M. Lassnig

102.0k total citations
62 papers, 304 citations indexed

About

M. Lassnig is a scholar working on Computer Networks and Communications, Information Systems and Management and Nuclear and High Energy Physics. According to data from OpenAlex, M. Lassnig has authored 62 papers receiving a total of 304 indexed citations (citations by other indexed papers that have themselves been cited), including 60 papers in Computer Networks and Communications, 36 papers in Information Systems and Management and 9 papers in Nuclear and High Energy Physics. Recurrent topics in M. Lassnig's work include Distributed and Parallel Computing Systems (56 papers), Advanced Data Storage Technologies (45 papers) and Scientific Computing and Data Management (34 papers). M. Lassnig is often cited by papers focused on Distributed and Parallel Computing Systems (56 papers), Advanced Data Storage Technologies (45 papers) and Scientific Computing and Data Management (34 papers). M. Lassnig collaborates with scholars based in Switzerland, United States and Austria. M. Lassnig's co-authors include V. Garonne, M-S. Barisits, C. Serfon, A. M. Nairz, L. Goossens, Miguel Castelo‐Branco, R. Vigne, G. A. Stewart, T. Wenaus and B. Koblitz and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Computational Science and Concurrency and Computation Practice and Experience.

In The Last Decade

M. Lassnig

58 papers receiving 291 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
M. Lassnig Switzerland 9 285 138 64 47 34 62 304
V. Garonne Switzerland 8 245 0.9× 110 0.8× 57 0.9× 40 0.9× 31 0.9× 45 260
Benjamin Gaidioz Switzerland 9 193 0.7× 80 0.6× 26 0.4× 24 0.5× 26 0.8× 29 203
E. Karavakis Switzerland 9 157 0.6× 95 0.7× 32 0.5× 21 0.4× 15 0.4× 32 184
D. Oleynik United States 10 211 0.7× 118 0.9× 55 0.9× 35 0.7× 36 1.1× 42 227
I. Vukotić United States 6 109 0.4× 33 0.2× 30 0.5× 14 0.3× 13 0.4× 26 127
A. Wäänänen Canada 7 202 0.7× 95 0.7× 16 0.3× 43 0.9× 74 2.2× 16 224
I. Legrand United States 7 99 0.3× 28 0.2× 19 0.3× 37 0.8× 19 0.6× 18 129
Frédéric Hemmer Switzerland 3 191 0.7× 108 0.8× 8 0.1× 55 1.2× 61 1.8× 5 204
Florian Schintke Germany 8 289 1.0× 59 0.4× 4 0.1× 104 2.2× 61 1.8× 37 318
Dimitrios Katramatos United States 8 230 0.8× 21 0.2× 7 0.1× 98 2.1× 44 1.3× 34 250

Countries citing papers authored by M. Lassnig

Since Specialization
Citations

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

Fields of papers citing papers by M. Lassnig

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of M. Lassnig

This figure shows the co-authorship network connecting the top 25 collaborators of M. Lassnig. A scholar is included among the top collaborators of M. Lassnig 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 M. Lassnig. M. Lassnig 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.
Borodin, M., K. De, J. Elmsheuser, et al.. (2024). Accelerating science: The usage of commercial clouds in ATLAS Distributed Computing. SHILAP Revista de lepidopterología. 295. 7002–7002. 1 indexed citations
2.
Barisits, M-S., R. M. Barnsley, J. Elmsheuser, et al.. (2024). Extending Rucio with modern cloud storage support. SHILAP Revista de lepidopterología. 295. 1030–1030. 1 indexed citations
3.
Elmsheuser, J., A. De Salvo, R. Hauser, et al.. (2024). The ATLAS experiment software on ARM. SHILAP Revista de lepidopterología. 295. 5019–5019. 1 indexed citations
4.
Clissa, L., M. Lassnig, & L. Rinaldi. (2023). How big is Big Data? A comprehensive survey of data production, storage, and streaming in science and industry. Frontiers in Big Data. 6. 1271639–1271639. 2 indexed citations
5.
Wegner, Tobias, M. Lassnig, P. Ueberholz, & C. Zeitnitz. (2021). Simulation and Evaluation of Cloud Storage Caching for Data Intensive Science. PubMed. 6(1). 5–5. 2 indexed citations
6.
Vale, T. Dias Do, F. Legger, J. Schovancova, et al.. (2020). Operational Intelligence for Distributed Computing Systems for Exascale Science. SHILAP Revista de lepidopterología. 245. 3017–3017. 3 indexed citations
7.
Bockelman, Brian, et al.. (2019). Bootstrapping a New LHC Data Transfer Ecosystem. SHILAP Revista de lepidopterología. 214. 4045–4045. 1 indexed citations
8.
Anisenkov, A. V., et al.. (2018). Global heterogeneous resource harvesting: the next-generation PanDA Pilot for ATLAS. Journal of Physics Conference Series. 1085. 32031–32031. 1 indexed citations
9.
Barisits, M-S., T. A. Beermann, V. Garonne, et al.. (2018). The ATLAS Data Management System Rucio: Supporting LHC Run-2 and beyond. Journal of Physics Conference Series. 1085. 32030–32030. 8 indexed citations
10.
Díaz, Javier, et al.. (2018). Modelling high-energy physics data transfers. CERN Document Server (European Organization for Nuclear Research). 13. 334–335. 1 indexed citations
11.
Beermann, T. A., M. Lassnig, M-S. Barisits, C. Serfon, & V. Garonne. (2017). C3PO - A Dynamic Data Placement Agent for ATLAS Distributed Data Management. Journal of Physics Conference Series. 898. 62012–62012. 2 indexed citations
12.
Lassnig, M., et al.. (2017). Machine learning of network metrics in ATLAS Distributed Data Management. Journal of Physics Conference Series. 898. 62009–62009. 1 indexed citations
13.
Garonne, V., M-S. Barisits, T. A. Beermann, et al.. (2017). Experiences with the new ATLAS Distributed Data Management System. Journal of Physics Conference Series. 898. 62019–62019. 3 indexed citations
14.
Serfon, C., M-S. Barisits, T. A. Beermann, et al.. (2016). Rucio, the next-generation Data Management system in ATLAS. Nuclear and Particle Physics Proceedings. 273-275. 969–975. 8 indexed citations
15.
Barisits, M-S., C. Serfon, V. Garonne, et al.. (2014). ATLAS Replica Management in Rucio: Replication Rules and Subscriptions. Journal of Physics Conference Series. 513(4). 42003–42003. 8 indexed citations
16.
Beermann, T. A., Peter Maettig, G. A. Stewart, et al.. (2014). Popularity Prediction Tool for ATLAS Distributed Data Management. Journal of Physics Conference Series. 513(4). 42004–42004. 3 indexed citations
17.
Serfon, C., M-S. Barisits, T. A. Beermann, et al.. (2014). ATLAS DQ2 to Rucio renaming infrastructure. Journal of Physics Conference Series. 513(4). 42008–42008. 2 indexed citations
18.
Vigne, R., Erich Schikuta, V. Garonne, et al.. (2014). DDM Workload Emulation. Journal of Physics Conference Series. 513(4). 42048–42048. 2 indexed citations
19.
Stewart, G. A., V. Garonne, M. Lassnig, et al.. (2012). Advances in service and operations for ATLAS data management. Journal of Physics Conference Series. 368. 12005–12005. 2 indexed citations
20.
Castelo‐Branco, Miguel, Ed Zaluska, David De Roure, M. Lassnig, & V. Garonne. (2009). Managing very large distributed datasets on a data grid. ePrints Soton (University of Southampton). 6 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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