Eric Wong

2.8k total citations
16 papers, 207 citations indexed

About

Eric Wong is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Health Information Management. According to data from OpenAlex, Eric Wong has authored 16 papers receiving a total of 207 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 4 papers in Computer Vision and Pattern Recognition and 3 papers in Health Information Management. Recurrent topics in Eric Wong's work include Adversarial Robustness in Machine Learning (7 papers), Electronic Health Records Systems (3 papers) and Anomaly Detection Techniques and Applications (3 papers). Eric Wong is often cited by papers focused on Adversarial Robustness in Machine Learning (7 papers), Electronic Health Records Systems (3 papers) and Anomaly Detection Techniques and Applications (3 papers). Eric Wong collaborates with scholars based in United States, Germany and India. Eric Wong's co-authors include J. Zico Kolter, Frank R. Schmidt, Jan Hendrik Metzen, Aleksander Mądry, Hadi Salman, Delip Rao, Li Zhang, Marianna Apidianaki, Shreya Havaldar and Qing Lyu and has published in prestigious journals such as SHILAP Revista de lepidopterología, Academic Medicine and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

In The Last Decade

Eric Wong

14 papers receiving 198 citations

Peers

Eric Wong

AI

CVPR

MB

SP

EEE

Paweł Morawiecki Poland

Anirudh Ravula United States

Michael Shwe United States

Jieun Eom South Korea

Daniil Ryabko France

Siyuan Cheng China

Qitian Wu China

J. Annevelink United States

Antoon Bosselaers Belgium

Ingo Thon Belgium

Paweł Morawiecki Poland

Eric Wong

117 ×0.7

AI

76 ×2.1

CVPR

9 ×0.3

MB

16 ×0.8

SP

29 ×1.6

EEE

Citations per year, relative to Eric Wong Eric Wong (= 1×) peers Paweł Morawiecki

Countries citing papers authored by Eric Wong

Since Specialization

Citations

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

Fields of papers citing papers by Eric Wong

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Eric Wong

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

All Works

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16 of 16 papers shown

1.

Robey, Alexander, et al.. (2025). Jailbreaking Black Box Large Language Models in Twenty Queries. 23–42. 15 indexed citations

2.

Wong, Eric. (2024). LEARNING PERTURBATION SETS FOR ROBUST MACHINE LEARNING. arXiv (Cornell University).

3.

Gu, Jindong, et al.. (2024). Initialization Matters for Adversarial Transfer Learning. 24831–24840. 3 indexed citations

4.

Lee, Insup, et al.. (2024). AR-Pro: Counterfactual Explanations for Anomaly Repair with Formal Properties. 16133–16159.

5.

Lyu, Qing, Shreya Havaldar, Adam Stein, et al.. (2023). Faithful Chain-of-Thought Reasoning. 305–329. 44 indexed citations

6.

Havaldar, Shreya, et al.. (2023). Comparing Styles across Languages. 6775–6791. 1 indexed citations

7.

Salman, Hadi, et al.. (2023). A Data-Based Perspective on Transfer Learning. 3613–3622. 9 indexed citations

8.

Salman, Hadi, et al.. (2022). Certified Patch Robustness via Smoothed Vision Transformers. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 15116–15126. 22 indexed citations

9.

Wong, Eric, et al.. (2022). DeepSplit: Scalable Verification of Deep Neural Networks via Operator Splitting. SHILAP Revista de lepidopterología. 1. 126–140. 4 indexed citations

10.

Wong, Eric, et al.. (2019). Adversarial Robustness Against the Union of Multiple Perturbation Models. International Conference on Machine Learning. 6640–6650. 8 indexed citations

11.

Wong, Eric, Frank R. Schmidt, & J. Zico Kolter. (2019). Wasserstein Adversarial Examples via Projected Sinkhorn Iterations. arXiv (Cornell University). 6808–6817. 21 indexed citations

12.

Wong, Eric, Frank R. Schmidt, Jan Hendrik Metzen, & J. Zico Kolter. (2018). Scaling provable adversarial defenses. Neural Information Processing Systems. 31. 8400–8409. 57 indexed citations

13.

Wong, Eric & J. Zico Kolter. (2015). An SVD and Derivative Kernel Approach to Learning from Geometric Data. Proceedings of the AAAI Conference on Artificial Intelligence. 29(1). 1 indexed citations

14.

Wong, Eric, et al.. (1996). Reaping the benefits of medical information systems. Academic Medicine. 71(4). 353–7. 7 indexed citations

15.

Wong, Eric, T. Allan Pryor, Stanley M. Huff, Peter J. Haug, & H. R. Warner. (1994). Interfacing a Stand-Alone Diagnostic Expert System with a Hospital Information System. Computers and Biomedical Research. 27(2). 116–129. 13 indexed citations

16.

Wong, Eric, et al.. (1994). Selecting a commercial clinical information system: an academic medical center's experience.. PubMed. 648–52. 2 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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