Pedro Casas

3.4k total citations
148 papers, 2.2k citations indexed

About

Pedro Casas is a scholar working on Computer Networks and Communications, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Pedro Casas has authored 148 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 120 papers in Computer Networks and Communications, 72 papers in Artificial Intelligence and 47 papers in Computer Vision and Pattern Recognition. Recurrent topics in Pedro Casas's work include Network Security and Intrusion Detection (57 papers), Internet Traffic Analysis and Secure E-voting (51 papers) and Image and Video Quality Assessment (46 papers). Pedro Casas is often cited by papers focused on Network Security and Intrusion Detection (57 papers), Internet Traffic Analysis and Secure E-voting (51 papers) and Image and Video Quality Assessment (46 papers). Pedro Casas collaborates with scholars based in Austria, Germany and Uruguay. Pedro Casas's co-authors include Raimund Schatz, Michael Seufert, Alessandro D’Alconzo, Pierdomenico Fiadino, Philippe Owezarski, Johan Mazel, Florian Wamser, Marco Mellia, Phuoc Tran‐Gia and Tobias Hoßfeld and has published in prestigious journals such as IEEE Access, IEEE Communications Magazine and TrAC Trends in Analytical Chemistry.

In The Last Decade

Pedro Casas

144 papers receiving 2.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Pedro Casas Austria 25 1.5k 927 857 417 303 148 2.2k
Jeffrey Erman United States 21 2.0k 1.3× 1.3k 1.4× 430 0.5× 477 1.1× 595 2.0× 29 2.5k
Rocky K. C. Chang Hong Kong 21 1.6k 1.0× 857 0.9× 814 0.9× 610 1.5× 348 1.1× 115 2.2k
Tim Wauters Belgium 27 1.5k 1.0× 321 0.3× 858 1.0× 592 1.4× 364 1.2× 156 2.3k
Lusheng Ji United States 23 2.4k 1.5× 302 0.3× 583 0.7× 289 0.7× 1.2k 4.0× 40 3.0k
Alessandro D’Alconzo Austria 18 706 0.5× 393 0.4× 261 0.3× 175 0.4× 230 0.8× 47 1.0k
Jeffrey Pang United States 26 1.8k 1.2× 394 0.4× 433 0.5× 155 0.4× 1.0k 3.4× 39 2.4k
Grenville Armitage Australia 29 4.1k 2.7× 3.0k 3.2× 763 0.9× 1.1k 2.7× 678 2.2× 159 5.0k
Pere Barlet‐Ros Spain 21 902 0.6× 647 0.7× 182 0.2× 173 0.4× 241 0.8× 83 1.3k
Sanjay Rao United States 26 4.2k 2.7× 299 0.3× 918 1.1× 359 0.9× 382 1.3× 94 4.5k
Xiaojun Hei China 19 1.7k 1.1× 257 0.3× 502 0.6× 95 0.2× 337 1.1× 106 2.0k

Countries citing papers authored by Pedro Casas

Since Specialization
Citations

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

Fields of papers citing papers by Pedro Casas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pedro Casas

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

All Works

20 of 20 papers shown
1.
Casas, Pedro, et al.. (2024). MOXAI – Manufacturing Optimization through Model-Agnostic Explainable AI and Data-Driven Process Tuning. PHM Society European Conference. 8(1). 7–7. 1 indexed citations
2.
Casas, Pedro, et al.. (2024). On the Quest for Foundation Generative-AI Models for Anomaly Detection in Time-Series Data. 252–260. 2 indexed citations
3.
Seufert, Michael, Stefan Geißler, Andreas Hotho, et al.. (2024). Marina : Realizing ML-Driven Real-Time Network Traffic Monitoring at Terabit Scale. IEEE Transactions on Network and Service Management. 21(3). 2773–2790. 8 indexed citations
4.
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6.
Seufert, Michael, et al.. (2021). Quality that Matters: QoE Monitoring in Education Service Provider (ESP) Networks. OPUS (Augsburg University). 830–835. 2 indexed citations
7.
Seufert, Michael, et al.. (2018). A Fair Share for All: Novel Adaptation Logic for QoE Fairness of HTTP Adaptive Video Streaming. OPUS (Augsburg University). 19–27. 3 indexed citations
8.
Shtern, Mark, Pedro Casas, & Vassilios Tzerpos. (2018). Evaluating music mastering quality using machine learning.. Conference of the Centre for Advanced Studies on Collaborative Research. 126–135. 1 indexed citations
9.
Casas, Pedro, Pierdomenico Fiadino, & Alessandro D’Alconzo. (2016). Machine-Learning Based Approaches for Anomaly Detection and Classification in Cellular Networks.. 33 indexed citations
10.
Casas, Pedro, Alessandro D’Alconzo, Pierdomenico Fiadino, et al.. (2016). DBStream: A holistic approach to large-scale network traffic monitoring and analysis. Computer Networks. 107. 5–19. 16 indexed citations
11.
Casas, Pedro, et al.. (2015). Towards DisNETPerf: a Distributed Internet Paths Performance Analyzer. Open Repository and Bibliography (University of Liège). 1 indexed citations
12.
Sackl, Andreas, Pedro Casas, Raimund Schatz, Lucjan Janowski, & Ralf Irmer. (2015). Quantifying the impact of network bandwidth fluctuations and outages on Web QoE. 1–6. 26 indexed citations
13.
Casas, Pedro, et al.. (2015). On the quest for new KPIs in mobile networks: The impact of throughput fluctuations on QoE. 1705–1710. 11 indexed citations
14.
Fiadino, Pierdomenico, et al.. (2015). Online Social Networks anatomy: On the analysis of Facebook and WhatsApp in cellular networks. 1–9. 9 indexed citations
15.
Casas, Pedro, et al.. (2014). DBStream: an Online Aggregation, Filtering and Processing System for Network Traffic Monitoring. TrAC Trends in Analytical Chemistry. 8 indexed citations
16.
D’Alconzo, Alessandro, et al.. (2014). Who to Blame when YouTube is not Working? Detecting Anomalies in CDN Provisioned Services. TrAC Trends in Analytical Chemistry. 1 indexed citations
17.
Casas, Pedro, Michael Seufert, Sebastian Egger, & Raimund Schatz. (2013). Quality of experience in remote virtual desktop services. OPUS (Augsburg University). 1352–1357. 24 indexed citations
18.
Schatz, Raimund, Tobias Hoßfeld, & Pedro Casas. (2012). Passive YouTube QoE Monitoring for ISPs. 358–364. 69 indexed citations
19.
Casas, Pedro, Johan Mazel, & Philippe Owezarski. (2012). Unsupervised Network Intrusion Detection Systems: Detecting the Unknown without Knowledge. Computer Communications. 35(7). 772–783. 161 indexed citations
20.
Casas, Pedro, Johan Mazel, & Philippe Owezarski. (2011). MINETRAC: mining flows for unsupervised analysis & semi-supervised classification. 87–94. 18 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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