Oscar Li
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
- Artificial Intelligence top 5%
- Explainable Artificial Intelligence (XAI)
- Adversarial Robustness in Machine Learning
- Machine Learning and Data Classification
- Anomaly Detection Techniques and Applications
- Machine Learning in Healthcare
- Domain Adaptation and Few-Shot Learning
Papers in
-
- Explainable Artificial Intelligence (XAI) 3
- Adversarial Robustness in Machine Learning 2
-
- Health Literacy and Information Accessibility 1
- Co-authors
- Chaofan Chen (3 shared papers)Cynthia Rudin (3 shared papers)Hao Liu (1 shared paper)Peter Hase (1 shared paper)Alina Jade Barnett (1 shared paper)Jonathan K. Su (1 shared paper)Xiaohui Tao (1 shared paper)Jennifer Rexford (1 shared paper)
- Journals
- Urology (2 papers)Journal of Adolescent Health (1 paper)Health Services Research (1 paper)Academic Medicine (1 paper)International Journal of Transgender Health (1 paper)
- Partner nations
- United StatesCzechiaChina
In The Last Decade
Oscar Li
7 papers receiving 369 citations
Peers
Comparison fields: 5 of 77
- Health Informatics 34
- Artificial Intelligence 304
- Computer Vision and Pattern Recognition 101
- Signal Processing 34
- Biophysics 16
Countries citing papers authored by Oscar Li
This map shows the geographic impact of Oscar Li'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 Oscar Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Oscar Li more than expected).
Fields of papers citing papers by Oscar Li
This network shows the impact of papers produced by Oscar Li. 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 Oscar Li. The network helps show where Oscar Li may publish in the future.
Co-authors
The 25 scholars most cited alongside Oscar Li, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 232 | |
| 2 | This Looks Like That: Deep Learning for Interpretable Image Recognition | 2019 | 76 |
| 3 | 2019 | 55 | |
| 4 | 2014 | 12 | |
| 5 | 2021 | 4 | |
| 6 | 2023 | 3 | |
| 7 | 2023 | 1 | |
| 8 | 2021 | 0 | |
| 9 | 2025 | 0 | |
| 10 | 2024 | 0 | |
| 11 | 2024 | 0 | |
| 12 | 2023 | 0 | |
| 13 | 2023 | 0 | |
| 14 | 2025 | 0 |
About Oscar Li
Oscar Li is a scholar working on Artificial Intelligence, General Health Professions, Urology, Public Health, Environmental and Occupational Health and Psychiatry and Mental health, having authored 14 papers that have together received 383 indexed citations. Recurring topics across this work include Explainable Artificial Intelligence (XAI) (3 papers), Adversarial Robustness in Machine Learning (2 papers), Urological Disorders and Treatments (2 papers), Sexual function and dysfunction studies (2 papers), Prenatal Substance Exposure Effects (1 paper), Health Literacy and Information Accessibility (1 paper), Anatomy and Medical Technology (1 paper) and Hormonal and reproductive studies (1 paper). The work is most often cited by research in Health Informatics (34 citations), Artificial Intelligence (304 citations), Computer Vision and Pattern Recognition (101 citations), Signal Processing (34 citations) and Biophysics (16 citations). Oscar Li has collaborated with scholars based in United States, Czechia and China. Frequent co-authors include Chaofan Chen, Cynthia Rudin, Hao Liu, Peter Hase, Alina Jade Barnett, Jonathan K. Su, Xiaohui Tao, Jennifer Rexford, Laurent Vanbever and Prateek Mittal. Their work appears in journals such as Urology, Journal of Adolescent Health, Health Services Research, Academic Medicine and International Journal of Transgender Health.
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.