Patrick Connor

2.2k total citations
17 papers, 169 citations indexed

About

Patrick Connor is a scholar working on Nuclear and High Energy Physics, Electrical and Electronic Engineering and Artificial Intelligence. According to data from OpenAlex, Patrick Connor has authored 17 papers receiving a total of 169 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Nuclear and High Energy Physics, 5 papers in Electrical and Electronic Engineering and 3 papers in Artificial Intelligence. Recurrent topics in Patrick Connor's work include Particle physics theoretical and experimental studies (7 papers), High-Energy Particle Collisions Research (4 papers) and Particle Detector Development and Performance (3 papers). Patrick Connor is often cited by papers focused on Particle physics theoretical and experimental studies (7 papers), High-Energy Particle Collisions Research (4 papers) and Particle Detector Development and Performance (3 papers). Patrick Connor collaborates with scholars based in Germany, United States and Belgium. Patrick Connor's co-authors include R. Žlebčík, H. Jung, F. Hautmann, A. Bermúdez Martínez, A. Lelek, V. Radescu, L. I. Estevez Banos, Daniela Domínguez Damiani, J. Lidrych and M. Schmitz and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Antennas and Propagation and Journal of Shoulder and Elbow Surgery.

In The Last Decade

Patrick Connor

13 papers receiving 162 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Patrick Connor Germany 6 128 24 20 7 7 17 169
Y. Takubo Japan 6 77 0.6× 28 1.2× 16 0.8× 6 0.9× 5 0.7× 28 100
S. Fazio United States 8 215 1.7× 14 0.6× 10 0.5× 5 0.7× 17 2.4× 17 243
Deepak Samuel India 8 101 0.8× 23 1.0× 8 0.4× 4 0.6× 15 2.1× 22 135
D. Amidei United States 4 92 0.7× 21 0.9× 19 0.9× 3 0.4× 4 0.6× 13 115
T. Lohse Germany 4 102 0.8× 19 0.8× 24 1.2× 7 1.0× 5 0.7× 13 119
R. Mendoza United States 7 73 0.6× 25 1.0× 20 1.0× 5 0.7× 22 3.1× 9 90
Giovanni Stagnitto Switzerland 9 172 1.3× 9 0.4× 16 0.8× 7 1.0× 7 1.0× 21 195
Lizhi Sheng China 6 27 0.2× 26 1.1× 15 0.8× 3 0.4× 11 1.6× 26 76
Isabel Bejar Alonso Switzerland 3 53 0.4× 23 1.0× 7 0.3× 4 0.6× 7 1.0× 4 72
David Melkumyan Germany 4 37 0.3× 21 0.9× 16 0.8× 6 0.9× 11 1.6× 27 63

Countries citing papers authored by Patrick Connor

Since Specialization
Citations

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

Fields of papers citing papers by Patrick Connor

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Patrick Connor

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

All Works

17 of 17 papers shown
1.
Wolf, M., et al.. (2025). Fast Perfekt: Regression-based refinement of fast simulation. SciPost Physics Core. 8(1).
2.
Bein, Samuel, Patrick Connor, K. Pedro, P. Schleper, & M. Wolf. (2024). Refining fast simulation using machine learning. SHILAP Revista de lepidopterología. 295. 9032–9032. 1 indexed citations
3.
Griese, Florian, et al.. (2023). FIRST radio galaxy data set containing curated labels of classes FRI, FRII, compact and bent. Data in Brief. 47. 108974–108974. 6 indexed citations
4.
Bushnell, Brandon D., Patrick Connor, Howard W. Harris, et al.. (2023). Two-Year Outcomes With A Bioinductive Collagen Implant Used In Augmentation Of Arthroscopic Repair Of Full-Thickness Rotator Cuff Tears: Final Results Of A Prospective Multi-Center Study. Journal of Shoulder and Elbow Surgery. 32(5). e243–e244. 1 indexed citations
5.
Rustige, L., Florian Griese, K. Borras, et al.. (2023). Morphological classification of radio galaxies with Wasserstein generative adversarial network-supported augmentation. 2(1). 264–277. 8 indexed citations
6.
7.
Raghavan, Vasanthan, Patrick Connor, Yu-Chin Ou, et al.. (2021). Hand and Body Blockage Measurements With Form-Factor User Equipment at 28 GHz. IEEE Transactions on Antennas and Propagation. 70(1). 607–620. 16 indexed citations
8.
Benato, L., Patrick Connor, Gregor Kasieczka, D. Krücker, & Mareike Meyer. (2020). Teaching machine learning with an application in collider particle physics. Journal of Instrumentation. 15(9). C09011–C09011. 3 indexed citations
9.
Martínez, A. Bermúdez, Patrick Connor, Daniela Domínguez Damiani, et al.. (2020). The transverse momentum spectrum of low mass Drell–Yan production at next-to-leading order in the parton branching method. The European Physical Journal C. 80(7). 31 indexed citations
10.
Martínez, A. Bermúdez, Patrick Connor, H. Jung, et al.. (2019). Collinear and TMD parton densities from fits to precision DIS measurements in the parton branching method. Physical review. D. 99(7). 54 indexed citations
11.
Martínez, A. Bermúdez, Patrick Connor, Daniela Domínguez Damiani, et al.. (2019). Production of Z bosons in the parton branching method. Physical review. D. 100(7). 36 indexed citations
12.
Connor, Patrick, et al.. (2017). Advanced lithographic filtration and contamination control for 14nm node and beyond semiconductor processes. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 10146. 101462B–101462B. 5 indexed citations
13.
Connor, Patrick, et al.. (2017). Enhanced Cleaning for the Point-of-Use Filter and its Effectiveness on Wafer Defectivity in Immersion ArF Lithography Process. Journal of Photopolymer Science and Technology. 30(6). 639–643. 3 indexed citations
14.
Connor, Patrick, et al.. (2016). Probing the Role of Slurry Chemistry on Nanoparticle-Media Adsorption Relevant to Cu CMP Filtration Applications. ECS Meeting Abstracts. MA2016-01(17). 1051–1051. 1 indexed citations
15.
Connor, Patrick, et al.. (2016). TMDlib 1.0.8 and TMDplotter 2.1.1. Proceedings Of Science. 39–39.
16.
Connor, Patrick, et al.. (2016). TMDlib 1.0.8 and TMDplotter 2.1.1. DESY Publication Database (PUBDB) (Deutsches Elektronen-Synchrotron). 1 indexed citations
17.
Herdan, Gustav, et al.. (1961). Small Particle Statistics--An Account of Statistical Methods for the Investigation of Finely Divided Materials.. Journal of the Royal Statistical Society Series A (General). 124(3). 436–436. 3 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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