Julien Aligon

456 total citations
14 papers, 188 citations indexed

About

Julien Aligon is a scholar working on Artificial Intelligence, Information Systems and Computer Networks and Communications. According to data from OpenAlex, Julien Aligon has authored 14 papers receiving a total of 188 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Artificial Intelligence, 4 papers in Information Systems and 2 papers in Computer Networks and Communications. Recurrent topics in Julien Aligon's work include Machine Learning in Healthcare (5 papers), Explainable Artificial Intelligence (XAI) (5 papers) and Caching and Content Delivery (2 papers). Julien Aligon is often cited by papers focused on Machine Learning in Healthcare (5 papers), Explainable Artificial Intelligence (XAI) (5 papers) and Caching and Content Delivery (2 papers). Julien Aligon collaborates with scholars based in France, Italy and Armenia. Julien Aligon's co-authors include Patrick Marcel, Matteo Golfarelli, Stefano Rizzi, Enrico Gallinucci, Paul Monsarrat, Philippe Kémoun, Louis Casteilla, Jean‐Christophe Pagès, Isabelle Ader and Cyrille Delpierre and has published in prestigious journals such as Scientific Reports, Decision Support Systems and Aging Cell.

In The Last Decade

Julien Aligon

11 papers receiving 182 citations

Peers

Julien Aligon

AI

CNC

IS

SP

MSOR

Joglas Souza Canada

Simona Rabinovici‐Cohen Israel

Musleh Alsulami Saudi Arabia

Neha Sharma India

José Cambronero United States

G. Rekha India

Tong Jin China

Jinyoung Yeo South Korea

S. V. Subrahmanya India

Adam Dziedzic United States

Joglas Souza Canada

Julien Aligon

96 ×1.4

AI

16 ×0.3

CNC

53 ×1.2

IS

28 ×0.8

SP

21 ×1.0

MSOR

Citations per year, relative to Julien Aligon Julien Aligon (= 1×) peers Joglas Souza

Countries citing papers authored by Julien Aligon

Since Specialization

Citations

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

Fields of papers citing papers by Julien Aligon

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Julien Aligon

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

All Works

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14 of 14 papers shown

1.

Aligon, Julien, Nicolas Labroche, Cyrille Delpierre, et al.. (2025). Discernibility in explanations: Designing more acceptable and meaningful machine learning models for medicine. Computational and Structural Biotechnology Journal. 27. 1800–1808.

2.

Martin, Manon, et al.. (2024). Effective data exploration through clustering of local attributive explanations. Information Systems. 127. 102464–102464.

3.

Bernard, David, Isabelle Ader, Philippe Kémoun, et al.. (2023). Explainable machine learning framework to predict personalized physiological aging. Aging Cell. 22(8). e13872–e13872. 43 indexed citations

4.

Kémoun, Philippe, et al.. (2023). Explanations as a New Metric for Feature Selection: A Systematic Approach. IEEE Journal of Biomedical and Health Informatics. 27(8). 4131–4142. 6 indexed citations

5.

Monsarrat, Paul, David B. Bernard, Julien Aligon, et al.. (2022). Systemic Periodontal Risk Score Using an Innovative Machine Learning Strategy: An Observational Study. Journal of Personalized Medicine. 12(2). 217–217. 9 indexed citations

6.

Aligon, Julien, et al.. (2022). AutoXAI. Proceedings of the 31st ACM International Conference on Information & Knowledge Management. 315–324. 5 indexed citations

7.

Aligon, Julien, et al.. (2022). Local Explanation-Based Method for Healthcare Risk Stratification. Studies in health technology and informatics. 294. 555–556.

8.

Aligon, Julien, et al.. (2022). A quantitative approach for the comparison of additive local explanation methods. Information Systems. 114. 102162–102162. 25 indexed citations

9.

Buffin‐Meyer, Bénédicte, et al.. (2021). PRYNT: a tool for prioritization of disease candidates from proteomics data using a combination of shortest-path and random walk algorithms. Scientific Reports. 11(1). 5764–5764. 4 indexed citations

10.

Ravat, Franck, et al.. (2018). Data Quality Impact in Business Inteligence. 12. 47–51. 4 indexed citations

11.

Astsatryan, Hrachya, et al.. (2018). Weather Data Visualization and Analytical Platform. Scalable Computing Practice and Experience. 19(2). 79–86. 3 indexed citations

12.

Aligon, Julien, et al.. (2018). Interest-based recommendations for business intelligence users. Information Systems. 86. 79–93. 11 indexed citations

13.

Aligon, Julien, Enrico Gallinucci, Matteo Golfarelli, Patrick Marcel, & Stefano Rizzi. (2014). A collaborative filtering approach for recommending OLAP sessions. Decision Support Systems. 69. 20–30. 43 indexed citations

14.

Aligon, Julien, et al.. (2013). Similarity measures for OLAP sessions. Knowledge and Information Systems. 39(2). 463–489. 35 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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