Giovanni Ponti

799 total citations
27 papers, 316 citations indexed

About

Giovanni Ponti is a scholar working on Signal Processing, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Giovanni Ponti has authored 27 papers receiving a total of 316 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Signal Processing, 10 papers in Artificial Intelligence and 6 papers in Computer Networks and Communications. Recurrent topics in Giovanni Ponti's work include Data Management and Algorithms (7 papers), Advanced Clustering Algorithms Research (5 papers) and Metabolomics and Mass Spectrometry Studies (4 papers). Giovanni Ponti is often cited by papers focused on Data Management and Algorithms (7 papers), Advanced Clustering Algorithms Research (5 papers) and Metabolomics and Mass Spectrometry Studies (4 papers). Giovanni Ponti collaborates with scholars based in Italy, Spain and Indonesia. Giovanni Ponti's co-authors include Andrea Tagarelli, Francesco Gullo, Sergio Greco, S. Migliori, G. Bracco, Guido Guarnieri, Filippo Palombi, Piero Procacci, Fiorenzo Ambrosino and F. Iannone and has published in prestigious journals such as Pattern Recognition, Information Sciences and Physica A Statistical Mechanics and its Applications.

In The Last Decade

Giovanni Ponti

24 papers receiving 299 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Giovanni Ponti Italy 10 112 100 45 45 39 27 316
Feng Luo China 9 85 0.8× 53 0.5× 31 0.7× 16 0.4× 37 0.9× 40 329
Peng Peng China 12 139 1.2× 59 0.6× 38 0.8× 24 0.5× 114 2.9× 41 395
Hongxing He Australia 10 278 2.5× 52 0.5× 19 0.4× 58 1.3× 36 0.9× 30 542
Siqi Chen China 9 90 0.8× 15 0.1× 16 0.4× 21 0.5× 31 0.8× 29 240
Wayne Pullan Australia 14 181 1.6× 25 0.3× 38 0.8× 52 1.2× 27 0.7× 30 615
Fang Wei Austria 10 109 1.0× 114 1.1× 34 0.8× 16 0.4× 57 1.5× 25 334
Jaemin Yoo South Korea 10 149 1.3× 20 0.2× 32 0.7× 10 0.2× 77 2.0× 28 294
Florian W. Beil Germany 8 267 2.4× 75 0.8× 42 0.9× 17 0.4× 42 1.1× 13 439
Zhao‐Rong Lai China 14 86 0.8× 58 0.6× 28 0.6× 20 0.4× 230 5.9× 32 466
Weiguo Li China 11 110 1.0× 14 0.1× 29 0.6× 19 0.4× 34 0.9× 52 462

Countries citing papers authored by Giovanni Ponti

Since Specialization
Citations

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

Fields of papers citing papers by Giovanni Ponti

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Giovanni Ponti

This figure shows the co-authorship network connecting the top 25 collaborators of Giovanni Ponti. A scholar is included among the top collaborators of Giovanni Ponti 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 Giovanni Ponti. Giovanni Ponti 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.
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Iannone, F., Fiorenzo Ambrosino, G. Bracco, et al.. (2019). CRESCO ENEA HPC clusters: a working example of a multifabric GPFS Spectrum Scale layout. Florence Research (University of Florence). 1051–1052. 95 indexed citations
3.
Gullo, Francesco, Giovanni Ponti, Andrea Tagarelli, & Sergio Greco. (2017). An information-theoretic approach to hierarchical clustering of uncertain data. Information Sciences. 402. 199–215. 22 indexed citations
4.
Migliori, S., et al.. (2017). A Staging Storage Sharing System For Data Handling In A Multisite Scientific Organization. Zenodo (CERN European Organization for Nuclear Research). 2 indexed citations
5.
Ponti, Giovanni. (2016). A probabilistic approach for financial IoT data. ENEA Open Archive (National Agency for New Technologies, Energy and Sustainable Economic Development). 73–74. 3 indexed citations
6.
Cuomo, Salvatore, Pasquale De Michele, Ardelio Galletti, & Giovanni Ponti. (2015). Visiting Styles in an Art Exhibition Supported by a Digital Fruition System. ENEA Open Archive (National Agency for New Technologies, Energy and Sustainable Economic Development). 9. 775–781. 11 indexed citations
7.
Cuomo, Salvatore, Pasquale De Michele, Ardelio Galletti, F. Pane, & Giovanni Ponti. (2015). Visitor Dynamics in a Cultural Heritage Scenario. 337–343. 9 indexed citations
8.
Cuomo, Salvatore, Pasquale De Michele, Ardelio Galletti, & Giovanni Ponti. (2015). Parallel Tools for Simulating the Depolarization Block on a Neural Model. Procedia Computer Science. 51. 745–754. 2 indexed citations
9.
Cuomo, Salvatore, Pasquale De Michele, Ardelio Galletti, & Giovanni Ponti. (2014). A Biologically Inspired Model for Analyzing Behaviours in Social Network Community and Cultural Heritage Scenario. ENEA Open Archive (National Agency for New Technologies, Energy and Sustainable Economic Development). 37. 485–492. 4 indexed citations
10.
11.
Gullo, Francesco, Giovanni Ponti, & Andrea Tagarelli. (2012). Minimizing the variance of cluster mixture models for clustering uncertain objects. Statistical Analysis and Data Mining The ASA Data Science Journal. 6(2). 116–135. 9 indexed citations
12.
Gullo, Francesco, Giovanni Ponti, Andrea Tagarelli, Giuseppe Tradigo, & Pierangelo Veltri. (2011). A time series approach for clustering mass spectrometry data. Journal of Computational Science. 3(5). 344–355. 24 indexed citations
13.
Greco, Sergio, Francesco Gullo, Giovanni Ponti, & Andrea Tagarelli. (2011). Collaborative clustering of XML documents. Journal of Computer and System Sciences. 77(6). 988–1008. 3 indexed citations
14.
Kovářík, Jaromír, et al.. (2011). Prosocial norms and degree heterogeneity in social networks. Physica A Statistical Mechanics and its Applications. 391(3). 849–853.
15.
Gullo, Francesco, Giovanni Ponti, Andrea Tagarelli, Giuseppe Tradigo, & Pierangelo Veltri. (2009). MaSDA: A system for analyzing mass spectrometry data. Computer Methods and Programs in Biomedicine. 95(2). S12–S21. 2 indexed citations
16.
Gullo, Francesco, et al.. (2009). Low-voltage electricity customer profiling based on load data clustering. 330–330. 14 indexed citations
17.
Gullo, Francesco, Giovanni Ponti, Andrea Tagarelli, Giuseppe Tradigo, & Pierangelo Veltri. (2009). Hierarchical clustering of microarray data with probe-level uncertainty. 1–6. 1 indexed citations
18.
Gullo, Francesco, Giovanni Ponti, Andrea Tagarelli, & Sergio Greco. (2008). A Hierarchical Algorithm for Clustering Uncertain Data via an Information-Theoretic Approach. 821–826. 24 indexed citations
19.
Gullo, Francesco, Giovanni Ponti, Andrea Tagarelli, & Sergio Greco. (2007). Accurate and Fast Similarity Detection in Time Series.. SEBD. 172–183. 1 indexed citations
20.
Gullo, Francesco, Giovanni Ponti, Andrea Tagarelli, Giuseppe Tradigo, & Pierangelo Veltri. (2007). A Time Series Based Approach for Classifying Mass Spectrometry Data. IRIS eCampus Telematic University (Università degli Studi eCampus). 412–420. 3 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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