Kevin Lin
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- Multimodal Machine Learning Applications 15
- Human Pose and Action Recognition 12
- Biomaterials top 1%
- Cancer Research top 2%
- Breast Cancer Treatment Studies 13
- Molecular Biology top 1%
- Epigenetics and DNA Methylation 13
- CRISPR and Genetic Engineering 12
- Oncology top 2%
- PARP inhibition in cancer therapy 26
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- Topic Modeling 11
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- Ovarian cancer diagnosis and treatment 11
Kevin Lin
318 papers receiving 12.5k citations
Hit Papers
Peers
Comparison fields: 5 of 217
- Computer Vision and Pattern Recognition 1.6k
- Biomaterials 894
- Cancer Research 1.0k
- Molecular Biology 4.2k
- Oncology 1.4k
Countries citing papers authored by Kevin Lin
This map shows the geographic impact of Kevin Lin'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 Kevin Lin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kevin Lin more than expected).
Fields of papers citing papers by Kevin Lin
This network shows the impact of papers produced by Kevin Lin. 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 Kevin Lin. The network helps show where Kevin Lin may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Kevin Lin, 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 | 2025 | 1 | |
| 2 | 2025 | 1 | |
| 3 | 2025 | 0 | |
| 4 | Lost in the Middle: How Language Models Use Long Contextsbreakdown → | 2024 | 285 |
| 5 | 2024 | 11 | |
| 6 | 2024 | 6 | |
| 7 | 2023 | 5 | |
| 8 | 2023 | 1 | |
| 9 | 2022 | 1 | |
| 10 | 2020 | 39 | |
| 11 | 2020 | 22 | |
| 12 | 2018 | 7 | |
| 13 | Loss of RAD51C promoter hypermethylation confers PARP inhibitor resistance | 2018 | 1 |
| 14 | 2017 | 98 | |
| 15 | 2016 | 75 | |
| 16 | RNA-seq Reveals Complicated Transcriptomic Responses to Drought Stress in a Nonmodel Tropic Plant, Bombax ceiba L. | 2015 | 6 |
| 17 | 2014 | 82 | |
| 18 | 2013 | 91 | |
| 19 | 2012 | 128 | |
| 20 | 2003 | 2 |
About Kevin Lin
Kevin Lin is a scholar working on Cancer Research, Oncology, Computer Vision and Pattern Recognition, Molecular Biology and Statistical and Nonlinear Physics, having authored 333 papers that have together received 12.8k indexed citations. Recurring topics across this work include PARP inhibition in cancer therapy (26 papers), Multimodal Machine Learning Applications (15 papers), Breast Cancer Treatment Studies (13 papers), Epigenetics and DNA Methylation (13 papers), CRISPR and Genetic Engineering (12 papers), Human Pose and Action Recognition (12 papers), Topic Modeling (11 papers) and Ovarian cancer diagnosis and treatment (11 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.6k citations), Biomaterials (894 citations), Cancer Research (1.0k citations), Molecular Biology (4.2k citations) and Oncology (1.4k citations). Kevin Lin has collaborated with scholars based in United States, United Kingdom and China. Frequent co-authors include Jinsang Kim, Kangwon Lee, Onas Bolton, Zicheng Liu, Lijuan Wang, Hsin‐Hsi Chen, Sangeeta N. Bhatia, Changhua Yang, Hai‐Quan Mao and Kam W. Leong. Their work appears in journals such as Nature Communications, Cancer Research, Journal of Clinical Oncology, Annals of Surgical Oncology and Cell Reports.
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.