Massimo Vecchio

4.2k total citations · 3 hit papers
67 papers, 2.9k citations indexed

About

Massimo Vecchio is a scholar working on Computer Networks and Communications, Electrical and Electronic Engineering and Information Systems. According to data from OpenAlex, Massimo Vecchio has authored 67 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 46 papers in Computer Networks and Communications, 22 papers in Electrical and Electronic Engineering and 21 papers in Information Systems. Recurrent topics in Massimo Vecchio's work include IoT and Edge/Fog Computing (24 papers), Blockchain Technology Applications and Security (19 papers) and Energy Efficient Wireless Sensor Networks (18 papers). Massimo Vecchio is often cited by papers focused on IoT and Edge/Fog Computing (24 papers), Blockchain Technology Applications and Security (19 papers) and Energy Efficient Wireless Sensor Networks (18 papers). Massimo Vecchio collaborates with scholars based in Italy, Spain and France. Massimo Vecchio's co-authors include Miguel Pincheira, Francesco Marcelloni, Muhammad Salek Ali, Fabio Antonelli, Raffaele Giaffreda, Mubashir Husain Rehmani, Koustabh Dolui, Zaffar Haider Janjua, Mojtaba Eskandari and Roberto López-Valcarce and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Communications Surveys & Tutorials and IEEE Access.

In The Last Decade

Massimo Vecchio

63 papers receiving 2.7k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Applications of Blockchains in the Internet of Things: A Comprehensive Survey

2018 563 citations Muhammad Salek Ali, Massimo Vecchio et al. profile →
Blockchain-based traceability in Agri-Food supply chain management: A practical implementation

2018 553 citations Miguel Pincheira, Muhammad Salek Ali et al. profile →
Passban IDS: An Intelligent Anomaly-Based Intrusion Detection System for IoT Edge Devices

2020 278 citations Mojtaba Eskandari, Zaffar Haider Janjua et al. IEEE Internet of Things Journal profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Massimo Vecchio Italy	23	1.6k	1.2k	702	568	297	67	2.9k
Nicola Dragoni Denmark	23	1.6k 1.0×	1.0k 0.8×	661 0.9×	516 0.9×	502 1.7×	106	2.5k
Manuel Díáz Spain	17	1.5k 0.9×	1.4k 1.1×	378 0.5×	312 0.5×	85 0.3×	107	2.5k
Meng Shen China	32	2.3k 1.4×	2.2k 1.8×	2.1k 3.0×	825 1.5×	544 1.8×	132	4.7k
Cristian Martín Spain	11	1.1k 0.7×	1.3k 1.1×	290 0.4×	195 0.3×	80 0.3×	30	2.0k
Raffaele Giaffreda Italy	15	821 0.5×	796 0.7×	187 0.3×	268 0.5×	69 0.2×	37	1.6k
Krishna Kant United States	20	1.3k 0.8×	542 0.4×	286 0.4×	568 1.0×	68 0.2×	237	2.1k
Ahmed E. Kosba United States	13	733 0.4×	1.5k 1.2×	651 0.9×	723 1.3×	223 0.8×	20	2.3k
Rakesh Tripathi India	29	1.8k 1.1×	1.5k 1.3×	1.2k 1.7×	313 0.6×	612 2.1×	55	3.0k
Randhir Kumar India	22	1.2k 0.7×	1.3k 1.1×	771 1.1×	236 0.4×	324 1.1×	43	2.1k
Qinghua Lu Australia	24	789 0.5×	1.6k 1.3×	515 0.7×	115 0.2×	98 0.3×	115	2.3k

Countries citing papers authored by Massimo Vecchio

Since Specialization

Citations

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

Fields of papers citing papers by Massimo Vecchio

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Massimo Vecchio

This figure shows the co-authorship network connecting the top 25 collaborators of Massimo Vecchio. A scholar is included among the top collaborators of Massimo Vecchio 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 Massimo Vecchio. Massimo Vecchio is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Vecchio, Massimo, et al.. (2024). Towards Cost-Effective Robotic Solution for Agricultural Data Acquisition. Iris (University of Trento). 1–6. 1 indexed citations

Pincheira, Miguel, et al.. (2024). Fostering Precision Agriculture through Affordable 3D LiDAR Deskewing with EKF. 1–6.

Pincheira, Miguel, Elena Donini, Massimo Vecchio, & Raffaele Giaffreda. (2023). An Infrastructure Cost and Benefits Evaluation Framework for Blockchain-Based Applications. Systems. 11(4). 184–184. 2 indexed citations

Pincheira, Miguel, et al.. (2023). An Adaptable and Unsupervised TinyML Anomaly Detection System for Extreme Industrial Environments. Sensors. 23(4). 2344–2344. 44 indexed citations

Pincheira, Miguel, et al.. (2022). A TinyML approach to non-repudiable anomaly detection in extreme industrial environments. IRIS eCampus Telematic University (Università degli Studi eCampus). 397–402. 14 indexed citations

Pincheira, Miguel, et al.. (2022). Tiny-MLOps: a framework for orchestrating ML applications at the far edge of IoT systems. IRIS eCampus Telematic University (Università degli Studi eCampus). 1–8. 18 indexed citations

Vecchio, Massimo, Paolo Azzoni, Andreas Menychtas, Ilias Maglogiannis, & Alexander Felfernig. (2021). A Fully Open-Source Approach to Intelligent Edge Computing: AGILE’s Lesson. Sensors. 21(4). 1309–1309. 8 indexed citations

Vecchio, Massimo, et al.. (2021). Design and Implementation of an Energy-Efficient Weather Station for Wind Data Collection. Sensors. 21(11). 3831–3831. 12 indexed citations

Eskandari, Mojtaba, Zaffar Haider Janjua, Massimo Vecchio, & Fabio Antonelli. (2020). Passban IDS: An Intelligent Anomaly-Based Intrusion Detection System for IoT Edge Devices. IEEE Internet of Things Journal. 7(8). 6882–6897. 278 indexed citations breakdown →

10.

Ali, Muhammad Salek, Massimo Vecchio, & Fabio Antonelli. (2020). A Blockchain-Based Framework for IoT Data Monetization Services. The Computer Journal. 64(2). 195–210. 14 indexed citations

11.

Hussein, Ahmed Taha, Mahmoud Barhamgi, Massimo Vecchio, & Charith Perera. (2019). Crowdsourced Peer Learning Activity for Internet of Things Education: A Case Study. IRIS eCampus Telematic University (Università degli Studi eCampus). 9 indexed citations

12.

Janjua, Zaffar Haider, et al.. (2019). IRESE: An intelligent rare-event detection system using unsupervised learning on the IoT edge. Engineering Applications of Artificial Intelligence. 84. 41–50. 39 indexed citations

13.

Vecchio, Massimo, Andrey Malinin, & Mark Gales. (2018). Improved Auto-Marking Confidence for Spoken Language Assessment. 2. 957–963. 1 indexed citations

14.

Perrone, Giovanni, Massimo Vecchio, Riccardo Pecori, & Raffaele Giaffreda. (2017). The Day After Mirai: A Survey on MQTT Security Solutions After the Largest Cyber-attack Carried Out through an Army of IoT Devices. IRIS eCampus Telematic University (Università degli Studi eCampus). 57 indexed citations

15.

Vecchio, Massimo, et al.. (2015). Learn by Examples How to Link the Internet of Things and the Cloud Computing Paradigms: A Fully Working Proof of Concept. IRIS eCampus Telematic University (Università degli Studi eCampus). 806–810. 1 indexed citations

16.

Poncela, Javier, Panagiotis Vlacheas, Raffaele Giaffreda, et al.. (2014). Smart Cities via Data Aggregation. Wireless Personal Communications. 76(2). 149–168. 14 indexed citations

17.

Vecchio, Massimo, Aline Carneiro Viana, Artur Ziviani, & Roy Friedman. (2010). DEEP: Density-based proactive data dissemination protocol for wireless sensor networks with uncontrolled sink mobility. Computer Communications. 33(8). 929–939. 33 indexed citations

18.

Marcelloni, Francesco & Massimo Vecchio. (2009). An Efficient Lossless Compression Algorithm for Tiny Nodes of Monitoring Wireless Sensor Networks. The Computer Journal. 52(8). 969–987. 133 indexed citations

19.

Lazzerini, Beatrice, Francesco Marcelloni, & Massimo Vecchio. (2009). A multi-objective evolutionary approach to image quality/compression trade-off in JPEG baseline algorithm. Applied Soft Computing. 10(2). 548–561. 26 indexed citations

20.

Marcelloni, Francesco, et al.. (2007). Reducing Power Consumption in Wireless Sensor Networks Using a Novel Approach to Data Aggregation. The Computer Journal. 51(2). 227–239. 52 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.

Explore authors with similar magnitude of impact