Nikolay Laptev
Impact in
- Signal Processing top 2%
- Time Series Analysis and Forecasting
- Artificial Intelligence top 2%
- Anomaly Detection Techniques and Applications
- Data Stream Mining Techniques
Papers in
-
- Time Series Analysis and Forecasting 4
- Data Management and Algorithms 4
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- Cloud Computing and Resource Management 8
- Data Mining Algorithms and Applications 4
- Co-authors
- Lingxue ZhuSaeed AmizadehIan FlintEaro WangRob J. HyndmanCarlo ZanioloKai ZengEstelle Sun
- Journals
- Proceedings of the VLDB Endowment (4 papers)IEEE Transactions on Services Computing (1 paper)ACM SIGMETRICS Performance Evaluation Review (1 paper)Journal of Accounting and Economics (1 paper)Proceedings of the ACM on Measurement and Analysis of Computing Systems (1 paper)
- Partner nations
- United StatesUnited KingdomCanada
In The Last Decade
Nikolay Laptev
26 papers receiving 916 citations
Hit Papers
Peers
Comparison fields: 5 of 97
- Signal Processing 312
- Artificial Intelligence 492
- Computer Networks and Communications 323
- Management Science and Operations Research 130
- Finance 69
Countries citing papers authored by Nikolay Laptev
This map shows the geographic impact of Nikolay Laptev'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 Laptev with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nikolay Laptev more than expected).
Fields of papers citing papers by Nikolay Laptev
This network shows the impact of papers produced by Nikolay Laptev. 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 Laptev. The network helps show where Nikolay Laptev may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Nikolay Laptev, 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 | 3 | |
| 2 | 2023 | 1 | |
| 3 | 2023 | 20 | |
| 4 | 2022 | 0 | |
| 5 | 2020 | 10 | |
| 6 | 2020 | 9 | |
| 7 | 2020 | 5 | |
| 8 | 2020 | 17 | |
| 9 | Applied timeseries Transfer learning | 2018 | 5 |
| 10 | 2018 | 58 | |
| 11 | 2017 | 1 | |
| 12 | 2017 | 5 | |
| 13 | 2016 | 5 | |
| 14 | 2016 | 0 | |
| 15 | 2015 | 139 | |
| 16 | 2015 | 22 | |
| 17 | 2013 | 16 | |
| 18 | 2012 | 83 | |
| 19 | 2011 | 11 | |
| 20 | 2008 | 10 |
About Nikolay Laptev
Nikolay Laptev is a scholar working on Signal Processing, Information Systems, Hardware and Architecture, Computer Networks and Communications and Information Systems and Management, having authored 28 papers that have together received 963 indexed citations. Recurring topics across this work include Cloud Computing and Resource Management (8 papers), Advanced Database Systems and Queries (5 papers), Time Series Analysis and Forecasting (4 papers), Data Mining Algorithms and Applications (4 papers), Data Management and Algorithms (4 papers), Data Stream Mining Techniques (3 papers), Financial Markets and Investment Strategies (3 papers) and Software System Performance and Reliability (3 papers). The work is most often cited by research in Signal Processing (312 citations), Artificial Intelligence (492 citations), Computer Networks and Communications (323 citations), Management Science and Operations Research (130 citations) and Finance (69 citations). Nikolay Laptev has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Lingxue Zhu, Saeed Amizadeh, Ian Flint, Earo Wang, Rob J. Hyndman, Carlo Zaniolo, Kai Zeng, Estelle Sun, Alastair Lawrence and James Ryans. Their work appears in journals such as Proceedings of the VLDB Endowment, IEEE Transactions on Services Computing, ACM SIGMETRICS Performance Evaluation Review, Journal of Accounting and Economics and Proceedings of the ACM on Measurement and Analysis of Computing Systems.
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.