Michele Sasdelli

498 total citations
17 papers, 228 citations indexed

About

Michele Sasdelli is a scholar working on Astronomy and Astrophysics, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Michele Sasdelli has authored 17 papers receiving a total of 228 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Astronomy and Astrophysics, 6 papers in Artificial Intelligence and 4 papers in Computer Vision and Pattern Recognition. Recurrent topics in Michele Sasdelli's work include Gamma-ray bursts and supernovae (7 papers), Stellar, planetary, and galactic studies (6 papers) and Astrophysical Phenomena and Observations (3 papers). Michele Sasdelli is often cited by papers focused on Gamma-ray bursts and supernovae (7 papers), Stellar, planetary, and galactic studies (6 papers) and Astrophysical Phenomena and Observations (3 papers). Michele Sasdelli collaborates with scholars based in Australia, United Kingdom and Germany. Michele Sasdelli's co-authors include P. A. Mazzali, Tat-Jun Chin, C. Ashall, S. Prentice, Gustavo Carneiro, Yee Wei Law, Bo Chen, Carlos Santiago, Catarina Barata and Jacinto C. Nascimento and has published in prestigious journals such as Monthly Notices of the Royal Astronomical Society, Pattern Recognition and Australasian Journal of Paramedicine.

In The Last Decade

Michele Sasdelli

16 papers receiving 217 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michele Sasdelli Australia 9 111 90 47 36 17 17 228
Joseph DePasquale United States 6 70 0.6× 39 0.4× 22 0.5× 26 0.7× 4 0.2× 19 157
Michaël Defferrard Switzerland 5 26 0.2× 39 0.4× 67 1.4× 16 0.4× 4 0.2× 7 181
Kam-Ching Leung United States 8 106 1.0× 45 0.5× 11 0.2× 9 0.3× 18 1.1× 34 229
José Enrique Ruiz Spain 9 151 1.4× 22 0.2× 11 0.2× 14 0.4× 82 4.8× 25 268
M.J. Fadili France 6 41 0.4× 17 0.2× 31 0.7× 19 0.5× 3 0.2× 14 184
John Timlin United States 10 244 2.2× 31 0.3× 61 1.3× 88 2.4× 35 2.1× 16 323
P. Huijse Chile 7 106 1.0× 36 0.4× 7 0.1× 7 0.2× 49 2.9× 24 213
Chenzhou Cui China 8 64 0.6× 27 0.3× 17 0.4× 5 0.1× 41 2.4× 49 188
John F. Wu United States 9 120 1.1× 25 0.3× 10 0.2× 15 0.4× 49 2.9× 24 211

Countries citing papers authored by Michele Sasdelli

Since Specialization
Citations

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

Fields of papers citing papers by Michele Sasdelli

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michele Sasdelli

This figure shows the co-authorship network connecting the top 25 collaborators of Michele Sasdelli. A scholar is included among the top collaborators of Michele Sasdelli 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 Michele Sasdelli. Michele Sasdelli 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.
Sasdelli, Michele, et al.. (2022). Globally optimal shape and spin pole determination with light-curve inversion. Monthly Notices of the Royal Astronomical Society. 513(1). 311–332. 2 indexed citations
2.
Chen, Bo, et al.. (2022). Physical Adversarial Attacks on an Aerial Imagery Object Detector. 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV). 3798–3808. 48 indexed citations
3.
Sasdelli, Michele, Gabriel Maicas, Stephan Lau, et al.. (2022). Mutual Information Neural Estimation for Unsupervised Multi-Modal Registration of Brain Images. 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). 121. 3510–3513. 4 indexed citations
4.
Doan, Anh-Dzung, Michele Sasdelli, David Suter, & Tat-Jun Chin. (2022). A Hybrid Quantum-Classical Algorithm for Robust Fitting. Australasian Journal of Paramedicine. 417–427. 16 indexed citations
5.
Taubenberger, S., M. Magee, M. Kromer, et al.. (2021). ASASSN-14lp: two possible solutions for the observed ultraviolet suppression. Monthly Notices of the Royal Astronomical Society. 506(1). 415–431. 3 indexed citations
6.
Sasdelli, Michele, Thalaiyasingam Ajanthan, Tat-Jun Chin, & Gustavo Carneiro. (2021). A Chaos Theory Approach to Understand Neural Network Optimization. Adelaide Research & Scholarship (AR&S) (University of Adelaide). 12. 1–10.
7.
Sasdelli, Michele & Tat-Jun Chin. (2021). Quantum Annealing Formulation for Binary Neural Networks. 1–10. 7 indexed citations
8.
Osborn, H. P., Megan Ansdell, Yani Ioannou, et al.. (2020). Rapid classification of TESS planet candidates with convolutional neural networks. Springer Link (Chiba Institute of Technology). 11 indexed citations
9.
Santiago, Carlos, Catarina Barata, Michele Sasdelli, Gustavo Carneiro, & Jacinto C. Nascimento. (2020). LOW: Training deep neural networks by learning optimal sample weights. Pattern Recognition. 110. 107585–107585. 26 indexed citations
10.
Felix, Rafael, Ben Harwood, Michele Sasdelli, & Gustavo Carneiro. (2019). Generalised zero-shot learning with domain classification in a joint semantic and visual space. Adelaide Research & Scholarship (AR&S) (University of Adelaide). 10 indexed citations
11.
Sidiropoulos, Panagiotis, et al.. (2019). Real-time Tracker with Fast Recovery from Target Loss. Adelaide Research & Scholarship (AR&S) (University of Adelaide). 1932–1936. 1 indexed citations
12.
Sasdelli, Michele, W. Hillebrandt, M. Kromer, et al.. (2016). A metric space for Type Ia supernova spectra: a new method to assess explosion scenarios. Monthly Notices of the Royal Astronomical Society. 466(4). 3784–3809. 5 indexed citations
13.
Ishida, Émille E. O., Michele Sasdelli, Ricardo Vilalta, et al.. (2016). Exploring the spectroscopic diversity of type Ia supernovae with Deep Learning and Unsupervised Clustering. Proceedings of the International Astronomical Union. 12(S325). 247–252. 2 indexed citations
14.
Sasdelli, Michele, Émille E. O. Ishida, W. Hillebrandt, et al.. (2016). Breaking the colour-reddening degeneracy in Type Ia supernovae. Monthly Notices of the Royal Astronomical Society. 460(1). 373–382. 8 indexed citations
15.
Ashall, C., P. A. Mazzali, Michele Sasdelli, & S. Prentice. (2016). Luminosity distributions of Type Ia supernovae. Monthly Notices of the Royal Astronomical Society. 460(4). 3529–3544. 36 indexed citations
16.
Sasdelli, Michele, Émille E. O. Ishida, Ricardo Vilalta, et al.. (2016). Exploring the spectroscopic diversity of Type Ia supernovae with dracula: a machine learning approach. Monthly Notices of the Royal Astronomical Society. 461(2). 2044–2059. 20 indexed citations
17.
Sasdelli, Michele, P. A. Mazzali, E. Pian, et al.. (2014). Abundance stratification in Type Ia supernovae – IV. The luminous, peculiar SN 1991T. Monthly Notices of the Royal Astronomical Society. 445(1). 711–725. 29 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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