Fabio Stella
Impact in
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- Advanced Bandit Algorithms Research
- Data Quality and Management
- Artificial Intelligence top 5%
- Bayesian Modeling and Causal Inference
- Topic Modeling
- Advanced Text Analysis Techniques
Papers in
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- Bayesian Modeling and Causal Inference 15
- Topic Modeling 8
- Data Stream Mining Techniques 6
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- Advanced Bandit Algorithms Research 8
- Risk and Portfolio Optimization 6
- Co-authors
- Markus Zanker (13 shared papers)Antonio Salmerón (1 shared paper)Mauro Scanagatta (1 shared paper)Alexei A. Gaivoronski (5 shared papers)Francesca Arcelli Fontana (2 shared papers)D. Magatti (4 shared papers)Marco Zanoni (1 shared paper)Elif Özkırımlı (1 shared paper)
- Journals
- International Journal of Approximate Reasoning (3 papers)Scientific Reports (2 papers)Annals of Operations Research (2 papers)Quantitative Finance (2 papers)Neurocomputing (2 papers)
- Partner nations
- ItalyAustriaSwitzerland
In The Last Decade
Fabio Stella
67 papers receiving 945 citations
Peers
Comparison fields: 5 of 140
- Management Science and Operations Research 220
- Artificial Intelligence 469
- Information Systems 220
- Software 28
- Finance 73
Countries citing papers authored by Fabio Stella
This map shows the geographic impact of Fabio Stella'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 Fabio Stella with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fabio Stella more than expected).
Fields of papers citing papers by Fabio Stella
This network shows the impact of papers produced by Fabio Stella. 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 Fabio Stella. The network helps show where Fabio Stella may publish in the future.
Co-authors
The 25 scholars most cited alongside Fabio Stella, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 72 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 156 | |
| 2 | 2015 | 70 | |
| 3 | 2015 | 66 | |
| 4 | 2000 | 47 | |
| 5 | 2022 | 41 | |
| 6 | 2009 | 41 | |
| 7 | 2011 | 39 | |
| 8 | 2016 | 38 | |
| 9 | 2011 | 33 | |
| 10 | 2011 | 31 | |
| 11 | 2017 | 30 | |
| 12 | 2003 | 27 | |
| 13 | 2013 | 27 | |
| 14 | 2012 | 25 | |
| 15 | 2019 | 21 | |
| 16 | 2014 | 19 | |
| 17 | 2021 | 19 | |
| 18 | 1997 | 18 | |
| 19 | 2023 | 14 | |
| 20 | 2007 | 13 |
About Fabio Stella
Fabio Stella is a scholar working on Artificial Intelligence, Management Science and Operations Research, Information Systems, Signal Processing and Molecular Biology, having authored 72 papers that have together received 996 indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (15 papers), Advanced Bandit Algorithms Research (8 papers), Topic Modeling (8 papers), Data Stream Mining Techniques (6 papers), Risk and Portfolio Optimization (6 papers), Stochastic processes and financial applications (5 papers), Time Series Analysis and Forecasting (5 papers) and Recommender Systems and Techniques (5 papers). The work is most often cited by research in Management Science and Operations Research (220 citations), Artificial Intelligence (469 citations), Information Systems (220 citations), Software (28 citations) and Finance (73 citations). Fabio Stella has collaborated with scholars based in Italy, Austria and Switzerland. Frequent co-authors include Markus Zanker, Antonio Salmerón, Mauro Scanagatta, Alexei A. Gaivoronski, Francesca Arcelli Fontana, D. Magatti, Marco Zanoni, Elif Özkırımlı, Y. A. Amer and Davide Luciani. Their work appears in journals such as International Journal of Approximate Reasoning, Scientific Reports, Annals of Operations Research, Quantitative Finance and Neurocomputing.
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.