Nikolay Bogoychev
- Artificial Intelligence top 10%
- Natural Language Processing Techniques 15
- Topic Modeling 15
- Speech Recognition and Synthesis 4
- Algorithms and Data Compression 3
- Text Readability and Simplification 3
- Speech and dialogue systems 1
- Hate Speech and Cyberbullying Detection 1
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- Multimodal Machine Learning Applications 4
- Co-authors
- Kenneth HeafieldAlham Fikri AjiMarcin Junczys-DowmuntRico SennrichRoman GrundkiewiczYoung Jin KimHany HassanBarry Haddow
- Journals
- Baltic Journal of Modern Computing (1 paper)Edinburgh Research Explorer (University of Edinburgh) (7 papers)Edinburgh Research Explorer (7 papers)
- Partner nations
- United KingdomUnited StatesSwitzerland
In The Last Decade
Nikolay Bogoychev
19 papers receiving 127 citations
Peers
Comparison fields: 5 of 31
- Artificial Intelligence 124
- Computer Vision and Pattern Recognition 39
- Applied Psychology 5
- Hardware and Architecture 4
- Software 2
Countries citing papers authored by Nikolay Bogoychev
This map shows the geographic impact of Nikolay Bogoychev'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 Nikolay Bogoychev with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nikolay Bogoychev more than expected).
Fields of papers citing papers by Nikolay Bogoychev
This network shows the impact of papers produced by Nikolay Bogoychev. 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 Nikolay Bogoychev. The network helps show where Nikolay Bogoychev may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Nikolay Bogoychev, 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 | 2023 | 1 | |
| 2 | 2023 | 2 | |
| 3 | 2023 | 10 | |
| 4 | 2022 | 1 | |
| 5 | 2021 | 7 | |
| 6 | 2020 | 1 | |
| 7 | 2020 | 3 | |
| 8 | 2020 | 26 | |
| 9 | 2020 | 2 | |
| 10 | 2020 | 9 | |
| 11 | 2019 | 8 | |
| 12 | 2019 | 3 | |
| 13 | 2019 | 28 | |
| 14 | 2018 | 7 | |
| 15 | 2018 | 10 | |
| 16 | Modern MT: A New Open-Source Machine Translation Platform for the Translation Industry | 2016 | 5 |
| 17 | Fast, Scalable Phrase-Based SMT Decoding | 2016 | 2 |
| 18 | 2016 | 2 | |
| 19 | 2016 | 2 | |
| 20 | 2015 | 9 |
About Nikolay Bogoychev
Nikolay Bogoychev is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing, having authored 20 papers that have together received 138 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (15 papers), Topic Modeling (15 papers), Speech Recognition and Synthesis (4 papers), Multimodal Machine Learning Applications (4 papers), Algorithms and Data Compression (3 papers), Text Readability and Simplification (3 papers), Speech and dialogue systems (1 paper) and Hate Speech and Cyberbullying Detection (1 paper). The work is most often cited by research in Artificial Intelligence (124 citations), Computer Vision and Pattern Recognition (39 citations) and Applied Psychology (5 citations). Nikolay Bogoychev has collaborated with scholars based in United Kingdom, United States and Switzerland. Frequent co-authors include Kenneth Heafield, Alham Fikri Aji, Marcin Junczys-Dowmunt, Rico Sennrich, Roman Grundkiewicz, Young Jin Kim, Hany Hassan, Barry Haddow, Pinzhen Chen and Ulrich Germann. Their work appears in journals such as Baltic Journal of Modern Computing, Edinburgh Research Explorer (University of Edinburgh) and Edinburgh Research Explorer.
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.