A. Ghosh

22.0k total citations
14 papers, 122 citations indexed

About

A. Ghosh is a scholar working on Nuclear and High Energy Physics, Astronomy and Astrophysics and Artificial Intelligence. According to data from OpenAlex, A. Ghosh has authored 14 papers receiving a total of 122 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Nuclear and High Energy Physics, 3 papers in Astronomy and Astrophysics and 3 papers in Artificial Intelligence. Recurrent topics in A. Ghosh's work include Particle physics theoretical and experimental studies (9 papers), Particle Detector Development and Performance (6 papers) and High-Energy Particle Collisions Research (3 papers). A. Ghosh is often cited by papers focused on Particle physics theoretical and experimental studies (9 papers), Particle Detector Development and Performance (6 papers) and High-Energy Particle Collisions Research (3 papers). A. Ghosh collaborates with scholars based in United States, Germany and France. A. Ghosh's co-authors include D. Whiteson, Benjamin Nachman, Tony Givargis, Pierre Baldi, X. Ju, Andrzej Siódmok, Andrew W. Steiner, Lee Lindblom, Fridolin Weber and Tim M. P. Tait and has published in prestigious journals such as SHILAP Revista de lepidopterología, Physical review. D and Journal of Cosmology and Astroparticle Physics.

In The Last Decade

A. Ghosh

10 papers receiving 120 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
A. Ghosh United States 8 65 33 32 18 13 14 122
Giuseppe Puglisi Italy 6 11 0.2× 42 1.3× 7 0.2× 6 0.3× 4 0.3× 22 75
Benjamin R. Ryan United States 7 135 2.1× 261 7.9× 10 0.3× 4 0.2× 5 0.4× 12 307
R. Williams United States 3 31 0.5× 153 4.6× 10 0.3× 24 1.3× 6 0.5× 7 169
T. Prince India 5 16 0.2× 43 1.3× 13 0.4× 5 0.3× 2 0.2× 15 76
S. Camarda Switzerland 7 214 3.3× 11 0.3× 14 0.4× 7 0.4× 2 0.2× 12 227
B. Miller Netherlands 4 19 0.3× 74 2.2× 23 0.7× 14 0.8× 6 102
H. Inchauspé Germany 5 28 0.4× 92 2.8× 8 0.3× 23 1.3× 7 111
Guang-Yao Zhao South Korea 9 148 2.3× 163 4.9× 22 0.7× 3 0.2× 8 0.6× 36 210
Jim Fowler United States 7 172 2.6× 69 2.1× 3 0.1× 4 0.2× 33 2.5× 17 261
John Belz United States 6 84 1.3× 39 1.2× 7 0.2× 5 0.3× 31 118

Countries citing papers authored by A. Ghosh

Since Specialization
Citations

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

Fields of papers citing papers by A. Ghosh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

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

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

All Works

14 of 14 papers shown
1.
Ghosh, A., et al.. (2025). Learning broken symmetries with approximate invariance. Physical review. D. 111(7).
2.
Shmakov, Alexander, Kevin Thomas Greif, M. J. Fenton, et al.. (2025). Full event particle-level unfolding with variable-length latent variational diffusion. SciPost Physics. 18(4). 6 indexed citations
3.
Modi, Chirag, A. Ghosh, Lee Lindblom, et al.. (2024). Neural simulation-based inference of the neutron star equation of state directly from telescope spectra. Journal of Cosmology and Astroparticle Physics. 2024(9). 9–9. 11 indexed citations
4.
Liu, Junze, A. Ghosh, Dylan Smith, Pierre Baldi, & D. Whiteson. (2023). Generalizing to new geometries with Geometry-Aware Autoregressive Models (GAAMs) for fast calorimeter simulation. Journal of Instrumentation. 18(11). P11003–P11003. 7 indexed citations
5.
Ghosh, A., et al.. (2023). Statistical patterns of theory uncertainties. SciPost Physics Core. 6(2). 9 indexed citations
6.
Baldi, Pierre, Jordan Ott, A. Ghosh, et al.. (2023). Deducing neutron star equation of state from telescope spectra with machine-learning-derived likelihoods. Journal of Cosmology and Astroparticle Physics. 2023(12). 22–22. 7 indexed citations
7.
Baldi, Pierre, Jordan Ott, A. Ghosh, et al.. (2023). Deducing neutron star equation of state parameters directly from telescope spectra with uncertainty-aware machine learning. Journal of Cosmology and Astroparticle Physics. 2023(2). 16–16. 12 indexed citations
8.
Ghosh, A., X. Ju, Benjamin Nachman, & Andrzej Siódmok. (2022). Towards a deep learning model for hadronization. Physical review. D. 106(9). 16 indexed citations
9.
Ghosh, A., Benjamin Nachman, & D. Whiteson. (2021). Uncertainty-aware machine learning for high energy physics. Physical review. D. 104(5). 29 indexed citations
10.
Ghosh, A.. (2020). Deep generative models for fast shower simulation in ATLAS. Journal of Physics Conference Series. 1525(1). 12077–12077. 13 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.
Hasib, A., J. Schaarschmidt, S. Gadatsch, et al.. (2018). New approaches using machine learning for fast shower simulation in ATLAS. CERN Bulletin.
13.
14.
Ghosh, A. & Tony Givargis. (2003). Cache optimization for embedded processor cores: an analytical approach. 342–347. 12 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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