William Luo
Impact in
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- Advanced Neural Network Applications
- Multimodal Machine Learning Applications
- Advanced Image and Video Retrieval Techniques
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- Domain Adaptation and Few-Shot Learning
- Adversarial Robustness in Machine Learning
Papers in
- Co-authors
- Andrei Barbu (1 shared paper)Boris Katz (1 shared paper)Christopher Wang (1 shared paper)Joshua B. Tenenbaum (1 shared paper)Samuel Eisenstein (4 shared papers)Siddharth Singh (3 shared papers)Raphael Cuomo (2 shared papers)Christina L. Cui (7 shared papers)
- Journals
- Journal of the American College of Surgeons (5 papers)International Journal of Colorectal Disease (2 papers)The American Journal of Surgery (2 papers)Journal of surgical education (1 paper)Oncotarget (1 paper)
- Partner nations
- United StatesThailandChina
In The Last Decade
William Luo
14 papers receiving 267 citations
Peers
Comparison fields: 5 of 60
- Computer Vision and Pattern Recognition 71
- Artificial Intelligence 88
- Oncology 49
- Cancer Research 17
- Infectious Diseases 21
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 | 118 |
| 2 | 2017 | 49 | |
| 3 | 2011 | 42 | |
| 4 | 2021 | 18 | |
| 5 | 2020 | 18 | |
| 6 | 2018 | 9 | |
| 7 | 2020 | 9 | |
| 8 | 2015 | 6 | |
| 9 | 2018 | 5 | |
| 10 | 2024 | 1 | |
| 11 | 2021 | 1 | |
| 12 | 2020 | 1 | |
| 13 | 2023 | 1 | |
| 14 | 2021 | 1 | |
| 15 | 2025 | 0 | |
| 16 | 2025 | 0 | |
| 17 | 2025 | 0 | |
| 18 | 2025 | 0 | |
| 19 | 2020 | 0 | |
| 20 | 2018 | 0 |
About William Luo
William Luo is a scholar working on Surgery, Oncology, Pulmonary and Respiratory Medicine, Genetics and Pharmacology, having authored 20 papers that have together received 279 indexed citations. Recurring topics across this work include Colorectal Cancer Surgical Treatments (4 papers), Cancer Immunotherapy and Biomarkers (2 papers), Colorectal and Anal Carcinomas (2 papers), Spinal Fractures and Fixation Techniques (2 papers), Diverticular Disease and Complications (2 papers), Inflammatory Bowel Disease (2 papers), Sarcoma Diagnosis and Treatment (1 paper) and Cancer Genomics and Diagnostics (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (71 citations), Artificial Intelligence (88 citations), Oncology (49 citations), Cancer Research (17 citations) and Infectious Diseases (21 citations). William Luo has collaborated with scholars based in United States, Thailand and China. Frequent co-authors include Andrei Barbu, Boris Katz, Christopher Wang, Joshua B. Tenenbaum, Samuel Eisenstein, Siddharth Singh, Raphael Cuomo, Christina L. Cui, Richard J. Pietras and Jeong-Yoon Song. Their work appears in journals such as Journal of the American College of Surgeons, International Journal of Colorectal Disease, The American Journal of Surgery, Journal of surgical education 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.