Amy X. Lu
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
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- Machine Learning in Healthcare
- Topic Modeling
Papers in
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- Machine Learning in Bioinformatics 2
- Genomics and Phylogenetic Studies 2
- Protein Structure and Dynamics 2
- Single-cell and spatial transcriptomics 1
- RNA and protein synthesis mechanisms 1
- Co-authors
- Mohamed Abdalla (1 shared paper)Matthew B. A. McDermott (1 shared paper)Marzyeh Ghassemi (2 shared papers)Haoran Zhang (1 shared paper)Seonwoo Min (1 shared paper)Christian Dallago (1 shared paper)Maria Littmann (1 shared paper)Tobias Olenyi (1 shared paper)
- Journals
- BMJ Open (1 paper)PLoS Computational Biology (1 paper)Current Protocols (1 paper)Patterns (1 paper)arXiv (Cornell University) (1 paper)
- Partner nations
- CanadaUnited StatesSouth Korea
In The Last Decade
Amy X. Lu
6 papers receiving 151 citations
Peers
Comparison fields: 5 of 51
- Health Informatics 34
- Artificial Intelligence 42
- Microbiology 8
- Molecular Biology 74
- Safety Research 8
Countries citing papers authored by Amy X. Lu
This map shows the geographic impact of Amy X. Lu'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 Amy X. Lu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Amy X. Lu more than expected).
Fields of papers citing papers by Amy X. Lu
This network shows the impact of papers produced by Amy X. Lu. 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 Amy X. Lu. The network helps show where Amy X. Lu may publish in the future.
Co-authors
The 25 scholars most cited alongside Amy X. Lu, 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 | 2020 | 70 | |
| 2 | 2021 | 59 | |
| 3 | 2022 | 17 | |
| 4 | 2018 | 4 | |
| 5 | The Cells Out of Sample (COOS) dataset and benchmarks for measuring out-of-sample generalization of image classifiers | 2019 | 1 |
| 6 | Systems and Algorithms for Convolutional Multi-Hybrid Language Models at Scale | 2025 | 1 |
| 7 | 2025 | 0 |
About Amy X. Lu
Amy X. Lu is a scholar working on Molecular Biology, Family Practice, Ecology, Health Informatics and Artificial Intelligence, having authored 7 papers that have together received 152 indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (2 papers), Genomics and Phylogenetic Studies (2 papers), Protein Structure and Dynamics (2 papers), Single-cell and spatial transcriptomics (1 paper), Cell Image Analysis Techniques (1 paper), Natural Language Processing Techniques (1 paper), Image Processing Techniques and Applications (1 paper) and RNA and protein synthesis mechanisms (1 paper). The work is most often cited by research in Health Informatics (34 citations), Artificial Intelligence (42 citations), Microbiology (8 citations), Molecular Biology (74 citations) and Safety Research (8 citations). Amy X. Lu has collaborated with scholars based in Canada, United States and South Korea. Frequent co-authors include Mohamed Abdalla, Matthew B. A. McDermott, Marzyeh Ghassemi, Haoran Zhang, Seonwoo Min, Christian Dallago, Maria Littmann, Tobias Olenyi, Konstantin Schütze and Michael Heinzinger. Their work appears in journals such as BMJ Open, PLoS Computational Biology, Current Protocols, Patterns and arXiv (Cornell University).
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.