D. Regruto

1.1k citations
86 papers · 817 indexed · h-index 17

D. Regruto

80 papers receiving 793 citations

Peers

D. Regruto
Comparison fields: 5 of 58
  • Control and Systems Engineering 671
  • Automotive Engineering 247
  • Statistics, Probability and Uncertainty 84
  • Civil and Structural Engineering 157
  • Numerical Analysis 23
Replace Kie Chung Cheung with:
Kie Chung Cheung Hong Kong
Emmanuel Prempain United Kingdom
Ningsu Luo Spain
Martin Herceg Slovakia
Bruce H. Wilson United States
Christoffer Sloth Denmark
Carlos E.T. Dórea Brazil
Miguel Ángel Naya Spain
A. Lecchini Belgium
Francisco González Spain
D. Regruto relative to Kie Chung Cheung Hong Kong Kie Chung Cheung's profile →
Citations per field
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Kie Chung Cheung · 1×
Citations per year

Countries citing papers authored by D. Regruto

Since Specialization
Citations

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

Fields of papers citing papers by D. Regruto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 18 scholars most cited alongside D. Regruto, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with D. Regruto Line = papers co-authored together D. Regruto links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20240
2 20241
3 20211
4 20191
5 20192
6 20181
7 20182
8 20177
9 20162
10
Model Predictive Control Education using a Rapid Prototyping Industrial Platform
20142
11 20141
12 201424
13 20126
14 201119
15 201153
16
Loop-shaping Design with Constant Magnitude Loci in Control Education*
20083
17 200899
18 20071
19 200740
20 200235

About D. Regruto

D. Regruto is a scholar working on Control and Systems Engineering, Statistics, Probability and Uncertainty, Automotive Engineering, Numerical Analysis and Civil and Structural Engineering, having authored 86 papers that have together received 817 indexed citations. Recurring topics across this work include Control Systems and Identification (55 papers), Fault Detection and Control Systems (41 papers), Advanced Control Systems Optimization (27 papers), Probabilistic and Robust Engineering Design (19 papers), Vehicle Dynamics and Control Systems (14 papers), Structural Health Monitoring Techniques (11 papers), Sparse and Compressive Sensing Techniques (7 papers) and Real-time simulation and control systems (7 papers). The work is most often cited by research in Control and Systems Engineering (671 citations), Automotive Engineering (247 citations), Statistics, Probability and Uncertainty (84 citations), Civil and Structural Engineering (157 citations) and Numerical Analysis (23 citations). D. Regruto has collaborated with scholars based in Italy, Netherlands and Switzerland. Frequent co-authors include V. Cerone, Dario Piga, M. Milanese, Mario Milanese, Mats Larsson, Sophie M. Fosson, Jean B. Lasserre, Michele Taragna, S. Malan and Edoardo Fadda. Their work appears in journals such as Automatica, IEEE Transactions on Automatic Control, International Journal of Robust and Nonlinear Control, IEEE Transactions on Control Systems Technology and Systems & Control Letters.

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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