Michele Tumminello
- Statistical and Nonlinear Physics top 0.5%
- Complex Network Analysis Techniques 17
- Opinion Dynamics and Social Influence 9
- Finance top 1%
- Financial Risk and Volatility Modeling 10
- Economics and Econometrics top 0.5%
- Complex Systems and Time Series Analysis 20
- Signal Processing top 5%
- Time Series Analysis and Forecasting 5
-
- Quantum Mechanics and Applications 5
-
- Quantum Information and Cryptography 5
-
- Bioinformatics and Genomic Networks 4
- Co-authors
- Rosario N. MantegnaFabrizio LilloTiziana Di MatteoTomaso AsteSalvatore MiccichèDror Y. KenettEshel Ben‐JacobGitit Gur-Gershgoren
- Journals
- Proceedings of the National Academy of Sciences (1 paper)PLoS ONE (5 papers)Scientific Reports (3 papers)
- Partner nations
- ItalyUnited StatesFinland
In The Last Decade
Michele Tumminello
58 papers receiving 2.1k citations
Hit Papers
Peers
Comparison fields: 5 of 151
- Statistical and Nonlinear Physics 893
- Finance 579
- Economics and Econometrics 1.4k
- Management Science and Operations Research 194
- Signal Processing 128
Countries citing papers authored by Michele Tumminello
This map shows the geographic impact of Michele Tumminello'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 Tumminello with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michele Tumminello more than expected).
Fields of papers citing papers by Michele Tumminello
This network shows the impact of papers produced by Michele Tumminello. 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 Tumminello. The network helps show where Michele Tumminello may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Michele Tumminello, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2024 | 1 | |
| 3 | 2023 | 11 | |
| 4 | 2022 | 3 | |
| 5 | 2021 | 13 | |
| 6 | 2020 | 31 | |
| 7 | 2020 | 10 | |
| 8 | 2019 | 3 | |
| 9 | 2019 | 21 | |
| 10 | 2017 | 18 | |
| 11 | 2016 | 3 | |
| 12 | 2015 | 26 | |
| 13 | 2015 | 1 | |
| 14 | 2014 | 33 | |
| 15 | 2011 | 34 | |
| 16 | 2011 | 22 | |
| 17 | 2010 | 254 | |
| 18 | 2009 | 1 | |
| 19 | 2007 | 53 | |
| 20 | Hierarchically nested time series models from dendrograms | 2005 | 2 |
About Michele Tumminello
Michele Tumminello is a scholar working on Finance, Statistical and Nonlinear Physics and Economics and Econometrics, having authored 60 papers that have together received 2.2k indexed citations. Recurring topics across this work include Complex Systems and Time Series Analysis (20 papers), Complex Network Analysis Techniques (17 papers), Financial Risk and Volatility Modeling (10 papers), Opinion Dynamics and Social Influence (9 papers), Time Series Analysis and Forecasting (5 papers), Quantum Mechanics and Applications (5 papers), Quantum Information and Cryptography (5 papers) and Bioinformatics and Genomic Networks (4 papers). The work is most often cited by research in Statistical and Nonlinear Physics (893 citations), Finance (579 citations) and Economics and Econometrics (1.4k citations). Michele Tumminello has collaborated with scholars based in Italy, United States and Finland. Frequent co-authors include Rosario N. Mantegna, Fabrizio Lillo, Tiziana Di Matteo, Tomaso Aste, Salvatore Miccichè, Dror Y. Kenett, Eshel Ben‐Jacob, Gitit Gur-Gershgoren, Asaf Madi and Jyrki Piilo. Their work appears in journals such as Proceedings of the National Academy of Sciences, PLoS ONE and Scientific Reports.
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.