William Luo
Impact in
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- Advanced Neural Network Applications
- Multimodal Machine Learning Applications
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- Domain Adaptation and Few-Shot Learning
- Adversarial Robustness in Machine Learning
Papers in ⓘ
- Co-authors
- Joshua B. Tenenbaum (1 shared paper)Boris Katz (1 shared paper)Christopher Wang (1 shared paper)Andrei Barbu (1 shared paper)Samuel Eisenstein (4 shared papers)Siddharth Singh (3 shared papers)Raphael Cuomo (2 shared papers)Christina L. Cui (5 shared papers)
- Journals
- Journal of the American College of Surgeons (3 papers)International Journal of Colorectal Disease (2 papers)Journal of surgical education (1 paper)HIV Medicine (1 paper)Oncotarget (1 paper)
- Partner nations
- United StatesThailandAustralia
In The Last Decade
William Luo
12 papers receiving 261 citations
Peers
Comparison fields: 5 of 65
- Computer Vision and Pattern Recognition 70
- Artificial Intelligence 87
- Oncology 60
- Infectious Diseases 27
- Obstetrics and Gynecology 11
Countries citing papers authored by William Luo
This map shows the geographic impact of William Luo'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 William Luo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites William Luo more than expected).
Fields of papers citing papers by William Luo
This network shows the impact of papers produced by William Luo. 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 William Luo. The network helps show where William Luo may publish in the future.
Co-authors
The 25 scholars most cited alongside William Luo, 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 | ObjectNet: A large-scale bias-controlled dataset for pushing the limits of object recognition models | 2019 | 116 |
| 2 | 2017 | 48 | |
| 3 | 2011 | 42 | |
| 4 | 2020 | 18 | |
| 5 | 2021 | 17 | |
| 6 | 2020 | 9 | |
| 7 | 2018 | 9 | |
| 8 | 2015 | 6 | |
| 9 | 2018 | 5 | |
| 10 | 2024 | 1 | |
| 11 | 2020 | 1 | |
| 12 | 2021 | 1 | |
| 13 | 2023 | 0 | |
| 14 | 2025 | 0 | |
| 15 | 2025 | 0 | |
| 16 | 2018 | 0 |
About William Luo
William Luo is a scholar working on Surgery, Oncology, Pulmonary and Respiratory Medicine, Pathology and Forensic Medicine and Public Health, Environmental and Occupational Health, having authored 16 papers that have together received 273 indexed citations. Recurring topics across this work include Colorectal Cancer Surgical Treatments (5 papers), Spine and Intervertebral Disc Pathology (2 papers), Stoma care and complications (2 papers), Colorectal and Anal Carcinomas (2 papers), Cancer Immunotherapy and Biomarkers (2 papers), Inflammatory Bowel Disease (2 papers), Spinal Fractures and Fixation Techniques (2 papers) and Colorectal Cancer Screening and Detection (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (70 citations), Artificial Intelligence (87 citations), Oncology (60 citations), Infectious Diseases (27 citations) and Obstetrics and Gynecology (11 citations). William Luo has collaborated with scholars based in United States, Thailand and Australia. Frequent co-authors include Joshua B. Tenenbaum, Boris Katz, Christopher Wang, Andrei Barbu, Samuel Eisenstein, Siddharth Singh, Raphael Cuomo, Christina L. Cui, Richard J. Pietras and Helena R. Chang. Their work appears in journals such as Journal of the American College of Surgeons, International Journal of Colorectal Disease, Journal of surgical education, HIV Medicine and Oncotarget.
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.