D. Nieto

10.5k total citations
23 papers, 148 citations indexed

About

D. Nieto is a scholar working on Nuclear and High Energy Physics, Astronomy and Astrophysics and Instrumentation. According to data from OpenAlex, D. Nieto has authored 23 papers receiving a total of 148 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Nuclear and High Energy Physics, 14 papers in Astronomy and Astrophysics and 2 papers in Instrumentation. Recurrent topics in D. Nieto's work include Astrophysics and Cosmic Phenomena (19 papers), Gamma-ray bursts and supernovae (8 papers) and Dark Matter and Cosmic Phenomena (8 papers). D. Nieto is often cited by papers focused on Astrophysics and Cosmic Phenomena (19 papers), Gamma-ray bursts and supernovae (8 papers) and Dark Matter and Cosmic Phenomena (8 papers). D. Nieto collaborates with scholars based in Spain, United States and Italy. D. Nieto's co-authors include T. B. Humensky, Bryan Kim, M. Sánchez‐Conde, Tjark Miener, Angela Kunoth, Mattia Di Mauro, N. Mirabal, V. Gammaldi, A. Domínguez and Javier Coronado-Blázquez and has published in prestigious journals such as Monthly Notices of the Royal Astronomical Society, IEEE Transactions on Image Processing and Journal of Cosmology and Astroparticle Physics.

In The Last Decade

D. Nieto

20 papers receiving 144 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
D. Nieto Spain 7 126 86 13 10 6 23 148
K. Egberts Germany 7 165 1.3× 109 1.3× 20 1.5× 7 0.7× 7 1.2× 20 189
A. Petrolini Italy 6 95 0.8× 33 0.4× 12 0.9× 6 0.6× 3 0.5× 26 113
Lili Yang China 8 117 0.9× 78 0.9× 5 0.4× 4 0.4× 2 0.3× 30 162
G. Maurin France 6 98 0.8× 107 1.2× 14 1.1× 4 0.4× 8 1.3× 21 130
I. Shilon Switzerland 4 65 0.5× 38 0.4× 12 0.9× 6 0.6× 7 1.2× 7 79
H. F. Yu Sweden 8 63 0.5× 157 1.8× 8 0.6× 4 0.4× 3 0.5× 14 169
S. M. Oser United States 7 174 1.4× 83 1.0× 7 0.5× 2 0.2× 1 0.2× 11 188
A. Sinha India 8 129 1.0× 121 1.4× 3 0.2× 4 0.4× 15 2.5× 14 154
G. Polesello Italy 11 398 3.2× 134 1.6× 12 0.9× 12 1.2× 1 0.2× 36 409
R. Conceição Portugal 9 201 1.6× 39 0.5× 24 1.8× 16 1.6× 2 0.3× 47 222

Countries citing papers authored by D. Nieto

Since Specialization
Citations

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

Fields of papers citing papers by D. Nieto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of D. Nieto

This figure shows the co-authorship network connecting the top 25 collaborators of D. Nieto. A scholar is included among the top collaborators of D. Nieto 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 D. Nieto. D. Nieto 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.
Miener, Tjark, D. Nieto, V. Gammaldi, D. Kerszberg, & J. Rico. (2023). Combined search in dwarf spheroidal galaxies for branon dark matter annihilation signatures with the MAGIC Telescopes. Proceedings Of Science. 196–196.
2.
Miener, Tjark, et al.. (2023). The performance of the MAGIC telescopes using deep convolutional neural networks with CTLearn. Proceedings Of Science. 220–220. 1 indexed citations
3.
Miener, Tjark, D. Nieto, V. Gammaldi, D. Kerszberg, & J. Rico. (2022). Constraining branon dark matter from observations of the Segue 1 dwarf spheroidal galaxy with the MAGIC telescopes. arXiv (Cornell University). 3 indexed citations
4.
Sánchez‐Conde, M., et al.. (2021). Cherenkov Telescope Array sensitivity to branon dark matter models. Proceedings of 37th International Cosmic Ray Conference — PoS(ICRC2021). 507–507. 1 indexed citations
5.
Arqueros, F., J. A. Barrio, A. Domínguez, et al.. (2021). Sensitivity of the Cherenkov Telescope Array for probing cosmology and fundamental physics with gamma-ray propagation. Journal of Cosmology and Astroparticle Physics. 2021(2). 48–48. 41 indexed citations
6.
Nieto, D., et al.. (2019). Studying Deep Convolutional Neural Networks With Hexagonal Lattices for Imaging Atmospheric Cherenkov Telescope Event Reconstruction. Proceedings of 36th International Cosmic Ray Conference — PoS(ICRC2019). 753–753. 10 indexed citations
7.
Coronado-Blázquez, Javier, M. Sánchez‐Conde, A. Domínguez, et al.. (2019). Unidentified Gamma-ray Sources as Targets for Indirect Dark Matter Detection with the Fermi-Large Area Telescope. Maryland Shared Open Access Repository (USMAI Consortium). 25 indexed citations
8.
Nieto, D., Q. Feng, T. B. Humensky, et al.. (2019). CTLearn: Deep Learning for Gamma-ray Astronomy. Proceedings of 36th International Cosmic Ray Conference — PoS(ICRC2019). 752–752. 12 indexed citations
9.
Bartos, I., J. R. Gair, M. Hendry, et al.. (2019). Strategies for the Follow-up of Gravitational Wave Transients at Very High-Energy Gamma Rays with the Cherenkov Telescope Array. Nuclear and Particle Physics Proceedings. 306-308. 69–73.
10.
Bartos, I., T. Di Girolamo, J. R. Gair, et al.. (2018). Strategies for the follow-up of gravitational wave transients with the Cherenkov Telescope Array. Monthly Notices of the Royal Astronomical Society. 477(1). 639–647. 5 indexed citations
11.
Nieto, D., et al.. (2017). Exploring deep learning as an event classification method for the Cherenkov Telescope Array. Proceedings of 35th International Cosmic Ray Conference — PoS(ICRC2017). 809–809. 13 indexed citations
12.
Nieto, D., T. B. Humensky, P. Kaaret, et al.. (2017). Prototype 9.7m Schwarzschild-Couder telescope for the Cherenkov Telescope Array: status of the optical system.. Proceedings of 35th International Cosmic Ray Conference — PoS(ICRC2017). 815–815. 1 indexed citations
13.
Nieto, D.. (2016). Hunting for dark matter subhalos among the Fermi-LAT sources with VERITAS. Proceedings of The 34th International Cosmic Ray Conference — PoS(ICRC2015). 1216–1216. 5 indexed citations
14.
Nieto, D., S. Griffiths, T. B. Humensky, et al.. (2016). Construction of a medium-sized Schwarzschild-Couder telescope as a candidate for the Cherenkov Telescope Array: development of the optical alignment system. Proceedings of The 34th International Cosmic Ray Conference — PoS(ICRC2015). 990–990. 2 indexed citations
15.
Rousselle, J., K. Byrum, R. A. Cameron, et al.. (2015). Construction of a Schwarzschild-Couder telescope as a candidate for the Cherenkov Telescope Array: Status of the optical system. Max Planck Digital Library. 938. 1 indexed citations
16.
Bartos, I., P. Vereš, D. Nieto, et al.. (2014). Cherenkov Telescope Array is well suited to follow up gravitational-wave transients. Monthly Notices of the Royal Astronomical Society. 443(1). 738–749. 11 indexed citations
17.
Nieto, D., J. Aleksić, J. A. Barrio, et al.. (2011). The search for galactic dark matter clump candidates with Fermi and MAGIC. International Cosmic Ray Conference. 5. 153. 1 indexed citations
18.
Sánchez‐Conde, M., A. Biland, M. Doro, et al.. (2009). The search for DM in nearby dSph galaxies with MAGIC: candidates, results and prospects. AIP conference proceedings. 191–196. 1 indexed citations
19.
Barrio, J. A., et al.. (2008). Pixel-by-pixel base representation in image classification from Cherenkov telescopes. 12–16.
20.
Nieto, D. & Angela Kunoth. (2006). Robust regression of scattered data with adaptive spline-wavelets. IEEE Transactions on Image Processing. 15(6). 1621–1632. 6 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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