×	5	1.0k
Qile Zhu United States	8	1.0k 0.9×	430 0.9×	264 1.1×	164 1.1×	106 0.8×	12	1.4k
Yifan He China	15	616 0.5×	259 0.5×	54 0.2×	89 0.6×	159 1.2×	139	1.2k
Stjepan Picek Netherlands	25	1.6k 1.4×	498 1.0×	479 2.1×	238 1.6×	308 2.2×	156	1.9k
Eleanor Rieffel United States	20	1.7k 1.5×	208 0.4×	85 0.4×	30 0.2×	235 1.7×	85	2.2k
Yingqi Liu United States	16	1.3k 1.2×	348 0.7×	463 2.0×	33 0.2×	131 1.0×	30	1.6k
Olivier Déforges France	18	220 0.2×	821 1.7×	344 1.5×	46 0.3×	90 0.7×	106	1.1k
Ankur Agrawal United States	15	511 0.5×	379 0.8×	36 0.2×	172 1.2×	467 3.4×	42	1.1k
Kijung Shin South Korea	20	697 0.6×	318 0.6×	132 0.6×	89 0.6×	72 0.5×	115	1.4k
Ludwig Schmidt United States	15	552 0.5×	403 0.8×	125 0.5×	30 0.2×	77 0.6×	38	974

Countries citing papers authored by Hang Su

Since Specialization

Citations

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

Fields of papers citing papers by Hang Su

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hang Su

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

Zhou, Yi, Hang Su, Tian Wang, & Qing Hu. (2025). Onet: Twin U-Net Architecture for Unsupervised Binary Semantic Segmentation in Radar and Remote Sensing Images. IEEE Transactions on Image Processing. 34. 2161–2172. 2 indexed citations

2.

Liu, Qiaoqiao, Yangfan Xu, Hang Su, et al.. (2025). Eco-friendly antioxidant carboxymethyl cellulose /pectin films incorporating oregano essential oil and vanillic acid for tomato shelf-life extension. International Journal of Biological Macromolecules. 323(Pt 2). 147151–147151. 1 indexed citations

3.

Su, Hang, et al.. (2024). Teacher-student learning of generative adversarial network-guided diffractive neural networks for visual tracking and imaging. Advanced Photonics Nexus. 3(6).

4.

Fang, Xinyuan, Xiaonan Hu, Baoli Li, et al.. (2024). Orbital angular momentum-mediated machine learning for high-accuracy mode-feature encoding. Light Science & Applications. 13(1). 49–49. 29 indexed citations

5.

Xie, Minghao, et al.. (2024). Statistical Characteristics of Multi‐Scale Auroral Arc Width Based on Machine Learning. Journal of Geophysical Research Space Physics. 129(1). 2 indexed citations

6.

Song, Hwanjun, et al.. (2024). FineSurE: Fine-grained Summarization Evaluation using LLMs. 906–922. 8 indexed citations

7.

Su, Hang, et al.. (2024). Understanding adversarial attacks on observations in deep reinforcement learning. Science China Information Sciences. 67(5). 2 indexed citations

8.

Su, Hang, et al.. (2023). Improving the robustness of adversarial attacks using an affine-invariant gradient estimator. Computer Vision and Image Understanding. 229. 103647–103647. 1 indexed citations

9.

Xu, Congan, Long Gao, Hang Su, et al.. (2023). Label Smoothing Auxiliary Classifier Generative Adversarial Network with Triplet Loss for SAR Ship Classification. Remote Sensing. 15(16). 4058–4058. 1 indexed citations

10.

Su, Hang, et al.. (2023). Event-based diffractive neural network chip for dynamic action recognition. Optics & Laser Technology. 169. 110136–110136. 10 indexed citations

11.

Dong, Yibo, Hang Su, Long Chen, et al.. (2023). Nanoprinted Diffractive Layer Integrated Vertical-Cavity Surface-Emitting Vortex Lasers with Scalable Topological Charge. Nano Letters. 23(19). 9096–9104. 13 indexed citations

12.

Li, Baoli, Qinyu Chen, Hang Su, et al.. (2023). Ultralow-power spiking neural networks for 1024-ary orbital angular momentum shift keying free-space optical communication. Journal of Optics. 25(7). 74001–74001. 6 indexed citations

13.

Zhu, Zijian, Hang Su, Jun Zhu, et al.. (2023). To make yourself invisible with Adversarial Semantic Contours. Computer Vision and Image Understanding. 230. 103659–103659. 2 indexed citations

14.

Li, Xingyu, Hang Su, Jiachen Wang, et al.. (2022). Denoised Internal Models: A Brain-inspired Autoencoder Against Adversarial Attacks. arXiv (Cornell University). 19(5). 456–471. 2 indexed citations

15.

Su, Hang, et al.. (2022). Deep Knowledge Tracing with Learning Curves. 282–291. 2 indexed citations

16.

Shi, Jianyang, Xinyuan Fang, Wenqing Niu, et al.. (2022). 800Gbps Visible Light Communication System Employing WDM and OAM Multiplexing. 1–3. 2 indexed citations

17.

Li, Xiaodan, Yuefeng Chen, Yuan He, et al.. (2021). QAIR: Practical Query-efficient Black-Box Attacks for Image Retrieval. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 3329–3338. 30 indexed citations

18.

Pang, Tianyu, Xiao Yang, Yinpeng Dong, et al.. (2020). Boosting Adversarial Training with Hypersphere Embedding. Neural Information Processing Systems. 33. 7779–7792. 12 indexed citations

19.

Dong, Yinpeng, Qian Fu, Xiao Yang, et al.. (2020). Benchmarking Adversarial Robustness on Image Classification. 318–328. 133 indexed citations

20.

Dong, Yinpeng, et al.. (2019). Improving Black-box Adversarial Attacks with a Transfer-based Prior. arXiv (Cornell University). 32. 10932–10942. 24 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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