Simon Malinowski

2.0k total citations · 3 hit papers
30 papers, 1.3k citations indexed

About

Simon Malinowski is a scholar working on Artificial Intelligence, Computer Networks and Communications and Control and Systems Engineering. According to data from OpenAlex, Simon Malinowski has authored 30 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 10 papers in Computer Networks and Communications and 6 papers in Control and Systems Engineering. Recurrent topics in Simon Malinowski's work include Algorithms and Data Compression (7 papers), Error Correcting Code Techniques (6 papers) and Cellular Automata and Applications (6 papers). Simon Malinowski is often cited by papers focused on Algorithms and Data Compression (7 papers), Error Correcting Code Techniques (6 papers) and Cellular Automata and Applications (6 papers). Simon Malinowski collaborates with scholars based in France, United Kingdom and United States. Simon Malinowski's co-authors include Brigitte Chebel‐Morello, Farhat Fnaiech, Romain Tavenard, Lotfi Saïdi, Jaouher Ben Ali, Noureddine Zerhouni, Racha Khelif, Emna Laajili, Christine Guillemot and Hervé Jeǵou and has published in prestigious journals such as PLoS ONE, Water Resources Research and IEEE Transactions on Information Theory.

In The Last Decade

Simon Malinowski

26 papers receiving 1.3k citations

Hit Papers

Accurate bearing remaining useful life prediction based o... 2014 2026 2018 2022 2014 2016 2016 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Simon Malinowski France 11 644 316 260 247 199 30 1.3k
Mei Yuan China 11 666 1.0× 261 0.8× 152 0.6× 213 0.9× 140 0.7× 40 1.1k
Jiusi Zhang China 20 1.0k 1.6× 354 1.1× 389 1.5× 270 1.1× 335 1.7× 43 1.9k
Liangwei Zhang China 13 575 0.9× 289 0.9× 290 1.1× 88 0.4× 86 0.4× 41 1.1k
Emmanuel Ramasso France 21 383 0.6× 259 0.8× 226 0.9× 144 0.6× 55 0.3× 51 1.2k
Shuai Zheng China 12 480 0.7× 195 0.6× 158 0.6× 174 0.7× 95 0.5× 25 960
Yifei Ding China 22 1.6k 2.5× 928 2.9× 748 2.9× 231 0.9× 185 0.9× 41 2.6k
Wu Deng China 22 454 0.7× 248 0.8× 348 1.3× 50 0.2× 131 0.7× 57 1.3k
Beitong Zhou China 9 482 0.7× 223 0.7× 213 0.8× 189 0.8× 291 1.5× 14 1.1k
Xiaohang Jin China 20 1.6k 2.4× 853 2.7× 218 0.8× 364 1.5× 260 1.3× 54 2.1k
Ying Zheng China 22 828 1.3× 311 1.0× 158 0.6× 164 0.7× 246 1.2× 127 1.5k

Countries citing papers authored by Simon Malinowski

Since Specialization
Citations

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

Fields of papers citing papers by Simon Malinowski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Simon Malinowski

This figure shows the co-authorship network connecting the top 25 collaborators of Simon Malinowski. A scholar is included among the top collaborators of Simon Malinowski 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 Simon Malinowski. Simon Malinowski 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
1.
Souto, Giovanna Ribeiro, et al.. (2024). Predicting COVID-19 cases in Belo Horizonte—Brazil taking into account mobility and vaccination issues. PLoS ONE. 19(2). e0269515–e0269515.
2.
Mori, Usue, et al.. (2023). Minimum Recall-Based Loss Function for Imbalanced Time Series Classification. IEEE Transactions on Knowledge and Data Engineering. 35(10). 10024–10034. 8 indexed citations
3.
Kijak, Ewa, et al.. (2023). MAAIP. Proceedings of the ACM on Computer Graphics and Interactive Techniques. 6(3). 1–20. 2 indexed citations
4.
Malinowski, Simon, et al.. (2023). A Novel Method for Temporal Graph Classification based on Transitive Reduction. SPIRE - Sciences Po Institutional REpository. 1–10.
5.
Ifrim, Georgiana, Romain Tavenard, Anthony Bagnall, et al.. (2023). Advanced Analytics and Learning on Temporal Data. Lecture notes in computer science. 1 indexed citations
6.
Lemaire, Vincent, et al.. (2021). Advanced Analytics and Learning on Temporal Data. Lecture notes in computer science. 7 indexed citations
7.
Kijak, Ewa, et al.. (2019). Combining convolutional side-outputs for road image segmentation. HAL (Le Centre pour la Communication Scientifique Directe). 1–8. 15 indexed citations
8.
Malinowski, Simon, et al.. (2016). Data Augmentation for Time Series Classification using Convolutional Neural Networks. SPIRE - Sciences Po Institutional REpository. 258 indexed citations breakdown →
9.
Malinowski, Simon, et al.. (2016). Dense Bag-of-Temporal-SIFT-Words for Time Series Classification. arXiv (Cornell University). 1 indexed citations
10.
Marnerides, Angelos K., Simon Malinowski, Ricardo Morla, & H.S. Kim. (2015). Fault diagnosis in DSL networks using support vector machines. Computer Communications. 62. 72–84. 9 indexed citations
11.
Chebel‐Morello, Brigitte, et al.. (2015). Feature selection for fault detection systems: application to the Tennessee Eastman process. Applied Intelligence. 44(1). 111–122. 19 indexed citations
12.
Malinowski, Simon, Brigitte Chebel‐Morello, & Noureddine Zerhouni. (2015). Remaining useful life estimation based on discriminating shapelet extraction. Reliability Engineering & System Safety. 142. 279–288. 32 indexed citations
13.
Ali, Jaouher Ben, Brigitte Chebel‐Morello, Lotfi Saïdi, Simon Malinowski, & Farhat Fnaiech. (2014). Accurate bearing remaining useful life prediction based on Weibull distribution and artificial neural network. Mechanical Systems and Signal Processing. 56-57. 150–172. 398 indexed citations breakdown →
14.
Khelif, Racha, et al.. (2014). Unsupervised Kernel Regression Modeling Approach for RUL Prediction. PHM Society European Conference. 2(1). 5 indexed citations
15.
Marnerides, Angelos K., Simon Malinowski, Ricardo Morla, Miguel R. D. Rodrigues, & Hyong S. Kim. (2012). Towards the improvement of diagnostic metrics Fault diagnosis for DSL-Based IPTV networks using the Rényi entropy. ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam). 2779–2784. 4 indexed citations
16.
Malinowski, Simon, et al.. (2008). Overlapped Arithmetic Codes With Memory. HAL (Le Centre pour la Communication Scientifique Directe). 1–5. 2 indexed citations
17.
Malinowski, Simon, et al.. (2007). Overlapped Quasi-Arithmetic Codes for Distributed Video Coding. 32 indexed citations
18.
Malinowski, Simon, Hervé Jeǵou, & Christine Guillemot. (2007). Deleted DOI: Error Recovery Properties and Soft Decoding of Quasi-Arithmetic Codes. EURASIP Journal on Advances in Signal Processing. 2008. 1–13. 52 indexed citations
19.
Malinowski, Simon, Hervé Jeǵou, & Christine Guillemot. (2007). Error Recovery Properties and Soft Decoding of Quasi-Arithmetic Codes. EURASIP Journal on Advances in Signal Processing. 2008(1). 4 indexed citations
20.
Malinowski, Simon, Hervé Jeǵou, & Christine Guillemot. (2006). On the link between the synchronization recovery and soft decoding of Variable Length Codes. 1–6. 1 indexed citations

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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