Alexey Svyatkovskiy

544 total citations · 1 hit paper
8 papers, 279 citations indexed

About

Alexey Svyatkovskiy is a scholar working on Artificial Intelligence, Information Systems and Nuclear and High Energy Physics. According to data from OpenAlex, Alexey Svyatkovskiy has authored 8 papers receiving a total of 279 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Artificial Intelligence, 2 papers in Information Systems and 2 papers in Nuclear and High Energy Physics. Recurrent topics in Alexey Svyatkovskiy's work include Topic Modeling (3 papers), Magnetic confinement fusion research (2 papers) and Software Engineering Research (2 papers). Alexey Svyatkovskiy is often cited by papers focused on Topic Modeling (3 papers), Magnetic confinement fusion research (2 papers) and Software Engineering Research (2 papers). Alexey Svyatkovskiy collaborates with scholars based in United States, United Kingdom and South Africa. Alexey Svyatkovskiy's co-authors include W. M. Tang, Julian Kates‐Harbeck, Kosuke Imai, Ge Dong, Neel Sundaresan, Colin B. Clement, Michele Tufano, Chenxiao Liu, Shuai Lu and Daxin Jiang and has published in prestigious journals such as Nature, Contributions to Plasma Physics and arXiv (Cornell University).

In The Last Decade

Alexey Svyatkovskiy

7 papers receiving 264 citations

Hit Papers

Predicting disruptive instabilities in controlled fusion ... 2019 2026 2021 2023 2019 50 100 150 200
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Predicting disruptive instabilities in controlled fusion plasmas through deep learning
    2019 242 citations Julian Kates‐Harbeck, Alexey Svyatkovskiy et al. Nature profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Alexey Svyatkovskiy United States 5 136 68 51 49 35 8 279
Julian Kates‐Harbeck United States 5 138 1.0× 57 0.8× 51 1.0× 49 1.0× 26 0.7× 10 303
M. Lungaroni Italy 12 145 1.1× 120 1.8× 74 1.5× 41 0.8× 41 1.2× 42 371
G. Pautasso Germany 10 201 1.5× 63 0.9× 74 1.5× 60 1.2× 39 1.1× 17 256
Malachi Schram United States 9 162 1.2× 53 0.8× 73 1.4× 34 0.7× 48 1.4× 42 390
Kelli Humbird United States 7 196 1.4× 59 0.9× 55 1.1× 56 1.1× 11 0.3× 24 375
Kevin Montes United States 9 272 2.0× 92 1.4× 119 2.3× 91 1.9× 57 1.6× 11 378
J.P. Qian China 10 251 1.8× 43 0.6× 95 1.9× 71 1.4× 15 0.4× 22 320
A. Pau Switzerland 14 332 2.4× 109 1.6× 133 2.6× 101 2.1× 62 1.8× 40 454
Christine Hennig Germany 10 153 1.1× 15 0.2× 86 1.7× 41 0.8× 71 2.0× 34 235
Dalong Chen China 13 327 2.4× 99 1.5× 127 2.5× 107 2.2× 48 1.4× 62 493

Countries citing papers authored by Alexey Svyatkovskiy

Since Specialization
Citations

This map shows the geographic impact of Alexey Svyatkovskiy'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 Alexey Svyatkovskiy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alexey Svyatkovskiy more than expected).

Fields of papers citing papers by Alexey Svyatkovskiy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Alexey Svyatkovskiy. 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 Alexey Svyatkovskiy. The network helps show where Alexey Svyatkovskiy may publish in the future.

Co-authorship network of co-authors of Alexey Svyatkovskiy

This figure shows the co-authorship network connecting the top 25 collaborators of Alexey Svyatkovskiy. A scholar is included among the top collaborators of Alexey Svyatkovskiy 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 Alexey Svyatkovskiy. Alexey Svyatkovskiy is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

8 of 8 papers shown
1.
Liu, Chenxiao, Shuai Lu, Weizhu Chen, et al.. (2023). Code Execution with Pre-trained Language Models. 4984–4999. 9 indexed citations
2.
Tang, W. M., Ge Dong, J.L. Barr, et al.. (2023). Implementation of AI/DEEP learning disruption predictor into a plasma control system. Contributions to Plasma Physics. 63(5-6). 2 indexed citations
3.
Drain, Dawn, et al.. (2022). Exploring and evaluating personalized models for code generation. arXiv (Cornell University). 1500–1508. 6 indexed citations
4.
Dong, Ge, et al.. (2021). FULLY CONVOLUTIONAL SPATIO-TEMPORAL MODELS FOR REPRESENTATION LEARNING IN PLASMA SCIENCE. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 2(1). 49–64. 10 indexed citations
5.
Kates‐Harbeck, Julian, Alexey Svyatkovskiy, & W. M. Tang. (2019). Predicting disruptive instabilities in controlled fusion plasmas through deep learning. Nature. 568(7753). 526–531. 242 indexed citations breakdown →
6.
Pivarski, J. & Alexey Svyatkovskiy. (2016). histogrammar-scala: 1.0.0. INFM-OAR (INFN Catania). 1 indexed citations
7.
Svyatkovskiy, Alexey, et al.. (2016). Large-scale text processing pipeline with Apache Spark. 3928–3935. 9 indexed citations
8.
Pivarski, J., et al.. (2016). histogrammar-python: 1.0.0. Zenodo (CERN European Organization for Nuclear Research).

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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Julian Kates‐Harbeck Breakdown of academic impact, for papers by M. Lungaroni Breakdown of academic impact, for papers by G. Pautasso Breakdown of academic impact, for papers by Malachi Schram Breakdown of academic impact, for papers by Kelli Humbird Breakdown of academic impact, for papers by Kevin Montes Breakdown of academic impact, for papers by J.P. Qian Breakdown of academic impact, for papers by A. Pau Breakdown of academic impact, for papers by Christine Hennig Breakdown of academic impact, for papers by Dalong Chen
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