Aurélien Bibaut

540 total citations
7 papers, 285 citations indexed

About

Aurélien Bibaut is a scholar working on Statistics and Probability, Management Science and Operations Research and Computer Networks and Communications. According to data from OpenAlex, Aurélien Bibaut has authored 7 papers receiving a total of 285 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Statistics and Probability, 2 papers in Management Science and Operations Research and 1 paper in Computer Networks and Communications. Recurrent topics in Aurélien Bibaut's work include Advanced Causal Inference Techniques (4 papers), Statistical Methods and Inference (2 papers) and Statistical Methods in Clinical Trials (2 papers). Aurélien Bibaut is often cited by papers focused on Advanced Causal Inference Techniques (4 papers), Statistical Methods and Inference (2 papers) and Statistical Methods in Clinical Trials (2 papers). Aurélien Bibaut collaborates with scholars based in United States, Ivory Coast and Philippines. Aurélien Bibaut's co-authors include Cheng Ju, Mark van der Laan, Nikos Vlassis, Mark J. van der Laan, Benjamin F. Arnold, Lazarus Juziwelo, Tony Jebara, Ricardo Andrade-Pacheco, Jean Frantz Lemoine and Leda Hernandez and has published in prestigious journals such as Scientific Reports, Journal of Applied Statistics and Annual Review of Statistics and Its Application.

In The Last Decade

Aurélien Bibaut

6 papers receiving 279 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Aurélien Bibaut United States	4	107	69	59	19	15	7	285
Zhi Qiao China	11	177 1.7×	97 1.4×	64 1.1×	10 0.5×	15 1.0×	29	456
Nema Salem Saudi Arabia	8	89 0.8×	105 1.5×	58 1.0×	24 1.3×	19 1.3×	21	354
Tapabrata Chakraborti United Kingdom	10	99 0.9×	127 1.8×	107 1.8×	19 1.0×	19 1.3×	33	345
Shanxiong Chen China	11	153 1.4×	129 1.9×	83 1.4×	18 0.9×	18 1.2×	66	443
Sabyasachi Mukhopadhyay India	10	92 0.9×	85 1.2×	63 1.1×	14 0.7×	24 1.6×	45	351
Ştefan Holban Romania	8	134 1.3×	97 1.4×	59 1.0×	11 0.6×	12 0.8×	53	350
Qianqian Du China	8	124 1.2×	91 1.3×	97 1.6×	33 1.7×	21 1.4×	12	296
Dathar Abas Hasan Iraq	11	67 0.6×	57 0.8×	71 1.2×	12 0.6×	10 0.7×	23	309
Pascal Germain Canada	8	166 1.6×	72 1.0×	34 0.6×	10 0.5×	9 0.6×	19	259

Countries citing papers authored by Aurélien Bibaut

Since Specialization

Citations

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

Fields of papers citing papers by Aurélien Bibaut

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Aurélien Bibaut

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

All Works

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7 of 7 papers shown

1.

Bibaut, Aurélien & Nathan Kallus. (2025). Demystifying Inference After Adaptive Experiments. Annual Review of Statistics and Its Application. 12(1). 407–423.

2.

Bibaut, Aurélien, et al.. (2024). Forecasting the cost of drought events in France by Super Learning from a short time series of many slightly dependent data. Computational Statistics. 40(5). 2277–2321. 1 indexed citations

3.

Bibaut, Aurélien, et al.. (2024). Learning the Covariance of Treatment Effects Across Many Weak Experiments. 153–162. 1 indexed citations

4.

Andrade-Pacheco, Ricardo, Jean Frantz Lemoine, Leda Hernandez, et al.. (2020). Finding hotspots: development of an adaptive spatial sampling approach. Scientific Reports. 10(1). 10939–10939. 20 indexed citations

5.

Vlassis, Nikos, et al.. (2019). On the Design of Estimators for Bandit Off-Policy Evaluation. International Conference on Machine Learning. 6468–6476. 7 indexed citations

6.

Bibaut, Aurélien, Ivana Malenica, Nikos Vlassis, & Mark J. van der Laan. (2019). More Efficient Off-Policy Evaluation through Regularized Targeted Learning. arXiv (Cornell University). 654–663. 4 indexed citations

7.

Ju, Cheng, Aurélien Bibaut, & Mark van der Laan. (2018). The relative performance of ensemble methods with deep convolutional neural networks for image classification. Journal of Applied Statistics. 45(15). 2800–2818. 252 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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