Rui M. Castro

460 total citations
13 papers, 233 citations indexed

About

Rui M. Castro is a scholar working on Artificial Intelligence, Computer Networks and Communications and Computational Mechanics. According to data from OpenAlex, Rui M. Castro has authored 13 papers receiving a total of 233 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Artificial Intelligence, 5 papers in Computer Networks and Communications and 4 papers in Computational Mechanics. Recurrent topics in Rui M. Castro's work include Sparse and Compressive Sensing Techniques (4 papers), Distributed Sensor Networks and Detection Algorithms (3 papers) and Complex Network Analysis Techniques (3 papers). Rui M. Castro is often cited by papers focused on Sparse and Compressive Sensing Techniques (4 papers), Distributed Sensor Networks and Detection Algorithms (3 papers) and Complex Network Analysis Techniques (3 papers). Rui M. Castro collaborates with scholars based in Netherlands, United States and Switzerland. Rui M. Castro's co-authors include Jarvis Haupt, Robert D. Nowak, Deniz Üstebay, Michael Rabbat, Richard G. Baraniuk, Andreas Krause, Bo Chen, Ery Arias-Castro, Xiaodong Wang and Ali Tajer and has published in prestigious journals such as Journal of the American Statistical Association, IEEE Transactions on Information Theory and The Annals of Statistics.

In The Last Decade

Rui M. Castro

13 papers receiving 224 citations

Peers

Rui M. Castro

CNC

CM

AI

MSOR

BE

Max Simchowitz United States

Yolanda Tsang United States

Mario Coutiño Netherlands

Cun Mu United States

Yuyuan Ouyang United States

Laming Chen China

Yash Deshpande Germany

Douglas S. Gonçalves Brazil

Shirin Jalali United States

Yura Malitsky Sweden

Max Simchowitz United States

Rui M. Castro

37 ×0.4

CNC

148 ×1.9

CM

140 ×1.9

AI

19 ×0.6

MSOR

16 ×0.6

BE

Citations per year, relative to Rui M. Castro Rui M. Castro (= 1×) peers Max Simchowitz

Countries citing papers authored by Rui M. Castro

Since Specialization

Citations

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

Fields of papers citing papers by Rui M. Castro

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Rui M. Castro. 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 Rui M. Castro. The network helps show where Rui M. Castro may publish in the future.

Co-authorship network of co-authors of Rui M. Castro

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

All Works

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13 of 13 papers shown

1.

Castro, Rui M., et al.. (2025). Sparse anomaly detection across referentials: A rank-based higher criticism approach. The Annals of Statistics. 53(2). 1 indexed citations

2.

Castro, Rui M., et al.. (2022). Anomaly Detection for a Large Number of Streams: A Permutation-Based Higher Criticism Approach. Journal of the American Statistical Association. 119(545). 461–474. 2 indexed citations

3.

Castro, Rui M., et al.. (2021). Neural Latent Space Model for Dynamic Networks and Temporal Knowledge Graphs. Proceedings of the AAAI Conference on Artificial Intelligence. 35(5). 4054–4062. 10 indexed citations

4.

Castro, Rui M., et al.. (2019). Cliques in rank-1 random graphs: The role of inhomogeneity. Bernoulli. 26(1). 6 indexed citations

5.

Vaart, Aad van der, et al.. (2017). Consistent estimation in general sublinear preferential attachment trees. Electronic Journal of Statistics. 11(2). 5 indexed citations

6.

Arias-Castro, Ery, et al.. (2017). Distribution-Free Detection of Structured Anomalies: Permutation and Rank-Based Scans. Journal of the American Statistical Association. 113(522). 789–801. 17 indexed citations

7.

Castro, Rui M., et al.. (2015). Adaptive Sensing for Estimation of Structured Sparse Signals. IEEE Transactions on Information Theory. 61(4). 2060–2080. 11 indexed citations

8.

Coolen, Bram F., Desiree Abdurrachim, Rui M. Castro, et al.. (2012). Accelerated high‐frame‐rate mouse heart cine‐MRI using compressed sensing reconstruction. NMR in Biomedicine. 26(4). 451–457. 17 indexed citations

9.

Tajer, Ali, Rui M. Castro, & Xiaodong Wang. (2012). Adaptive Sensing of Congested Spectrum Bands. IEEE Transactions on Information Theory. 58(9). 6110–6125. 15 indexed citations

10.

Chen, Bo, Rui M. Castro, & Andreas Krause. (2012). Joint Optimization and Variable Selection of High-dimensional Gaussian Processes. TU/e Research Portal. 1379–1386. 19 indexed citations

11.

Haupt, Jarvis, Richard G. Baraniuk, Rui M. Castro, & Robert D. Nowak. (2012). Sequentially designed compressed sensing. TU/e Research Portal. 401–404. 27 indexed citations

12.

Haupt, Jarvis, Rui M. Castro, & Robert D. Nowak. (2011). Distilled Sensing: Adaptive Sampling for Sparse Detection and Estimation. IEEE Transactions on Information Theory. 57(9). 6222–6235. 79 indexed citations

13.

Üstebay, Deniz, Rui M. Castro, & Michael Rabbat. (2011). Efficient Decentralized Approximation via Selective Gossip. IEEE Journal of Selected Topics in Signal Processing. 5(4). 805–816. 24 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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