Qin Gao
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- Electrocatalysts for Energy Conversion 7
- Artificial Intelligence top 5%
- Natural Language Processing Techniques 20
- Topic Modeling 19
- Structural Biology top 10%
- Materials Chemistry top 10%
- Graphene research and applications 7
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- Advanced Memory and Neural Computing 18
- Perovskite Materials and Applications 11
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- Neuroscience and Neural Engineering 9
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- Surface and Thin Film Phenomena 6
- Co-authors
- Stephan VogelMichael WidomR. M. FeenstraRongxing HeWei ShenMing LiYimin JiangMartin P. Harmer
- Cited by
- Renewable Energy, Sustainability and the EnvironmentArtificial IntelligenceStructural Biology
- Journals
- Science (1 paper)Angewandte Chemie International Edition (1 paper)Energy & Environmental Science (1 paper)
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Qin Gao
80 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 77
- Renewable Energy, Sustainability and the Environment 230
- Artificial Intelligence 363
- Structural Biology 16
- Materials Chemistry 520
- Electrical and Electronic Engineering 558
Countries citing papers authored by Qin Gao
This map shows the geographic impact of Qin Gao'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 Qin Gao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qin Gao more than expected).
Fields of papers citing papers by Qin Gao
This network shows the impact of papers produced by Qin Gao. 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 Qin Gao. The network helps show where Qin Gao may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Qin Gao, 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 | 0 | |
| 3 | 2025 | 1 | |
| 4 | 2025 | 0 | |
| 5 | 2024 | 9 | |
| 6 | 2024 | 13 | |
| 7 | 2023 | 7 | |
| 8 | 2023 | 8 | |
| 9 | 2023 | 1 | |
| 10 | 2022 | 71 | |
| 11 | 2021 | 15 | |
| 12 | 2019 | 28 | |
| 13 | 2019 | 4 | |
| 14 | 2018 | 43 | |
| 15 | 2018 | 5 | |
| 16 | 2017 | 146 | |
| 17 | Utilizing Target-Side Semantic Role Labels to Assist Hierarchical Phrase-based Machine Translation | 2011 | 8 |
| 18 | CMU Haitian Creole-English Translation System for WMT 2011 | 2011 | 4 |
| 19 | Corpus Expansion for Statistical Machine Translation with Semantic Role Label Substitution Rules | 2011 | 13 |
| 20 | Semi-supervised Word Alignment with Mechanical Turk | 2010 | 2 |
About Qin Gao
Qin Gao is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering and Polymers and Plastics, having authored 85 papers that have together received 1.4k indexed citations. Recurring topics across this work include Natural Language Processing Techniques (20 papers), Topic Modeling (19 papers), Advanced Memory and Neural Computing (18 papers), Perovskite Materials and Applications (11 papers), Neuroscience and Neural Engineering (9 papers), Electrocatalysts for Energy Conversion (7 papers), Graphene research and applications (7 papers) and Surface and Thin Film Phenomena (6 papers). The work is most often cited by research in Renewable Energy, Sustainability and the Environment (230 citations), Artificial Intelligence (363 citations) and Structural Biology (16 citations). Qin Gao has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Stephan Vogel, Michael Widom, R. M. Feenstra, Rongxing He, Wei Shen, Ming Li, Yimin Jiang, Martin P. Harmer, Nishtha Srivastava and Wei Lu. Their work appears in journals such as Science, Angewandte Chemie International Edition and Energy & Environmental Science.
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.