Matteo Terzi
- Artificial Intelligence top 10%
- Industrial and Manufacturing Engineering top 5%
- Control and Systems Engineering top 10%
- Computer Networks and Communications
- Electrical and Electronic Engineering
- Co-authors
- Gian Antonio SustoAlessandro BeghiChiara MasieroSimone Del FaveroClaudio CobelliAngelo CenedesePratik ChaudhariAndrea Schirru
- Topics
- Anomaly Detection Techniques and Applications (9 papers)Context-Aware Activity Recognition Systems (4 papers)Adversarial Robustness in Machine Learning (4 papers)
- Cited by
- Industrial and Manufacturing EngineeringStatistics, Probability and UncertaintyArtificial Intelligence
- Partner nations
- ItalySwitzerlandUnited States
In The Last Decade
Matteo Terzi
16 papers receiving 286 citations
Peers
Comparison fields: 5 of 72
- Artificial Intelligence 134
- Industrial and Manufacturing Engineering 78
- Control and Systems Engineering 68
- Computer Networks and Communications 40
- Electrical and Electronic Engineering 32
Countries citing papers authored by Matteo Terzi
This map shows the geographic impact of Matteo Terzi'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 Matteo Terzi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matteo Terzi more than expected).
Fields of papers citing papers by Matteo Terzi
This network shows the impact of papers produced by Matteo Terzi. 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 Matteo Terzi. The network helps show where Matteo Terzi may publish in the future.
Co-authorship network of co-authors of Matteo Terzi
This figure shows the co-authorship network connecting the top 25 collaborators of Matteo Terzi. A scholar is included among the top collaborators of Matteo Terzi 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 Matteo Terzi. Matteo Terzi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 0 | |
| 3 | 64 | |
| 4 | 12 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | 18 | |
| 8 | 47 | |
| 9 | 52 | |
| 10 | 5 | |
| 11 | 4 | |
| 12 | 14 | |
| 13 | 5 | |
| 14 | 60 | |
| 15 | 4 | |
| 16 | Human Activity Recognition with Wearable Devices: A Symbolic Approach. | 1 |
| 17 | Compensation system for high range mean sea level variations designed for wave power plants. Mechanical design and hydrodynamic modelling | 1 |
About Matteo Terzi
Matteo Terzi is a scholar working on Human-Computer Interaction, Computer Vision and Pattern Recognition and Media Technology, having authored 17 papers that have together received 292 indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (9 papers), Context-Aware Activity Recognition Systems (4 papers) and Adversarial Robustness in Machine Learning (4 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (78 citations), Statistics, Probability and Uncertainty (30 citations) and Artificial Intelligence (134 citations). Matteo Terzi has collaborated with scholars based in Italy, Switzerland and United States. Frequent co-authors include Gian Antonio Susto, Alessandro Beghi, Chiara Masiero, Simone Del Favero, Claudio Cobelli, Angelo Cenedese, Pratik Chaudhari, Andrea Schirru, Simone Pampuri and Ruggero Carli. Their work appears in journals such as Information Sciences, Neurocomputing and IEEE Transactions on Control Systems Technology.
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.