M. Ughetto

56.0k total citations
6 papers, 91 citations indexed

About

M. Ughetto is a scholar working on Nuclear and High Energy Physics, Computational Theory and Mathematics and Materials Chemistry. According to data from OpenAlex, M. Ughetto has authored 6 papers receiving a total of 91 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Nuclear and High Energy Physics, 2 papers in Computational Theory and Mathematics and 2 papers in Materials Chemistry. Recurrent topics in M. Ughetto's work include Particle physics theoretical and experimental studies (3 papers), Computational Drug Discovery Methods (2 papers) and Machine Learning in Materials Science (2 papers). M. Ughetto is often cited by papers focused on Particle physics theoretical and experimental studies (3 papers), Computational Drug Discovery Methods (2 papers) and Machine Learning in Materials Science (2 papers). M. Ughetto collaborates with scholars based in Sweden, Spain and United Kingdom. M. Ughetto's co-authors include Anna Gogleva, Aurélie Bornot, Matthias Pfeifer, Matthew J. Martin, Dimitris Polychronopoulos, Paul D. Smith, Eliseo Papa, Jonathan R. Dry, Miika Ahdesmäki and Ultan McDermott and has published in prestigious journals such as Nature Communications, The Journal of Physical Chemistry C and Computer Physics Communications.

In The Last Decade

M. Ughetto

5 papers receiving 89 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
M. Ughetto Sweden	4	34	30	17	16	7	6	91
Jamie Overbeek United States	5	64 1.9×	5 0.2×	10 0.6×	25 1.6×	10 1.4×	7	122
E. Asilar Austria	5	22 0.6×	41 1.4×	6 0.4×	37 2.3×		11	86
S. Y. Jun United States	5	28 0.8×	30 1.0×	9 0.5×	7 0.4×		19	78
Aristeidis Tsaris United States	6	11 0.3×	16 0.5×	24 1.4×	13 0.8×		15	86
Clark Barwick United States	9	16 0.5×	9 0.3×	19 1.1×	7 0.4×	1 0.1×	13	268
Jeff Smith United States	4	15 0.4×	9 0.3×	10 0.6×	13 0.8×		7	256
L. Rinaldi Italy	5	15 0.4×	9 0.3×	11 0.6×		9 1.3×	25	103
C.P. O'Grady United States	5	11 0.3×	28 0.9×	9 0.5×	3 0.2×		11	97
X. Chen France	6	32 0.9×	19 0.6×	4 0.2×		3 0.4×	10	86
Rong Zhao China	6	44 1.3×	15 0.5×	3 0.2×	3 0.2×	2 0.3×	15	102

Countries citing papers authored by M. Ughetto

Since Specialization

Citations

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

Fields of papers citing papers by M. Ughetto

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of M. Ughetto

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

All Works

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6 of 6 papers shown

1.

Ughetto, M., et al.. (2024). Machine Learning-Based Interpretation of Optical Properties of Colloidal Gold with Convolutional Neural Networks. The Journal of Physical Chemistry C. 128(33). 13909–13916. 4 indexed citations

2.

Kneur, Jean-Loı̈c, G. Moultaka, M. Ughetto, D. Zerwas, & A. Djouadi. (2023). SuSpect3: A C++ code for the supersymmetric and Higgs particle spectrum of the MSSM. Computer Physics Communications. 291. 108805–108805. 3 indexed citations

3.

Gogleva, Anna, Dimitris Polychronopoulos, Matthias Pfeifer, et al.. (2022). Knowledge graph-based recommendation framework identifies drivers of resistance in EGFR mutant non-small cell lung cancer. Nature Communications. 13(1). 1667–1667. 48 indexed citations

4.

Rózemberczki, Benedek, Charles Tapley Hoyt, Anna Gogleva, et al.. (2022). ChemicalX: A Deep Learning Library for Drug Pair Scoring. Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. 3819–3828. 9 indexed citations

5.

Ughetto, M.. (2016). ATLAS Supersymmetry Searches. CERN Document Server (European Organization for Nuclear Research).

6.

Abulaiti, Y., H. Åkerstedt, K. Bendtz, et al.. (2015). Zboson production inp+Pbcollisions atsNN=5.02TeV measured with the ATLAS detector. Physical Review C. 92(4). 27 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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