Roberto Pellungrini
Impact in
- Health Informatics top 10%
- Artificial Intelligence in Healthcare and Education
- Transportation top 5%
- Human Mobility and Location-Based Analysis
- Urban Transport and Accessibility
- Transportation Planning and Optimization
Papers in
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- Privacy-Preserving Technologies in Data 5
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- Human Mobility and Location-Based Analysis 6
- Co-authors
- Luca Pappalardo (6 shared papers)Filippo Simini (4 shared papers)Gianni Barlacchi (3 shared papers)Anna Monreale (8 shared papers)Francesca Pratesi (2 shared papers)Andrea Beretta (1 shared paper)Fosca Giannotti (2 shared papers)Salvatore Rinzivillo (1 shared paper)
In The Last Decade
Roberto Pellungrini
14 papers receiving 160 citations
Peers
Comparison fields: 5 of 57
- Health Informatics 15
- Transportation 75
- Artificial Intelligence 43
- Signal Processing 13
- Building and Construction 16
Countries citing papers authored by Roberto Pellungrini
This map shows the geographic impact of Roberto Pellungrini'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 Roberto Pellungrini with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Roberto Pellungrini more than expected).
Fields of papers citing papers by Roberto Pellungrini
This network shows the impact of papers produced by Roberto Pellungrini. 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 Roberto Pellungrini. The network helps show where Roberto Pellungrini may publish in the future.
Co-authors
The 20 scholars most cited alongside Roberto Pellungrini, 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 | 2022 | 42 | |
| 2 | 2017 | 35 | |
| 3 | 2024 | 29 | |
| 4 | 2019 | 11 | |
| 5 | 2020 | 10 | |
| 6 | 2023 | 9 | |
| 7 | 2023 | 9 | |
| 8 | 2024 | 5 | |
| 9 | 2019 | 3 | |
| 10 | 2025 | 3 | |
| 11 | 2019 | 2 | |
| 12 | 2024 | 1 | |
| 13 | 2025 | 1 | |
| 14 | 2024 | 1 | |
| 15 | 2025 | 0 | |
| 16 | 2025 | 0 | |
| 17 | 2025 | 0 | |
| 18 | 2024 | 0 | |
| 19 | 2024 | 0 |
About Roberto Pellungrini
Roberto Pellungrini is a scholar working on Artificial Intelligence, Transportation, Health Informatics, Radiology, Nuclear Medicine and Imaging and Computer Networks and Communications, having authored 19 papers that have together received 161 indexed citations. Recurring topics across this work include Human Mobility and Location-Based Analysis (6 papers), Privacy-Preserving Technologies in Data (5 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Artificial Intelligence in Healthcare and Education (3 papers), Pancreatic and Hepatic Oncology Research (2 papers), Data-Driven Disease Surveillance (2 papers), Traffic Prediction and Management Techniques (2 papers) and Vehicular Ad Hoc Networks (VANETs) (2 papers). The work is most often cited by research in Health Informatics (15 citations), Transportation (75 citations), Artificial Intelligence (43 citations), Signal Processing (13 citations) and Building and Construction (16 citations). Roberto Pellungrini has collaborated with scholars based in Italy, Germany and Brazil. Frequent co-authors include Luca Pappalardo, Filippo Simini, Gianni Barlacchi, Anna Monreale, Francesca Pratesi, Andrea Beretta, Fosca Giannotti, Salvatore Rinzivillo, Daniele Campa and Federico Canzian. Their work appears in journals such as European Journal of Cancer, Digestive and Liver Disease, IEEE Transactions on Intelligent Transportation Systems, Applied Sciences and United European Gastroenterology Journal.
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.