S. Klous

23.7k total citations
29 papers, 302 citations indexed

About

S. Klous is a scholar working on Nuclear and High Energy Physics, Computer Networks and Communications and Artificial Intelligence. According to data from OpenAlex, S. Klous has authored 29 papers receiving a total of 302 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Nuclear and High Energy Physics, 7 papers in Computer Networks and Communications and 6 papers in Artificial Intelligence. Recurrent topics in S. Klous's work include Particle Detector Development and Performance (6 papers), Distributed and Parallel Computing Systems (6 papers) and Particle physics theoretical and experimental studies (4 papers). S. Klous is often cited by papers focused on Particle Detector Development and Performance (6 papers), Distributed and Parallel Computing Systems (6 papers) and Particle physics theoretical and experimental studies (4 papers). S. Klous collaborates with scholars based in Netherlands, Germany and United Kingdom. S. Klous's co-authors include M. Baak, R. F. Koopman, H. L. Snoek, Yuri Demchenko, Miriam Klous, Tom van Engers, Michael Lees, Douglas Thain, Jesús A. Izaguirre and Paul Brenner and has published in prestigious journals such as Scientific Reports, ACM Computing Surveys and Physica A Statistical Mechanics and its Applications.

In The Last Decade

S. Klous

26 papers receiving 291 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
S. Klous Netherlands	8	50	47	38	31	30	29	302
Dongsheng Liu China	9	15 0.3×	86 1.8×	35 0.9×	32 1.0×	5 0.2×	36	284
Sallie Keller‐McNulty United States	11	15 0.3×	74 1.6×	35 0.9×	18 0.6×	31 1.0×	49	421
Huifeng Xue China	10	61 1.2×	52 1.1×	32 0.8×	4 0.1×	12 0.4×	31	328
Xiaoqian Chen China	9	14 0.3×	38 0.8×	20 0.5×	12 0.4×	10 0.3×	38	270
Andreas M. Hein France	11	21 0.4×	92 2.0×	69 1.8×	3 0.1×	18 0.6×	68	451
Ingolf Krueger United States	13	72 1.4×	70 1.5×	81 2.1×	12 0.4×	13 0.4×	24	301
Fan Liu China	14	11 0.2×	57 1.2×	17 0.4×	4 0.1×	18 0.6×	37	463
John Fulcher Australia	8	19 0.4×	153 3.3×	41 1.1×	12 0.4×	11 0.4×	56	413

Countries citing papers authored by S. Klous

Since Specialization

Citations

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

Fields of papers citing papers by S. Klous

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of S. Klous

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

All Works

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20 of 20 papers shown

Amiri, Saba, Henri E. Bal, Adam Belloum, et al.. (2024). Private and Secure Distributed Deep Learning: A Survey. ACM Computing Surveys. 57(4). 1–43. 1 indexed citations

Oprescu, Ana, et al.. (2024). A Framework to Optimize the Energy Cost of Securing Neural Network Inference. UvA-DARE (University of Amsterdam). 339–346.

Engers, Tom van, et al.. (2023). Do agents dream of abiding by the rules?. UvA-DARE (University of Amsterdam). 81–90. 2 indexed citations

Klous, S., et al.. (2022). Manipulation of the Bitcoin market: an agent-based study. Financial Innovation. 8(1). 60–60. 16 indexed citations

Lees, Michael, et al.. (2022). Modelling the dynamic relationship between spread of infection and observed crowd movement patterns at large scale events. Scientific Reports. 12(1). 14825–14825. 3 indexed citations

Amiri, Saba, Adam Belloum, Eric Nalisnick, S. Klous, & Leon Gommans. (2022). On the impact of non-IID data on the performance and fairness of differentially private federated learning. UvA-DARE (University of Amsterdam). 52–58. 7 indexed citations

Engers, Tom van, et al.. (2020). Run, agent, run! architecture and benchmarking of actor-based agents. UvA-DARE (University of Amsterdam). 11–20. 1 indexed citations

Baak, M., R. F. Koopman, H. L. Snoek, & S. Klous. (2020). A new correlation coefficient between categorical, ordinal and interval variables with Pearson characteristics. Computational Statistics & Data Analysis. 152. 107043–107043. 136 indexed citations

Belloum, Adam, et al.. (2020). Policy Enforcement for Secure and Trustworthy Data Sharing in Multi-domain Infrastructures. UvA-DARE (University of Amsterdam). 160. 104–113. 2 indexed citations

10.

Lees, Michael, et al.. (2020). Intermittent and persistent movement patterns of dance event visitors in large sporting venues. Physica A Statistical Mechanics and its Applications. 563. 125448–125448. 7 indexed citations

11.

Georgievska, Sonja, et al.. (2019). Detecting high indoor crowd density with Wi-Fi localization: a statistical mechanics approach. Journal Of Big Data. 6(1). 15 indexed citations

12.

Klous, S.. (2010). Event streaming in the online system: Real-time organization of ATLAS data. 3. 1–8. 1 indexed citations

13.

Klous, S.. (2010). Event streaming in the online system. CERN Document Server (European Organization for Nuclear Research).

14.

Klous, S.. (2005). The LHCb vertex detector. Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment. 549(1-3). 55–59. 1 indexed citations

15.

Thain, Douglas, S. Klous, Justin M. Wozniak, et al.. (2005). Separating Abstractions from Resources in a Tactical Storage System. 23. 55–55. 16 indexed citations

16.

Klous, S., et al.. (2005). Transparent access to Grid resources for user software. Concurrency and Computation Practice and Experience. 18(7). 787–801. 9 indexed citations

17.

Schmelling, M., W. Hofmann, N. Harnew, et al.. (2004). SEU robustness, total dose radiation hardness and analog performance of the Beetle chip. CERN Document Server (European Organization for Nuclear Research). 1 indexed citations

18.

Brand, J. F. J. van den, D. Baumeister, M. van Beuzekom, et al.. (2003). Characterisation of a radiation hard front-end chip for the vertex detector of the LHCb experiment at CERN. Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment. 509(1-3). 176–182.

19.

Brook, N. H., H. Bulten, J. Closier, et al.. (2003). LHCb distributed computing and the GRID. Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment. 502(2-3). 334–338. 2 indexed citations

20.

Agari, M., J. F. J. van den Brand, C. Bauer, et al.. (2003). Beetle—a radiation hard readout chip for the LHCb experiment. Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment. 518(1-2). 468–469. 15 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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