Andy Zou
Impact in
- Health Informatics top 10%
- Artificial Intelligence in Healthcare and Education
- Artificial Intelligence top 10%
- Topic Modeling
- Natural Language Processing Techniques
- Domain Adaptation and Few-Shot Learning
- Anomaly Detection Techniques and Applications
- Adversarial Robustness in Machine Learning
Papers in
-
- Explainable Artificial Intelligence (XAI) 2
- Natural Language Processing Techniques 1
- Topic Modeling 1
- Anomaly Detection Techniques and Applications 1
- Adversarial Robustness in Machine Learning 1
-
- Cancer-related gene regulation 1
- Signaling Pathways in Disease 1
- Co-authors
- Dawn Song (2 shared papers)Dan Hendrycks (3 shared papers)Jacob Steinhardt (2 shared papers)Mantas Mazeika (2 shared papers)Collin Burns (1 shared paper)Steven Basart (1 shared paper)Bo Li (1 shared paper)Leonard Tang (1 shared paper)
- Journals
- Journal of Clinical Oncology (1 paper)International Conference on Learning Representations (1 paper)2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (1 paper)
- Partner nations
- United StatesJamaicaUnited Kingdom
In The Last Decade
Andy Zou
3 papers receiving 242 citations
Andy Zou's Hit Papers
Peers
Comparison fields: 5 of 69
- Health Informatics 18
- Artificial Intelligence 188
- Computer Vision and Pattern Recognition 63
- Structural Biology 2
- Hepatology 10
Countries citing papers authored by Andy Zou
This map shows the geographic impact of Andy Zou'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 Andy Zou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andy Zou more than expected).
Fields of papers citing papers by Andy Zou
This network shows the impact of papers produced by Andy Zou. 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 Andy Zou. The network helps show where Andy Zou may publish in the future.
Co-authors
The 24 scholars most cited alongside Andy Zou, 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 | Measuring Massive Multitask Language Understanding Hit paper breakdown → | 2021 | 182 |
| 2 | 2022 | 48 | |
| 3 | 2024 | 27 | |
| 4 | 2024 | 0 |
About Andy Zou
Andy Zou is a scholar working on Artificial Intelligence, Molecular Biology, Oncology, Infectious Diseases and Organic Chemistry, having authored 4 papers that have together received 257 indexed citations. Recurring topics across this work include Explainable Artificial Intelligence (XAI) (2 papers), Cancer-related gene regulation (1 paper), Signaling Pathways in Disease (1 paper), CAR-T cell therapy research (1 paper), Natural Language Processing Techniques (1 paper), Topic Modeling (1 paper), Anomaly Detection Techniques and Applications (1 paper) and Adversarial Robustness in Machine Learning (1 paper). The work is most often cited by research in Health Informatics (18 citations), Artificial Intelligence (188 citations), Computer Vision and Pattern Recognition (63 citations), Structural Biology (2 citations) and Hepatology (10 citations). Andy Zou has collaborated with scholars based in United States, Jamaica and United Kingdom. Frequent co-authors include Dawn Song, Dan Hendrycks, Jacob Steinhardt, Mantas Mazeika, Collin Burns, Steven Basart, Bo Li, Leonard Tang, Jiaqi Huang and Eric Tu. Their work appears in journals such as Journal of Clinical Oncology, International Conference on Learning Representations and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
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.