Marco Levorato

4.0k total citations · 2 hit papers
160 papers, 2.6k citations indexed

About

Marco Levorato is a scholar working on Computer Networks and Communications, Electrical and Electronic Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Marco Levorato has authored 160 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 105 papers in Computer Networks and Communications, 87 papers in Electrical and Electronic Engineering and 28 papers in Computer Vision and Pattern Recognition. Recurrent topics in Marco Levorato's work include Cooperative Communication and Network Coding (38 papers), Advanced MIMO Systems Optimization (33 papers) and IoT and Edge/Fog Computing (32 papers). Marco Levorato is often cited by papers focused on Cooperative Communication and Network Coding (38 papers), Advanced MIMO Systems Optimization (33 papers) and IoT and Edge/Fog Computing (32 papers). Marco Levorato collaborates with scholars based in United States, Italy and Finland. Marco Levorato's co-authors include Michele Zorzi, Urbashi Mitra, Yoshitomo Matsubara, Andrea Goldsmith, Wei Xu, Derrick Wing Kwan Ng, Mérouane Debbah, Yonina C. Eldar, Zhaohui Yang and Sabur Baidya and has published in prestigious journals such as IEEE Transactions on Information Theory, IEEE Transactions on Signal Processing and IEEE Access.

In The Last Decade

Marco Levorato

145 papers receiving 2.5k 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.

Edge Learning for B5G Networks With Distributed Signal Processing: Semantic Communication, Edge Computing, and Wireless Sensing

2023 392 citations Wei Xu, Zhaohui Yang et al. IEEE Journal of Selected Topics in Signal Processing profile →
Split Computing and Early Exiting for Deep Learning Applications: Survey and Research Challenges

2022 145 citations Marco Levorato, Francesco Restuccia et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Marco Levorato United States	26	1.4k	1.3k	425	402	296	160	2.6k
Dirk Pesch Ireland	28	1.7k 1.3×	2.0k 1.5×	207 0.5×	323 0.8×	246 0.8×	190	3.0k
Ahmed Al‐Dubai United Kingdom	30	1.9k 1.4×	1.7k 1.3×	430 1.0×	363 0.9×	464 1.6×	160	3.4k
Muhammad Awais Javed Pakistan	24	1.4k 1.1×	1.8k 1.3×	381 0.9×	191 0.5×	326 1.1×	140	2.8k
Dan Wu China	33	1.7k 1.3×	1.9k 1.4×	578 1.4×	309 0.8×	286 1.0×	191	3.4k
Hongzi Zhu China	32	1.3k 1.0×	1.5k 1.1×	441 1.0×	342 0.9×	230 0.8×	118	2.8k
Fuqiang Liu China	24	1.2k 0.9×	1.6k 1.2×	227 0.5×	239 0.6×	161 0.5×	186	2.6k
Elias Yaacoub Qatar	25	1.5k 1.1×	1.9k 1.4×	294 0.7×	206 0.5×	374 1.3×	217	3.0k
Ghulam Abbas Pakistan	26	1.2k 0.9×	1.1k 0.8×	448 1.1×	182 0.5×	159 0.5×	147	2.3k
Xiangming Wen China	27	2.3k 1.7×	2.3k 1.7×	204 0.5×	346 0.9×	470 1.6×	367	3.6k
Eduardo Cerqueira Brazil	23	1.9k 1.4×	1.4k 1.0×	153 0.4×	389 1.0×	353 1.2×	241	2.7k

Countries citing papers authored by Marco Levorato

Since Specialization

Citations

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

Fields of papers citing papers by Marco Levorato

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Marco Levorato

This figure shows the co-authorship network connecting the top 25 collaborators of Marco Levorato. A scholar is included among the top collaborators of Marco Levorato 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 Marco Levorato. Marco Levorato 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

Singhal, Chetna, et al.. (2025). Distributing Inference Tasks Over Interconnected Systems Through Dynamic DNNs. SPIRE - Sciences Po Institutional REpository. 33(4). 1717–1730. 1 indexed citations

Levorato, Marco, et al.. (2024). NaviSplit: Dynamic Multi-Branch Split DNNs for Efficient Distributed Autonomous Navigation. 196–201.

Condia, Josie E. Rodriguez, et al.. (2024). Effective Application-level Error Modeling of Permanent Faults on AI Accelerators. 1–7.

Levorato, Marco, et al.. (2024). Edge Computing with Early Exiting for Adaptive Inference in Mobile Autonomous Systems. 2980–2985. 1 indexed citations

Faruque, Mohammad Abdullah Al, et al.. (2024). Distributed Radiance Fields for Edge Video Compression and Metaverse Integration in Autonomous Driving. 71–76. 1 indexed citations

Xu, Wei, Zhaohui Yang, Derrick Wing Kwan Ng, et al.. (2023). Edge Learning for B5G Networks With Distributed Signal Processing: Semantic Communication, Edge Computing, and Wireless Sensing. IEEE Journal of Selected Topics in Signal Processing. 17(1). 9–39. 392 indexed citations breakdown →

Levorato, Marco, et al.. (2023). Intrusion Detection Framework for Invasive FPV Drones Using Video Streaming Characteristics. ACM Transactions on Cyber-Physical Systems. 7(2). 1–29. 10 indexed citations

Chiasserini, Carla Fabiana, et al.. (2023). Invited Paper: Enhancing Privacy in Federated Learning via Early Exit. 1–5.

Jung, Soyi, Chanyoung Park, Marco Levorato, Jae‐Hyun Kim, & Joongheon Kim. (2023). Two-Stage Self-Adaptive Task Outsourcing Decision Making for Edge-Assisted Multi-UAV Networks. IEEE Transactions on Vehicular Technology. 1–16. 5 indexed citations

10.

Malandrino, Francesco, et al.. (2023). Tuning DNN Model Compression to Resource and Data Availability in Cooperative Training. IEEE/ACM Transactions on Networking. 32(2). 1600–1615. 1 indexed citations

11.

Levorato, Marco, et al.. (2022). Testudo: Collaborative Intelligence for Latency-Critical Autonomous Systems. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 42(6). 1770–1783. 7 indexed citations

12.

Guimarães, Leonardo, Eulanda M. dos Santos, Edleno Silva de Moura, et al.. (2021). A Small World Graph Approach for an Efficient Indoor Positioning System. Sensors. 21(15). 5013–5013. 3 indexed citations

13.

Jung, Soyi, Joongheon Kim, Marco Levorato, Carlos Cordeiro, & Jae‐Hyun Kim. (2021). Infrastructure-Assisted On-Driving Experience Sharing for Millimeter-Wave Connected Vehicles. IEEE Transactions on Vehicular Technology. 70(8). 7307–7321. 23 indexed citations

14.

Restuccia, Francesco, et al.. (2021). Federated Deep Reinforcement Learning for the Distributed Control of NextG Wireless Networks. 248–253. 29 indexed citations

15.

Choi, Hyun-Ho, Wonjae Shin, Marco Levorato, & H. Vincent Poor. (2019). Harvest-Or-Access: Slotted ALOHA for Wireless Powered Communication Networks. IEEE Transactions on Vehicular Technology. 68(11). 11394–11398. 17 indexed citations

16.

Faezi, Sina, et al.. (2017). Work-in-progress: driving behavior modeling and estimation for battery optimization in electric vehicles. 1 indexed citations

17.

Bozorgzadeh, Eli, et al.. (2015). A Unified Stochastic Model for Energy Management in Solar-Powered Embedded Systems. International Conference on Computer Aided Design. 621–626. 7 indexed citations

18.

O’Neill, Daniel, Marco Levorato, Andrea Goldsmith, & Urbashi Mitra. (2010). Residential Demand Response Using Reinforcement Learning. 409–414. 212 indexed citations

19.

Levorato, Marco, Paolo Casari, & Michele Zorzi. (2006). On the Performance of Access Strategies for MIMO Ad Hoc Networks.. Global Communications Conference. 6 indexed citations

20.

Casari, Paolo, Marco Levorato, & Michele Zorzi. (2005). Some Issues Concerning MAC Design in Ad Hoc Networks with MIMO Communications. Research Padua Archive (University of Padua). 3 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.

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