Daniel Murnane

424 citations
16 papers · 143 · 1 hit paper · h-index 5

Impact in

Papers in

Daniel Murnane

11 papers receiving 124 citations

Daniel Murnane's Hit Papers

Software and computing for Run 3 of the ATLAS experiment at the LHC 2025 · 41 citations
410Years since publication10203040

Peers

Daniel Murnane
Comparison fields: 5 of 12
  • Nuclear and High Energy Physics 129
  • Information Systems and Management 4
  • Hardware and Architecture 3
  • Radiation 3
  • Artificial Intelligence 10
Replace F. Rehm with:
F. Rehm Switzerland
Y. Kazhykarim Switzerland
J. S. Dancu Switzerland
Horacio Crotte Ledesma Switzerland
Dimitrios Sidiropoulos Kontos Switzerland
Peilong Wang France
C. Li China
S. Kubota United States
C. Bennett Switzerland
Humberto Reyes-González Germany
Daniel Murnane relative to F. Rehm Switzerland F. Rehm's profile →
Citations per field
00.5×1.5×2×
F. Rehm · 1×
Citations per year

Countries citing papers authored by Daniel Murnane

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Murnane

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Daniel Murnane, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daniel Murnane Line = papers co-authored together Daniel Murnane links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1 201760
2
Software and computing for Run 3 of the ATLAS experiment at the LHC
Hit paper breakdown →
202541
3 202110
4 20238
5 20236
6 20245
7 20214
8 20233
9 20232
10 20232
11 20231
12 20231
13 20210
14 20240
15 20260
16 20260

About Daniel Murnane

Daniel Murnane is a scholar working on Nuclear and High Energy Physics, Artificial Intelligence, Computer Networks and Communications, Hardware and Architecture and Radiation, having authored 16 papers that have together received 143 indexed citations. Recurring topics across this work include Particle Detector Development and Performance (12 papers), Particle physics theoretical and experimental studies (9 papers), Neutrino Physics Research (3 papers), Advanced Graph Neural Networks (3 papers), Distributed and Parallel Computing Systems (1 paper), Distributed Sensor Networks and Detection Algorithms (1 paper), Parallel Computing and Optimization Techniques (1 paper) and Radiation Detection and Scintillator Technologies (1 paper). The work is most often cited by research in Nuclear and High Energy Physics (129 citations), Information Systems and Management (4 citations), Hardware and Architecture (3 citations), Radiation (3 citations) and Artificial Intelligence (10 citations). Daniel Murnane has collaborated with scholars based in United States, France and Australia. Frequent co-authors include Andy Buckley, Martin J. White, Christopher Sean Rogan, Lars Andreas DAL, Paul Jackson, Aldo Saavedra, Abram Krislock, Ben Farmer, Anders Kvellestad and Antje Putze. Their work appears in journals such as The European Physical Journal C, Journal of Instrumentation, Journal of High Energy Physics, Journal of Physics Conference Series and EPJ Web of Conferences.

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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