Harm van Beek

403 total citations
12 papers, 216 citations indexed

About

Harm van Beek is a scholar working on Information Systems, Signal Processing and Artificial Intelligence. According to data from OpenAlex, Harm van Beek has authored 12 papers receiving a total of 216 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Information Systems, 4 papers in Signal Processing and 4 papers in Artificial Intelligence. Recurrent topics in Harm van Beek's work include Digital and Cyber Forensics (7 papers), Advanced Malware Detection Techniques (4 papers) and Aging, Elder Care, and Social Issues (2 papers). Harm van Beek is often cited by papers focused on Digital and Cyber Forensics (7 papers), Advanced Malware Detection Techniques (4 papers) and Aging, Elder Care, and Social Issues (2 papers). Harm van Beek collaborates with scholars based in Netherlands, Switzerland and Germany. Harm van Beek's co-authors include Alex Nelson, Eoghan Casey, Sean Barnum, Sjouke Mauw, R.A.F. Bhoedjang, J. C. M. Baeten, Frank Breitinger, Mark Scanlon, Hugo Jonker and Marko van Eekelen and has published in prestigious journals such as Digital Investigation, Science & Justice and Forensic Science International Digital Investigation.

In The Last Decade

Harm van Beek

11 papers receiving 186 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Harm van Beek Netherlands	7	188	108	87	47	24	12	216
Christopher Hargreaves United Kingdom	8	201 1.1×	155 1.4×	87 1.0×	56 1.2×	37 1.5×	23	244
Bradley Schatz Australia	9	237 1.3×	180 1.7×	98 1.1×	85 1.8×	42 1.8×	18	273
Bodo Billerbeck Australia	9	230 1.2×	85 0.8×	67 0.8×	161 3.4×	33 1.4×	19	317
Jiaul H. Paik India	10	153 0.8×	35 0.3×	58 0.7×	269 5.7×	25 1.0×	27	346
Joel Mackenzie Australia	10	108 0.6×	65 0.6×	83 1.0×	137 2.9×	46 1.9×	32	229
Giovanni Cozzolino Italy	8	85 0.5×	38 0.4×	42 0.5×	52 1.1×	46 1.9×	19	163
Catherine Berrut France	8	70 0.4×	56 0.5×	82 0.9×	103 2.2×	14 0.6×	16	205
Quan Hung Tran United States	14	118 0.6×	51 0.5×	80 0.9×	345 7.3×	19 0.8×	26	427
Yves Chiaramella France	7	64 0.3×	54 0.5×	42 0.5×	128 2.7×	35 1.5×	20	191
Theo P. van der Weide Netherlands	9	83 0.4×	51 0.5×	14 0.2×	119 2.5×	76 3.2×	24	189

Countries citing papers authored by Harm van Beek

Since Specialization

Citations

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

Fields of papers citing papers by Harm van Beek

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Harm van Beek. 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 Harm van Beek. The network helps show where Harm van Beek may publish in the future.

Co-authorship network of co-authors of Harm van Beek

This figure shows the co-authorship network connecting the top 25 collaborators of Harm van Beek. A scholar is included among the top collaborators of Harm van Beek 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 Harm van Beek. Harm van Beek 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.

Beek, Harm van, et al.. (2025). Fine-Tuning Large Language Models for Digital Forensics: Case Study and General Recommendations. Open University of the Netherlands Research Portal. 6(4). 1–18.

2.

Beek, Harm van, et al.. (2020). Digital forensics as a service: Stepping up the game. Forensic Science International Digital Investigation. 35. 301021–301021. 21 indexed citations

3.

Jonker, Hugo, et al.. (2019). File Fragmentation in the Wild: a Privacy-Friendly Approach. Radboud Repository (Radboud University). 1–6. 2 indexed citations

4.

Beek, Harm van. (2018). A forensic visual aid: Traces versus knowledge. Science & Justice. 58(6). 425–432. 5 indexed citations

5.

Casey, Eoghan, et al.. (2017). Advancing coordinated cyber-investigations and tool interoperability using a community developed specification language. Digital Investigation. 22. 14–45. 32 indexed citations

6.

Beek, Harm van, et al.. (2015). Digital forensics as a service: Game on. Digital Investigation. 15. 20–38. 45 indexed citations

7.

Beek, Harm van, et al.. (2014). Digital Forensics as a Service: A game changer. Digital Investigation. 11. S54–S62. 61 indexed citations

8.

Bhoedjang, R.A.F., et al.. (2012). Engineering an online computer forensic service. Digital Investigation. 9(2). 96–108. 23 indexed citations

9.

Beek, Harm van. (2005). Specification and analysis of Internet applications. 17 indexed citations

10.

Beek, Harm van, et al.. (2003). Automatic Conformance Testing of Internet Applications. 1 indexed citations

11.

Baeten, J. C. M., Harm van Beek, & Sjouke Mauw. (2001). Specifying internet applications with DiCons. TU/e Research Portal. 576–584. 7 indexed citations

12.

Beek, Harm van, et al.. (2000). Internet Protocols for Distributed Consensus - The DiCons language. 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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