Matteo Saveriano

1.2k total citations · 1 hit paper
65 papers, 609 citations indexed

About

Matteo Saveriano is a scholar working on Control and Systems Engineering, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Matteo Saveriano has authored 65 papers receiving a total of 609 indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Control and Systems Engineering, 26 papers in Computer Vision and Pattern Recognition and 16 papers in Artificial Intelligence. Recurrent topics in Matteo Saveriano's work include Robot Manipulation and Learning (33 papers), Robotic Mechanisms and Dynamics (13 papers) and Human Pose and Action Recognition (11 papers). Matteo Saveriano is often cited by papers focused on Robot Manipulation and Learning (33 papers), Robotic Mechanisms and Dynamics (13 papers) and Human Pose and Action Recognition (11 papers). Matteo Saveriano collaborates with scholars based in Italy, Germany and Austria. Matteo Saveriano's co-authors include Dongheui Lee, Fares J. Abu‐Dakka, Luka Peternel, Aljaž Kramberger, Riccardo Caccavale, Alberto Finzi, Pietro Falco, Raffaele Soloperto, Silvia Rossi and Justus Piater and has published in prestigious journals such as PLoS ONE, Automatica and IEEE Access.

In The Last Decade

Matteo Saveriano

58 papers receiving 599 citations

Hit Papers

Dynamic movement primitives in robotics: A tutorial survey 2023 2026 2024 2025 2023 25 50 75 100
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.

  1. Dynamic movement primitives in robotics: A tutorial survey
    2023 100 citations Matteo Saveriano, Fares J. Abu‐Dakka et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Matteo Saveriano Italy 13 391 191 161 158 75 65 609
João Silvério Italy 13 511 1.3× 123 0.6× 215 1.3× 184 1.2× 98 1.3× 31 638
Zoe McCarthy United States 10 434 1.1× 220 1.2× 161 1.0× 188 1.2× 135 1.8× 13 668
Rudolf Lioutikov Germany 15 471 1.2× 184 1.0× 271 1.7× 155 1.0× 59 0.8× 24 661
Daniel Kappler Germany 12 393 1.0× 198 1.0× 168 1.0× 189 1.2× 61 0.8× 20 555
Harish Ravichandar United States 12 446 1.1× 165 0.9× 253 1.6× 138 0.9× 108 1.4× 34 721
Balakumar Sundaralingam United States 12 345 0.9× 206 1.1× 107 0.7× 129 0.8× 54 0.7× 17 482
Alexis Maldonado Germany 13 243 0.6× 197 1.0× 135 0.8× 102 0.6× 83 1.1× 20 516
Karinne Ramírez-Amaro Germany 16 332 0.8× 263 1.4× 196 1.2× 108 0.7× 65 0.9× 37 627
Alexandros Paraschos Germany 12 506 1.3× 162 0.8× 321 2.0× 183 1.2× 75 1.0× 19 658
Soshi Iba United States 12 234 0.6× 165 0.9× 80 0.5× 79 0.5× 53 0.7× 24 424

Countries citing papers authored by Matteo Saveriano

Since Specialization
Citations

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

Fields of papers citing papers by Matteo Saveriano

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matteo Saveriano

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

All Works

20 of 20 papers shown
1.
Lamon, Edoardo, et al.. (2025). Surface defect identification using Bayesian filtering on a 3D mesh. Measurement Sensors. 38. 101849–101849.
2.
Paolillo, Antonio, et al.. (2025). Imitation learning-based Direct Visual Servoing using the large projection formulation. Robotics and Autonomous Systems. 190. 104971–104971.
3.
Braun, Philipp, et al.. (2024). Static anti-windup with shifted equilibria applied to a Segway-like vehicle. Automatica. 169. 111830–111830. 1 indexed citations
4.
Abu‐Dakka, Fares J., Matteo Saveriano, & Ville Kyrki. (2024). A unified formulation of geometry-aware discrete dynamic movement primitives. Neurocomputing. 598. 128056–128056. 4 indexed citations
5.
Lamon, Edoardo, et al.. (2024). A Passive Variable Impedance Control Strategy with Viscoelastic Parameters Estimation of Soft Tissues for Safe Ultrasonography. Institutional Research Information System (Università degli Studi di Trento). 1298–1304. 3 indexed citations
6.
Saveriano, Matteo, et al.. (2024). Receding-Constraint Model Predictive Control using a Learned Approximate Control-Invariant Set. Institutional Research Information System (Università degli Studi di Trento). 11626–11632.
7.
Saveriano, Matteo, et al.. (2024). Neutrons Sensitivity of Deep Reinforcement Learning Policies on EdgeAI Accelerators. IEEE Transactions on Nuclear Science. 71(8). 1480–1486. 3 indexed citations
8.
Makridis, Michail, et al.. (2024). Antifragility in complex dynamical systems. Iris (University of Trento). 1(1). 5 indexed citations
9.
Saveriano, Matteo, et al.. (2024). Safe Execution of Learned Orientation Skills with Conic Control Barrier Functions. 13376–13382. 2 indexed citations
10.
Lamon, Edoardo, et al.. (2024). Elasticity Measurements of Expanded Foams Using a Collaborative Robotic Arm. Institutional Research Information System (Università degli Studi di Trento). 3 indexed citations
11.
Lamon, Edoardo, et al.. (2024). Towards Robotised Palpation for Cancer Detection through Online Tissue Viscoelastic Characterisation with a Collaborative Robotic Arm. Institutional Research Information System (Università degli Studi di Trento). 2380–2386. 1 indexed citations
12.
Lamon, Edoardo, et al.. (2024). A Passivity-Based Variable Impedance Controller for Incremental Learning of Periodic Interactive Tasks. Institutional Research Information System (Università degli Studi di Trento). 2604–2609. 1 indexed citations
13.
Saveriano, Matteo, et al.. (2024). A Novel Safety-Aware Energy Tank Formulation Based on Control Barrier Functions. IEEE Robotics and Automation Letters. 9(6). 5206–5213. 3 indexed citations
14.
Saveriano, Matteo, et al.. (2023). Continual learning from demonstration of robotics skills. Robotics and Autonomous Systems. 165. 104427–104427. 12 indexed citations
15.
Johannsen, L., et al.. (2020). Robotic Light Touch Assists Human Balance Control During Maximum Forward Reaching. Human Factors The Journal of the Human Factors and Ergonomics Society. 64(3). 514–526. 1 indexed citations
16.
Agostini, Alejandro, Matteo Saveriano, Dongheui Lee, & Justus Piater. (2020). Manipulation Planning Using Object-Centered Predicates and Hierarchical Decomposition of Contextual Actions. IEEE Robotics and Automation Letters. 5(4). 5629–5636. 9 indexed citations
17.
Abu‐Dakka, Fares J. & Matteo Saveriano. (2020). Variable Impedance Control and Learning—A Review. Frontiers in Robotics and AI. 7. 590681–590681. 5 indexed citations
18.
Saveriano, Matteo, et al.. (2016). The Role of Coupling Terms in Variable Impedance Policies Learning. 6 indexed citations
19.
Saveriano, Matteo, et al.. (2015). Incremental kinesthetic teaching of end-effector and null-space motion primitives. Iris (University of Trento). 3570–3575. 34 indexed citations
20.
Saveriano, Matteo & Dongheui Lee. (2013). Point cloud based dynamical system modulation for reactive avoidance of convex and concave obstacles. Institutional Research Information System (Università degli Studi di Trento). 5380–5387. 21 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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