Emilie Kaufmann

2.6k total citations
13 papers, 211 citations indexed

About

Emilie Kaufmann is a scholar working on Management Science and Operations Research, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Emilie Kaufmann has authored 13 papers receiving a total of 211 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Management Science and Operations Research, 4 papers in Artificial Intelligence and 3 papers in Computer Networks and Communications. Recurrent topics in Emilie Kaufmann's work include Advanced Bandit Algorithms Research (9 papers), Machine Learning and Algorithms (3 papers) and Reinforcement Learning in Robotics (3 papers). Emilie Kaufmann is often cited by papers focused on Advanced Bandit Algorithms Research (9 papers), Machine Learning and Algorithms (3 papers) and Reinforcement Learning in Robotics (3 papers). Emilie Kaufmann collaborates with scholars based in France, Switzerland and Canada. Emilie Kaufmann's co-authors include Andrée Delahaye‐Duriez, Nathaniel Korda, Rémi Munos, Aurélien Garivier, Rémi Munos, Thomas Bonald, Lilian Besson, Marc Lelarge, Christophe Moy and Thierry Carrel and has published in prestigious journals such as SHILAP Revista de lepidopterología, The Annals of Statistics and Computational and Structural Biotechnology Journal.

In The Last Decade

Emilie Kaufmann

12 papers receiving 202 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Emilie Kaufmann France 6 67 67 62 47 26 13 211
Aybar C. Acar Türkiye 8 48 0.7× 50 0.7× 154 2.5× 28 0.6× 19 0.7× 20 297
Wiesław Paja Poland 9 62 0.9× 26 0.4× 60 1.0× 37 0.8× 5 0.2× 55 354
Ali Ahmed Sudan 12 109 1.6× 107 1.6× 81 1.3× 16 0.3× 65 2.5× 28 365
Miguel García-Remesal Spain 11 128 1.9× 32 0.5× 228 3.7× 19 0.4× 17 0.7× 35 366
Siqi Chen China 9 90 1.3× 50 0.7× 42 0.7× 7 0.1× 21 0.8× 29 240
Mengqi Luo China 7 47 0.7× 30 0.4× 51 0.8× 10 0.2× 10 0.4× 20 194
C. A. Floudas United States 7 23 0.3× 80 1.2× 93 1.5× 16 0.3× 29 1.1× 7 377
Hosney Jahan China 10 48 0.7× 100 1.5× 94 1.5× 4 0.1× 27 1.0× 18 271
José Cruz-Toledo Canada 7 136 2.0× 20 0.3× 341 5.5× 26 0.6× 13 0.5× 10 412
Zhiyong Lu United States 6 169 2.5× 38 0.6× 307 5.0× 13 0.3× 9 0.3× 10 423

Countries citing papers authored by Emilie Kaufmann

Since Specialization
Citations

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

Fields of papers citing papers by Emilie Kaufmann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Emilie Kaufmann

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

All Works

13 of 13 papers shown
1.
2.
Garivier, Aurélien & Emilie Kaufmann. (2021). Nonasymptotic sequential tests for overlapping hypotheses applied to near-optimal arm identification in bandit models. Sequential Analysis. 40(1). 61–96. 6 indexed citations
3.
Kaufmann, Emilie & Abbas Mehrabian. (2019). New Algorithms for Multiplayer Bandits when Arm Means Vary Among Players. arXiv (Cornell University). 1 indexed citations
4.
Kaufmann, Emilie, et al.. (2019). On Multi-Armed Bandit Designs for Phase I Clinical Trials.. arXiv (Cornell University). 1 indexed citations
5.
Barandun, S, Emilie Kaufmann, Brigitta Gahl, et al.. (2019). Single-center experience with the combination of Cardioplexol™ cardioplegia and MiECC for isolated coronary artery bypass graft procedures. Journal of Thoracic Disease. 11(S10). S1471–S1479. 5 indexed citations
6.
Kaufmann, Emilie, et al.. (2019). Machine learning applications in drug development. Computational and Structural Biotechnology Journal. 18. 241–252. 141 indexed citations
7.
Besson, Lilian, Emilie Kaufmann, & Christophe Moy. (2018). Aggregation of multi-armed bandits learning algorithms for opportunistic spectrum access. HAL (Le Centre pour la Communication Scientifique Directe). 1–6. 5 indexed citations
8.
Kaufmann, Emilie. (2018). On Bayesian index policies for sequential resource allocation. The Annals of Statistics. 46(2). 2 indexed citations
9.
Besson, Lilian & Emilie Kaufmann. (2017). Multi-Player Bandits Models Revisited. HAL (Le Centre pour la Communication Scientifique Directe). 1 indexed citations
10.
Kaufmann, Emilie & Aurélien Garivier. (2017). Learning the distribution with largest mean: two bandit frameworks. SHILAP Revista de lepidopterología. 60. 114–131. 5 indexed citations
11.
Kaufmann, Emilie, Thomas Bonald, & Marc Lelarge. (2015). A Spectral Algorithm with Additive Clustering for the Recovery of\n Overlapping Communities in Networks. arXiv (Cornell University). 6 indexed citations
12.
Korda, Nathaniel, Emilie Kaufmann, & Rémi Munos. (2013). Thompson Sampling for 1-Dimensional Exponential Family Bandits. arXiv (Cornell University). 26. 1448–1456. 28 indexed citations
13.
Kaufmann, Emilie, Nathaniel Korda, & Rémi Munos. (2012). Thompson Sampling: An Optimal Finite Time Analysis. 10 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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