Aliaksei Sandryhaila

27 papers receiving 3.2k citations

Hit Papers

Discrete Signal Processing on Graphs20132026201720212013201420142015250500750

Peers

Aliaksei Sandryhaila
Comparison fields: 5 of 111
  • Artificial Intelligence 2.3k
  • Statistical and Nonlinear Physics 1.4k
  • Computer Vision and Pattern Recognition 546
  • Computer Networks and Communications 525
  • Molecular Biology 349
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Citations per year

Countries citing papers authored by Aliaksei Sandryhaila

Since Specialization
Citations

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

Fields of papers citing papers by Aliaksei Sandryhaila

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Aliaksei Sandryhaila

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1
Discrete Signal Processing on Graphs: Sampling Theorybreakdown →
419
2
Big Data Analysis with Signal Processing on Graphs
56
3
Signal Recovery on Graphs
12
4 1
5
Discrete Signal Processing on Graphs: Frequency Analysisbreakdown →
549
6 71
7
Big Data Analysis with Signal Processing on Graphs: Representation and processing of massive data sets with irregular structurebreakdown →
500
8 98
9 93
10 49
11 19
12
Discrete Signal Processing on Graphsbreakdown →
948
13 64
14 11
15 14
16 5
17
Algebraic Signal Processing: Modeling and Subband Analysis
3
18 1
19 1
20 2

About Aliaksei Sandryhaila

Aliaksei Sandryhaila is a scholar working on Computational Mathematics, Signal Processing and Statistical and Nonlinear Physics, having authored 29 papers that have together received 3.3k indexed citations. Recurring topics across this work include Advanced Graph Neural Networks (16 papers), Complex Network Analysis Techniques (12 papers) and Digital Filter Design and Implementation (9 papers). The work is most often cited by research in Statistical and Nonlinear Physics (1.4k citations), Artificial Intelligence (2.3k citations) and Computational Mathematics (41 citations). Aliaksei Sandryhaila has collaborated with scholars based in United States and Switzerland. Frequent co-authors include José M. F. Moura, Jelena Kovačević, Siheng Chen, Rohan Varma, Markus Püschel, Soummya Kar, Samir Saba, Jelena Kovačević, Zihao Wang and James C. Hoe. Their work appears in journals such as IEEE Transactions on Signal Processing, IEEE Signal Processing Magazine and SIAM Journal on Matrix Analysis and Applications.

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.

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