A. Aurisano

20.4k total citations · 1 hit paper
13 papers, 407 citations indexed

About

A. Aurisano is a scholar working on Nuclear and High Energy Physics, Radiation and Computer Networks and Communications. According to data from OpenAlex, A. Aurisano has authored 13 papers receiving a total of 407 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Nuclear and High Energy Physics, 2 papers in Radiation and 1 paper in Computer Networks and Communications. Recurrent topics in A. Aurisano's work include Particle physics theoretical and experimental studies (7 papers), Neutrino Physics Research (6 papers) and Particle Detector Development and Performance (4 papers). A. Aurisano is often cited by papers focused on Particle physics theoretical and experimental studies (7 papers), Neutrino Physics Research (6 papers) and Particle Detector Development and Performance (4 papers). A. Aurisano collaborates with scholars based in United States, Russia and Italy. A. Aurisano's co-authors include A. Himmel, M. Williams, Alexander Radovic, M. Kagan, D. Rousseau, T. Wongjirad, K. Terao, A. Sousa, F. Psihas and D. Rocco and has published in prestigious journals such as Nature, SHILAP Revista de lepidopterología and Physics Letters B.

In The Last Decade

A. Aurisano

12 papers receiving 393 citations

Hit Papers

Machine learning at the energy and intensity frontiers of... 2018 2026 2020 2023 2018 50 100 150 200 250
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Machine learning at the energy and intensity frontiers of particle physics
    2018 253 citations Alexander Radovic, M. Williams et al. Nature profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
A. Aurisano United States 6 245 92 45 37 35 13 407
A. Himmel United States 3 205 0.8× 86 0.9× 45 1.0× 21 0.6× 33 0.9× 4 356
Federico Carminati Switzerland 9 156 0.6× 107 1.2× 26 0.6× 18 0.5× 56 1.6× 69 409
Julian Kates‐Harbeck United States 5 138 0.6× 57 0.6× 29 0.6× 27 0.7× 20 0.6× 10 303
K. Terao United States 7 165 0.7× 84 0.9× 100 2.2× 23 0.6× 23 0.7× 26 450
Alexander Radovic Italy 1 128 0.5× 69 0.8× 39 0.9× 13 0.4× 14 0.4× 2 253
M. Williams United States 10 573 2.3× 85 0.9× 43 1.0× 127 3.4× 24 0.7× 24 724
Johann Brehmer United States 12 454 1.9× 149 1.6× 30 0.7× 100 2.7× 7 0.2× 23 600
B. Sammuli United States 10 241 1.0× 40 0.4× 40 0.9× 33 0.9× 42 1.2× 29 326
A. Portas Spain 10 156 0.6× 36 0.4× 11 0.2× 32 0.9× 62 1.8× 40 262
K. Krüger Germany 10 204 0.8× 102 1.1× 15 0.3× 14 0.4× 31 0.9× 14 390

Countries citing papers authored by A. Aurisano

Since Specialization
Citations

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

Fields of papers citing papers by A. Aurisano

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of A. Aurisano

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

All Works

13 of 13 papers shown
1.
Aurisano, A., et al.. (2024). Graph neural network for neutrino physics event reconstruction. Physical review. D. 110(3). 1 indexed citations
2.
Cerati, G. B., et al.. (2024). Addressing GPU memory limitations for Graph Neural Networks in High-Energy Physics applications. SHILAP Revista de lepidopterología. 2. 1 indexed citations
3.
Hewes, V, G. B. Cerati, Jim Kowalkowski, et al.. (2023). A Case Study of Data Management Challenges Presented in Large-Scale Machine Learning Workflows. 71–81. 5 indexed citations
4.
Aurisano, A., G. B. Cerati, Jim Kowalkowski, et al.. (2021). Graph Neural Network for Object Reconstruction in Liquid Argon Time Projection Chambers. SHILAP Revista de lepidopterología. 251. 3054–3054. 7 indexed citations
5.
Анфимов, Н., A. Antoshkin, A. Aurisano, O. Samoylov, & A. Sotnikov. (2020). JINR stand measurements for improvements in the NOvA detector simulation chain. Journal of Instrumentation. 15(6). C06066–C06066.
6.
Psihas, F., E. Niner, M. Groh, et al.. (2019). Context-enriched identification of particles with a convolutional network for neutrino events. Physical review. D. 100(7). 5 indexed citations
7.
Radovic, Alexander, M. Williams, D. Rousseau, et al.. (2018). Machine learning at the energy and intensity frontiers of particle physics. Nature. 560(7716). 41–48. 253 indexed citations breakdown →
8.
Aurisano, A.. (2018). Recent Results From Minos And Minos+. Zenodo (CERN European Organization for Nuclear Research). 423. 5 indexed citations
9.
Davies, G. S., et al.. (2017). Searches for Sterile Neutrinos with NOvA. Proceedings Of Science. 972–972. 1 indexed citations
10.
Aurisano, A., A. Radovic, D. Rocco, et al.. (2016). A convolutional neural network neutrino event classifier. Journal of Instrumentation. 11(9). P09001–P09001. 96 indexed citations
11.
Aurisano, A., C. Backhouse, R. Hatcher, et al.. (2015). The NOvA simulation chain. Journal of Physics Conference Series. 664(7). 72002–72002. 9 indexed citations
12.
Arnowitt, R., A. Aurisano, Bhaskar Dutta, et al.. (2007). Indirect measurements of the τ˜–χ˜10 mass difference and Mg˜ in the co-annihilation region of mSUGRA models at the LHC. Physics Letters B. 649(1). 73–82. 22 indexed citations
13.
Arnowitt, R., A. Aurisano, Bhaskar Dutta, et al.. (2006). Measuring the Stau Minus Neutralino Mass Difference in Co-annihilation Scenarios at the LHC. arXiv (Cornell University). 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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