María Lomelí

1.2k total citations · 1 hit paper
12 papers, 130 citations indexed

About

María Lomelí is a scholar working on Artificial Intelligence, Statistics and Probability and Information Systems. According to data from OpenAlex, María Lomelí has authored 12 papers receiving a total of 130 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Artificial Intelligence, 4 papers in Statistics and Probability and 2 papers in Information Systems. Recurrent topics in María Lomelí's work include Bayesian Methods and Mixture Models (3 papers), Statistical Methods and Bayesian Inference (2 papers) and Software Reliability and Analysis Research (2 papers). María Lomelí is often cited by papers focused on Bayesian Methods and Mixture Models (3 papers), Statistical Methods and Bayesian Inference (2 papers) and Software Reliability and Analysis Research (2 papers). María Lomelí collaborates with scholars based in United Kingdom, Italy and France. María Lomelí's co-authors include Mark Harman, Pierre-Emmanuel Mazaré, Lucas Hosseini, Jeff Johnson, Chengqi Deng, Hervé Jeǵou, Yee Whye Teh, Stefano Favaro, Matthijs Douze and Erik Meijer and has published in prestigious journals such as Journal of Machine Learning Research, Journal of Computational and Graphical Statistics and Nature Machine Intelligence.

In The Last Decade

María Lomelí

12 papers receiving 123 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

The Faiss Library

2025 33 citations Matthijs Douze, Chengqi Deng et al. IEEE Transactions on Big Data profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
María Lomelí United Kingdom	6	42	41	28	15	13	12	130
Konstantin Schekotihin Austria	7	86 2.0×	31 0.8×	27 1.0×	26 1.7×	3 0.2×	32	147
Sachin Gupta India	7	30 0.7×	25 0.6×	64 2.3×	42 2.8×	4 0.3×	34	142
Daoguang Zan China	6	117 2.8×	66 1.6×	95 3.4×	22 1.5×	19 1.5×	11	202
Samir Loudni France	6	29 0.7×	12 0.3×	31 1.1×	40 2.7×	19 1.5×	25	93
Houari Sahraoui Canada	4	69 1.6×	44 1.1×	100 3.6×	34 2.3×	8 0.6×	6	134
Anastasia Mavridou United States	7	65 1.5×	44 1.1×	60 2.1×	23 1.5×	4 0.3×	25	136
Dragan Bojić Serbia	8	61 1.5×	45 1.1×	96 3.4×	45 3.0×	8 0.6×	28	158
Giovanni Giachetti Spain	8	49 1.2×	82 2.0×	95 3.4×	20 1.3×	5 0.4×	38	153
Srđan Krstić Switzerland	5	54 1.3×	49 1.2×	33 1.2×	41 2.7×	14 1.1×	16	129
Haoye Tian Luxembourg	8	34 0.8×	114 2.8×	138 4.9×	33 2.2×	29 2.2×	19	187

Countries citing papers authored by María Lomelí

Since Specialization

Citations

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

Fields of papers citing papers by María Lomelí

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of María Lomelí

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

All Works

Sort: Min cites: Since: Top N: Style:

12 of 12 papers shown

1.

Douze, Matthijs, Chengqi Deng, Jeff Johnson, et al.. (2025). The Faiss Library. IEEE Transactions on Big Data. 12(2). 346–361. 33 indexed citations breakdown →

2.

Weston, Jason, et al.. (2024). TOOLVERIFIER: Generalization to New Tools via Self-Verification. 5026–5041. 1 indexed citations

3.

Dessì, Roberto, et al.. (2023). Toolformer: Language Models Can Teach Themselves to Use Tools. 68539–68551. 2 indexed citations

4.

Broscheit, Samuel, Aleksandra Piktus, Patrick A. Lewis, et al.. (2023). Improving Wikipedia verifiability with AI. Nature Machine Intelligence. 5(10). 1142–1148. 12 indexed citations

5.

Harman, Mark, et al.. (2021). Testing Web Enabled Simulation at Scale Using Metamorphic Testing. 140–149. 35 indexed citations

6.

Lucas, Simon M., et al.. (2021). Measurement Challenges for Cyber Cyber Digital Twins. Queen Mary Research Online (Queen Mary University of London). 1–10. 11 indexed citations

7.

Drossopoulou, Sophia, Mark Harman, María Lomelí, et al.. (2021). Facebook’s Cyber–Cyber and Cyber–Physical Digital Twins. 1–9. 21 indexed citations

8.

Valera, Isabel, Melanie F. Pradier, María Lomelí, & Zoubin Ghahramani. (2020). General Latent Feature Models for Heterogeneous Datasets. Journal of Machine Learning Research. 21(100). 1–49. 2 indexed citations

9.

Lomelí, María, Stefano Favaro, & Yee Whye Teh. (2016). A Marginal Sampler for σ-Stable Poisson–Kingman Mixture Models. Journal of Computational and Graphical Statistics. 26(1). 44–53. 4 indexed citations

10.

Lomelí, María, Stefano Favaro, & Yee Whye Teh. (2015). A hybrid sampler for Poisson-Kingman mixture models. arXiv (Cornell University). 28. 2161–2169. 2 indexed citations

11.

Favaro, Stefano, et al.. (2014). On the stick-breaking representation of $\sigma$-stable Poisson-Kingman models. Electronic Journal of Statistics. 8(1). 5 indexed citations

12.

Favaro, Stefano, María Lomelí, & Yee Whye Teh. (2014). On a class of $$\sigma $$ σ -stable Poisson–Kingman models and an effective marginalized sampler. Statistics and Computing. 25(1). 67–78. 2 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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