John Giorgi
Impact in
- Artificial Intelligence top 5%
- Topic Modeling
- Natural Language Processing Techniques
- Domain Adaptation and Few-Shot Learning
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- Mycorrhizal Fungi and Plant Interactions
- Legume Nitrogen Fixing Symbiosis
Papers in
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- Topic Modeling 4
- Natural Language Processing Techniques 3
- Speech and dialogue systems 1
- AI in Service Interactions 1
- Advanced Text Analysis Techniques 1
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- Biomedical Text Mining and Ontologies 2
- Co-authors
- Gary Bader (6 shared papers)Bo Wang (2 shared papers)Manuela Krüger (1 shared paper)Gökalp Yildirir (1 shared paper)Steve Ndikumana (1 shared paper)Matthieu Hainaut (1 shared paper)Jeanne Ropars (1 shared paper)Emmanuelle Morin (1 shared paper)
- Journals
- Bioinformatics (2 papers)New Phytologist (1 paper)The Journal of Open Source Software (1 paper)
- Partner nations
- CanadaUnited StatesGermany
In The Last Decade
John Giorgi
8 papers receiving 684 citations
John Giorgi's Hit Papers
Peers
Comparison fields: 5 of 83
- Artificial Intelligence 429
- Plant Science 161
- Health Informatics 6
- Computer Vision and Pattern Recognition 77
- Pharmacology 53
Countries citing papers authored by John Giorgi
This map shows the geographic impact of John Giorgi'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 John Giorgi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John Giorgi more than expected).
Fields of papers citing papers by John Giorgi
This network shows the impact of papers produced by John Giorgi. 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 John Giorgi. The network helps show where John Giorgi may publish in the future.
Co-authors
The 25 scholars most cited alongside John Giorgi, 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 | DeCLUTR: Deep Contrastive Learning for Unsupervised Textual Representations Hit paper breakdown → | 2021 | 270 |
| 2 | 2018 | 170 | |
| 3 | 2018 | 137 | |
| 4 | 2019 | 63 | |
| 5 | 2022 | 36 | |
| 6 | 2023 | 21 | |
| 7 | 2023 | 3 | |
| 8 | 2021 | 1 |
About John Giorgi
John Giorgi is a scholar working on Artificial Intelligence, Molecular Biology, Computational Theory and Mathematics, Plant Science and Insect Science, having authored 8 papers that have together received 701 indexed citations. Recurring topics across this work include Topic Modeling (4 papers), Natural Language Processing Techniques (3 papers), Biomedical Text Mining and Ontologies (2 papers), Speech and dialogue systems (1 paper), Computational Drug Discovery Methods (1 paper), AI in Service Interactions (1 paper), Mycorrhizal Fungi and Plant Interactions (1 paper) and Advanced Text Analysis Techniques (1 paper). The work is most often cited by research in Artificial Intelligence (429 citations), Plant Science (161 citations), Health Informatics (6 citations), Computer Vision and Pattern Recognition (77 citations) and Pharmacology (53 citations). John Giorgi has collaborated with scholars based in Canada, United States and Germany. Frequent co-authors include Gary Bader, Bo Wang, Bo Wang, Manuela Krüger, Gökalp Yildirir, Steve Ndikumana, Matthieu Hainaut, Jeanne Ropars, Emmanuelle Morin and Timea Marton. Their work appears in journals such as Bioinformatics, New Phytologist and The Journal of Open Source Software.
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.