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Riccardo Scattolini

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Electronics and Electrical Engineering 53 2368 2269 57 56 314 12910

Riccardo Scattolini publications per year

The chart shows the history of publications by Riccardo Scattolini between 1981 and 2025, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Riccardo Scattolini published across 45 years, from 1981 to 2025, averaging 7.8 papers a year. Output peaked at 17 publications in 2021. 21 of the 350 publications appeared in the last two years.

No. of publications
5 10 15
Bar chart. Horizontal axis: year, 1981 to 2025. Vertical axis: number of publications, 0 to 17. Peak 17 publications in 2021. 1981: 2 publications 1982: 1 publication 1983: 4 publications 1984: 3 publications 1985: 3 publications 1986: 4 publications 1987: 4 publications 1988: 3 publications 1989: 5 publications 1990: 5 publications 1991: 8 publications 1992: 6 publications 1993: 4 publications 1994: 5 publications 1995: 7 publications 1996: 13 publications 1997: 6 publications 1998: 5 publications 1999: 7 publications 2000: 7 publications 2001: 10 publications 2002: 9 publications 2003: 3 publications 2004: 13 publications 2005: 7 publications 2006: 6 publications 2007: 12 publications 2008: 10 publications 2009: 12 publications 2010: 9 publications 2011: 7 publications 2012: 12 publications 2013: 10 publications 2014: 11 publications 2015: 9 publications 2016: 10 publications 2017: 5 publications 2018: 13 publications 2019: 13 publications 2020: 13 publications 2021: 17 publications 2022: 6 publications 2023: 10 publications 2024: 16 publications 2025: 5 publications
1981 2025

350 publications in total across all disciplines

View publications per year as a table
Riccardo Scattolini: publications per year, 1981 to 2025
Year Publications
1981 2
1982 1
1983 4
1984 3
1985 3
1986 4
1987 4
1988 3
1989 5
1990 5
1991 8
1992 6
1993 4
1994 5
1995 7
1996 13
1997 6
1998 5
1999 7
2000 7
2001 10
2002 9
2003 3
2004 13
2005 7
2006 6
2007 12
2008 10
2009 12
2010 9
2011 7
2012 12
2013 10
2014 11
2015 9
2016 10
2017 5
2018 13
2019 13
2020 13
2021 17
2022 6
2023 10
2024 16
2025 5
Total 350
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Riccardo Scattolini publication distribution in Electronics and Electrical Engineering in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Electronics and Electrical Engineering in 2026. The highlighted bar marks where Riccardo Scattolini sits on this spectrum.

No. of scientists
100 200 300 400
Bar chart with 53 bars. Horizontal axis: publications, 34–53 to 1,065+. Vertical axis: number of scientists, 0 to 445. Most scientists, 445, have 174–193 publications. The last bar groups every scientist with 1,065 publications or more. The highlighted bar, 314–333 publications, is where this scientist sits. 34–53 publications: 24 scientists 54–73 publications: 52 scientists 74–93 publications: 114 scientists 94–113 publications: 203 scientists 114–133 publications: 269 scientists 134–153 publications: 355 scientists 154–173 publications: 403 scientists 174–193 publications: 445 scientists 194–213 publications: 430 scientists 214–233 publications: 431 scientists 234–253 publications: 399 scientists 254–273 publications: 366 scientists 274–293 publications: 335 scientists 294–313 publications: 300 scientists 314–333 publications: 276 scientists 334–353 publications: 250 scientists 354–373 publications: 214 scientists 374–393 publications: 187 scientists 394–413 publications: 152 scientists 414–433 publications: 169 scientists 434–453 publications: 147 scientists 454–473 publications: 111 scientists 474–493 publications: 117 scientists 494–513 publications: 103 scientists 514–533 publications: 99 scientists 534–553 publications: 92 scientists 554–573 publications: 75 scientists 574–593 publications: 58 scientists 594–613 publications: 69 scientists 614–633 publications: 50 scientists 634–653 publications: 62 scientists 654–673 publications: 54 scientists 674–693 publications: 44 scientists 694–713 publications: 37 scientists 714–733 publications: 28 scientists 734–753 publications: 26 scientists 754–773 publications: 26 scientists 774–793 publications: 19 scientists 794–813 publications: 23 scientists 814–833 publications: 20 scientists 834–853 publications: 16 scientists 854–873 publications: 20 scientists 874–893 publications: 11 scientists 894–913 publications: 11 scientists 914–933 publications: 16 scientists 934–953 publications: 13 scientists 954–973 publications: 10 scientists 974–993 publications: 11 scientists 994–1,013 publications: 9 scientists 1,014–1,033 publications: 9 scientists 1,034–1,053 publications: 10 scientists 1,054–1,064 publications: 6 scientists 1,065+ publications: 99 scientists
34–53 publications 1,065+

This scientist: 314 publications — 60th percentile

60% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 1,065 publications or more.

View publications distribution as a table
Number of Electronics and Electrical Engineering scientists by publication count, Research.com 2026 ranking edition. Based on 6,875 ranked scientists.
Publications Scientists This scientist
34–53 24
54–73 52
74–93 114
94–113 203
114–133 269
134–153 355
154–173 403
174–193 445
194–213 430
214–233 431
234–253 399
254–273 366
274–293 335
294–313 300
314–333 276 314
334–353 250
354–373 214
374–393 187
394–413 152
414–433 169
434–453 147
454–473 111
474–493 117
494–513 103
514–533 99
534–553 92
554–573 75
574–593 58
594–613 69
614–633 50
634–653 62
654–673 54
674–693 44
694–713 37
714–733 28
734–753 26
754–773 26
774–793 19
794–813 23
814–833 20
834–853 16
854–873 20
874–893 11
894–913 11
914–933 16
934–953 13
954–973 10
974–993 11
994–1,013 9
1,014–1,033 9
1,034–1,053 10
1,054–1,064 6
1,065+ 99
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Riccardo Scattolini D-index placement in Electronics and Electrical Engineering in 2026

The chart shows the D-index (discipline H-index) distribution of Electronics and Electrical Engineering scientists ranked by Research.com in 2026. The highlighted bar marks where Riccardo Scattolini sits on this spectrum.

No. of scientists
50 100 150 200 250
Bar chart with 82 bars. Horizontal axis: D-Index, 30 to 111+. Vertical axis: number of scientists, 0 to 263. Most scientists, 263, have 32 D-Index. The last bar groups every scientist with 111 D-Index or more. The highlighted bar, 53 D-Index, is where this scientist sits. 30 D-Index: 178 scientists 31 D-Index: 257 scientists 32 D-Index: 263 scientists 33 D-Index: 262 scientists 34 D-Index: 244 scientists 35 D-Index: 236 scientists 36 D-Index: 211 scientists 37 D-Index: 220 scientists 38 D-Index: 214 scientists 39 D-Index: 214 scientists 40 D-Index: 205 scientists 41 D-Index: 187 scientists 42 D-Index: 194 scientists 43 D-Index: 201 scientists 44 D-Index: 155 scientists 45 D-Index: 189 scientists 46 D-Index: 148 scientists 47 D-Index: 160 scientists 48 D-Index: 134 scientists 49 D-Index: 130 scientists 50 D-Index: 141 scientists 51 D-Index: 156 scientists 52 D-Index: 108 scientists 53 D-Index: 130 scientists 54 D-Index: 112 scientists 55 D-Index: 97 scientists 56 D-Index: 111 scientists 57 D-Index: 102 scientists 58 D-Index: 108 scientists 59 D-Index: 120 scientists 60 D-Index: 103 scientists 61 D-Index: 93 scientists 62 D-Index: 92 scientists 63 D-Index: 74 scientists 64 D-Index: 77 scientists 65 D-Index: 73 scientists 66 D-Index: 64 scientists 67 D-Index: 69 scientists 68 D-Index: 60 scientists 69 D-Index: 39 scientists 70 D-Index: 57 scientists 71 D-Index: 59 scientists 72 D-Index: 46 scientists 73 D-Index: 49 scientists 74 D-Index: 38 scientists 75 D-Index: 35 scientists 76 D-Index: 32 scientists 77 D-Index: 35 scientists 78 D-Index: 31 scientists 79 D-Index: 22 scientists 80 D-Index: 34 scientists 81 D-Index: 31 scientists 82 D-Index: 34 scientists 83 D-Index: 23 scientists 84 D-Index: 18 scientists 85 D-Index: 30 scientists 86 D-Index: 19 scientists 87 D-Index: 19 scientists 88 D-Index: 20 scientists 89 D-Index: 8 scientists 90 D-Index: 17 scientists 91 D-Index: 7 scientists 92 D-Index: 14 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 12 scientists 97 D-Index: 10 scientists 98 D-Index: 10 scientists 99 D-Index: 12 scientists 100 D-Index: 16 scientists 101 D-Index: 5 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 8 scientists 105 D-Index: 9 scientists 106 D-Index: 13 scientists 107 D-Index: 4 scientists 108 D-Index: 5 scientists 109 D-Index: 10 scientists 110 D-Index: 8 scientists 111+ D-Index: 96 scientists
30 D-Index 111+

This scientist: 53 D-Index — 66th percentile

66% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 111 D-Index or more.

View D-Index distribution as a table
Number of Electronics and Electrical Engineering scientists by D-index, Research.com 2026 ranking edition. Based on 6,875 ranked scientists.
D-Index Scientists This scientist
30 178
31 257
32 263
33 262
34 244
35 236
36 211
37 220
38 214
39 214
40 205
41 187
42 194
43 201
44 155
45 189
46 148
47 160
48 134
49 130
50 141
51 156
52 108
53 130 53
54 112
55 97
56 111
57 102
58 108
59 120
60 103
61 93
62 92
63 74
64 77
65 73
66 64
67 69
68 60
69 39
70 57
71 59
72 46
73 49
74 38
75 35
76 32
77 35
78 31
79 22
80 34
81 31
82 34
83 23
84 18
85 30
86 19
87 19
88 20
89 8
90 17
91 7
92 14
93 9
94 15
95 10
96 12
97 10
98 10
99 12
100 16
101 5
102 7
103 7
104 8
105 9
106 13
107 4
108 5
109 10
110 8
111+ 96
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Overview

Riccardo Scattolini is affiliated with the Polytechnic University of Milan in Italy. Their research primarily focuses on engineering, with a strong emphasis on control and systems engineering. The subfields of their work include electrical and electronic engineering, artificial intelligence, statistical and nonlinear physics, and building and construction.

The main topics covered in their publications encompass advanced control systems optimization, fault detection and control systems, neural networks and applications, control systems and identification, microgrid control and optimization, smart grid energy management, and optimal power flow distribution.

Recent scholarly contributions by Riccardo Scattolini include the following papers:

  • Robust tube-based model predictive control with Koopman operators, 2022, Automatica
  • On Recurrent Neural Networks for learning-based control: Recent results and ideas for future developments, 2022, Journal of Process Control
  • Learning model predictive control with long short-term memory networks, 2021, International Journal of Robust and Nonlinear Control
  • Hierarchical Control in Islanded DC Microgrids with Flexible Structures, 2021, Virtual Community of Pathological Anatomy (University of Castilla La Mancha)
  • On the stability properties of Gated Recurrent Units neural networks, 2021, Systems & Control Letters

Frequent co-authors collaborating with Riccardo Scattolini include Fabio Bonassi, Marcello Farina, Alessio La Bella, Enrico Terzi, and Lorenzo Fagiano.

The main venues where Scattolini's research is published are:

  • arXiv (Cornell University)
  • IFAC-PapersOnLine
  • Zenodo (CERN European Organization for Nuclear Research)
  • Automatica
  • IEEE Transactions on Control Systems Technology

Best Publications

  • Architectures for distributed and hierarchical Model Predictive Control - A review

    Riccardo Scattolini

  • Distributed model predictive control: A tutorial review and future research directions

    Panagiotis D. Christofides;Riccardo Scattolini;David Muñoz de la Peña;Jinfeng Liu

  • Constrained receding-horizon predictive control

    D.W. Clarke;R. Scattolini

  • A stabilizing model-based predictive control algorithm for nonlinear systems

    L. Magni;G.De Nicolao;L. Magnani;R. Scattolini

  • Stochastic linear Model Predictive Control with chance constraints – A review

    Marcello Farina;Luca Giulioni;Riccardo Scattolini

  • Distributed predictive control: A non-cooperative algorithm with neighbor-to-neighbor communication for linear systems

    Marcello Farina;Riccardo Scattolini

  • Stabilizing receding-horizon control of nonlinear time-varying systems

    G. De Nicolao;L. Magni;R. Scattolini

  • Robust model predictive control for nonlinear discrete-time systems

    L. Magni;G. De Nicolao;R. Scattolini;F. Allgöwer

  • Model Predictive Control Schemes for Consensus in Multi-Agent Systems with Single- and Double-Integrator Dynamics

    G. Ferrari-Trecate;L. Galbusera;M.P.E. Marciandi;R. Scattolini

  • Technical communique: Stabilizing decentralized model predictive control of nonlinear systems

    L. Magni;R. Scattolini

  • Distributed Moving Horizon Estimation for Linear Constrained Systems

    Marcello Farina;Giancarlo Ferrari-Trecate;Riccardo Scattolini

  • Stability and Robustness of Nonlinear Receding Horizon Control

    G. De Nicolao;L. Magni;R. Scattolini

  • Robustness and robust design of MPC for nonlinear discrete-time systems

    Lalo Magni;Riccardo Scattolini

  • Regional Input-to-State Stability for Nonlinear Model Predictive Control

    L. Magni;D.M. Raimondo;R. Scattolini

  • Fondamenti di Controlli Automatici

    Paolo Giuseppe Emilio Bolzern;Riccardo Scattolini;Nicola Luigi Schiavoni

  • Robust Tube-based Model Predictive Control with Koopman Operators-Extended Version

    Unknown

  • A Two-Layer Stochastic Model Predictive Control Scheme for Microgrids

    Stefano Raimondi Cominesi;Marcello Farina;Luca Giulioni;Bruno Picasso

  • Decentralized MPC of nonlinear systems: An input-to-state stability approach

    D.M. Raimondo;L. Magni;R. Scattolini

  • Brief paper: Moving-horizon partition-based state estimation of large-scale systems

    Marcello Farina;Giancarlo Ferrari-Trecate;Riccardo Scattolini

  • Model predictive control of continuous-time nonlinear systems with piecewise constant control

    L. Magni;R. Scattolini

  • Distributed Moving Horizon Estimation for Nonlinear Constrained Systems

    Marcello Farina;Giancarlo Ferrari-Trecate;Riccardo Scattolini

Frequent Co-Authors

Marcello Farina
Marcello Farina Polytechnic University of Milan
Lalo Magni
Lalo Magni University of Pavia
Patrizio Colaneri
Patrizio Colaneri Polytechnic University of Milan
Lorenzo Fagiano
Lorenzo Fagiano Polytechnic University of Milan
Sergio Bittanti
Sergio Bittanti Polytechnic University of Milan
Antonella Ferrara
Antonella Ferrara University of Pavia
Matteo Corno
Matteo Corno Polytechnic University of Milan
Sergio M. Savaresi
Sergio M. Savaresi Polytechnic University of Milan
Frank Allgöwer
Frank Allgöwer University of Stuttgart
Moritz Diehl
Moritz Diehl University of Freiburg

External Links

Personal website of Riccardo Scattolini Google Scholar page

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