Andrey Malinin
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition
- Signal Processing
- Experimental and Cognitive Psychology
- Radiology, Nuclear Medicine and Imaging
- Co-authors
- Mark GalesKate KnillYu WangAnton RagniKonstantinos G. KyriakopoulosK.M. KnillMuhammad RashidXixin Wu
- Topics
- Topic Modeling (9 papers)Speech Recognition and Synthesis (8 papers)Natural Language Processing Techniques (8 papers)
- Journals
- Computers in Biology and MedicineSpeech CommunicationApollo (University of Cambridge)
- Partner nations
- United KingdomRussiaSwitzerland
In The Last Decade
Andrey Malinin
16 papers receiving 182 citations
Peers
Comparison fields: 5 of 35
- Artificial Intelligence 180
- Computer Vision and Pattern Recognition 44
- Signal Processing 23
- Experimental and Cognitive Psychology 11
- Radiology, Nuclear Medicine and Imaging 10
Countries citing papers authored by Andrey Malinin
This map shows the geographic impact of Andrey Malinin'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 Andrey Malinin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrey Malinin more than expected).
Fields of papers citing papers by Andrey Malinin
This network shows the impact of papers produced by Andrey Malinin. 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 Andrey Malinin. The network helps show where Andrey Malinin may publish in the future.
Co-authorship network of co-authors of Andrey Malinin
This figure shows the co-authorship network connecting the top 25 collaborators of Andrey Malinin. A scholar is included among the top collaborators of Andrey Malinin based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Andrey Malinin. Andrey Malinin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 4 | |
| 3 | 4 | |
| 4 | 5 | |
| 5 | Uncertainty in Gradient Boosting via Ensembles | 2 |
| 6 | 3 | |
| 7 | 1 | |
| 8 | 8 | |
| 9 | 17 | |
| 10 | 9 | |
| 11 | 30 | |
| 12 | 16 | |
| 13 | 1 | |
| 14 | 56 | |
| 15 | 17 | |
| 16 | 3 | |
| 17 | 10 | |
| 18 | 11 |
About Andrey Malinin
Andrey Malinin is a scholar working on Artificial Intelligence, Neurology and Pathology and Forensic Medicine, having authored 18 papers that have together received 197 indexed citations. Recurring topics across this work include Topic Modeling (9 papers), Speech Recognition and Synthesis (8 papers) and Natural Language Processing Techniques (8 papers). The work is most often cited by research in Artificial Intelligence (180 citations), Health Informatics (4 citations) and Computer Vision and Pattern Recognition (44 citations). Andrey Malinin has collaborated with scholars based in United Kingdom, Russia and Switzerland. Frequent co-authors include Mark Gales, Kate Knill, Yu Wang, Anton Ragni, Konstantinos G. Kyriakopoulos, K.M. Knill, Muhammad Rashid, Xixin Wu, Andrew Caines and Meritxell Bach Cuadra. Their work appears in journals such as Computers in Biology and Medicine, Speech Communication and Apollo (University of Cambridge).
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.