H. M. Gray

113.2k total citations
27 papers, 117 citations indexed

About

H. M. Gray is a scholar working on Nuclear and High Energy Physics, Computer Networks and Communications and Artificial Intelligence. According to data from OpenAlex, H. M. Gray has authored 27 papers receiving a total of 117 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Nuclear and High Energy Physics, 6 papers in Computer Networks and Communications and 5 papers in Artificial Intelligence. Recurrent topics in H. M. Gray's work include Particle physics theoretical and experimental studies (20 papers), Particle Detector Development and Performance (15 papers) and High-Energy Particle Collisions Research (9 papers). H. M. Gray is often cited by papers focused on Particle physics theoretical and experimental studies (20 papers), Particle Detector Development and Performance (15 papers) and High-Energy Particle Collisions Research (9 papers). H. M. Gray collaborates with scholars based in United States, Switzerland and France. H. M. Gray's co-authors include Pieter Glatzel, Uwe Bergmann, Stephen P. Cramer, Jesper Bendix, K. Terashi, Cécile Germain, Sarah E. Nelson, T. Theveneaux-Pelzer, C. Leggett and J. Elmsheuser and has published in prestigious journals such as The Journal of Chemical Physics, SHILAP Revista de lepidopterología and Reports on Progress in Physics.

In The Last Decade

H. M. Gray

20 papers receiving 116 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
H. M. Gray United States 7 43 26 19 17 14 27 117
S. Rankowitz United States 9 27 0.6× 28 1.1× 4 0.2× 4 0.2× 14 1.0× 12 139
V. Gibson United Kingdom 6 71 1.7× 39 1.5× 6 0.3× 4 0.2× 9 0.6× 14 136
В. А. Крылов Russia 7 10 0.2× 13 0.5× 32 1.7× 2 0.1× 2 0.1× 22 97
W. Kroeger United States 9 55 1.3× 73 2.8× 11 0.6× 2 0.1× 20 1.4× 19 158
C. Lopez-Cuenca Switzerland 7 42 1.0× 83 3.2× 4 0.2× 5 0.3× 7 0.5× 9 162
S. Bolognesi Switzerland 9 336 7.8× 27 1.0× 11 0.6× 7 0.4× 5 0.4× 20 401
Yinhong Luo China 9 91 2.1× 10 0.4× 3 0.2× 3 0.2× 9 0.6× 52 277
M. Nozaki Japan 6 92 2.1× 23 0.9× 3 0.2× 2 0.1× 6 0.4× 29 151
R. D. Harding United Kingdom 8 17 0.4× 13 0.5× 14 0.7× 3 0.2× 38 182
D. Kühn Austria 9 91 2.1× 13 0.5× 21 1.1× 1 0.1× 4 0.3× 25 232

Countries citing papers authored by H. M. Gray

Since Specialization
Citations

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

Fields of papers citing papers by H. M. Gray

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of H. M. Gray

This figure shows the co-authorship network connecting the top 25 collaborators of H. M. Gray. A scholar is included among the top collaborators of H. M. Gray 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 H. M. Gray. H. M. Gray 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.
Ai, X., et al.. (2023). A non-linear Kalman filter for track parameters estimation in high energy physics. Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment. 1049. 168041–168041. 2 indexed citations
2.
Brüning, O., H. M. Gray, K. Klein, et al.. (2022). The scientific potential and technological challenges of the High-Luminosity Large Hadron Collider program. Reports on Progress in Physics. 85(4). 46201–46201. 10 indexed citations
3.
Nelson, Sarah E., et al.. (2022). Time out: Prediction of self-exclusion from daily fantasy sports.. Psychology of Addictive Behaviors. 36(4). 318–332. 6 indexed citations
4.
Gray, H. M. & K. Terashi. (2022). Quantum Computing Applications in Future Colliders. Frontiers in Physics. 10. 7 indexed citations
5.
Gray, H. M., et al.. (2021). Porting HEP Parameterized Calorimeter Simulation Code to GPUs. Frontiers in Big Data. 4. 665783–665783. 4 indexed citations
6.
Ai, X., C. Allaire, N. Calace, et al.. (2020). Acts Project: v3.0.0. Zenodo (CERN European Organization for Nuclear Research). 2 indexed citations
7.
Gray, H. M. & P. Janot. (2020). Higgs Physics. Comptes Rendus Physique. 21(1). 23–43. 1 indexed citations
8.
Gray, H. M., M. Kiehn, F. Klimpel, et al.. (2020). The Acts project: track reconstruction software for HL-LHC and beyond. SHILAP Revista de lepidopterología. 245. 10003–10003. 3 indexed citations
9.
Muškinja, M., J. D. Chapman, & H. M. Gray. (2020). Geant4 performance optimization in the ATLAS experiment. SHILAP Revista de lepidopterología. 245. 2036–2036.
10.
Saito, M., P. Calafiura, H. M. Gray, et al.. (2020). Quantum annealing algorithms for track pattern recognition. SHILAP Revista de lepidopterología. 245. 10006–10006. 4 indexed citations
11.
Chapman, J. D., K. Cranmer, S. Gadatsch, et al.. (2020). Fast simulation methods in ATLAS: from classical to generative models. SHILAP Revista de lepidopterología. 245. 2035–2035.
12.
Kiehn, M., P. Calafiura, Steven Farrell, et al.. (2019). The TrackML high-energy physics tracking challenge on Kaggle. SHILAP Revista de lepidopterología. 214. 6037–6037. 4 indexed citations
13.
Rousseau, D., P. Calafiura, Steven Farrell, et al.. (2018). The TrackML challenge. SPIRE - Sciences Po Institutional REpository. 1–23. 2 indexed citations
14.
Braun, N., P. Calafiura, Steven Farrell, et al.. (2017). Track reconstruction at LHC as a collaborative data challenge use case with RAMP. SHILAP Revista de lepidopterología. 150. 15–15. 4 indexed citations
15.
Gray, H. M., et al.. (2013). Search for the Standard Model Higgs boson produced in association with a vector boson and decaying to bottom quarks with the ATLAS detector. SHILAP Revista de lepidopterología. 49. 18027–18027. 1 indexed citations
16.
Gray, H. M.. (2012). Measurement of theb-jet cross-section with associated vector boson production with the ATLAS experiment at the LHC. SHILAP Revista de lepidopterología. 28. 12050–12050. 1 indexed citations
17.
Aad, G., H. M. Gray, З. Маршалл, D. López Mateos, & K. Perez. (2012). Measurement of the charge asymmetry in top quark pairproduction in pp collisions at √s = 7 TeV using the ATLASdetector. eScholarship (California Digital Library). 4 indexed citations
18.
Aad, G., H. M. Gray, З. Маршалл, D. Lopez Mateos, & K. Perez. (2012). Search for the Higgs Boson in the H → WW^((*))→ l^+ vl^-v Decay Channel in pp Collisions at √s = 7 TeV with the ATLAS Detector. CaltechAUTHORS (California Institute of Technology). 1 indexed citations
19.
Aad, G., H. M. Gray, З. Маршалл, D. López Mateos, & K. Perez. (2011). Search for new phenomena in final states with largejet multiplicities and missing transverse momentumusing √s = 7 TeV pp collisions with the ATLASdetector. eScholarship (California Digital Library).
20.
Gray, H. M.. (2009). Alignment of the ATLAS inner detector tracking system. Journal of Instrumentation. 4(3). P03018–P03018.

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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