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Marco C. Campi

Marco C. Campi

D-Index & Metrics

Engineering and Technology

D-Index
42
Citations
10051
World Ranking
6398
National Ranking
209

Marco C. Campi publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Marco C. Campi sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 134 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 117 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 59 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38 publications 804+

This scientist: 222 publications — 56th percentile

56% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

Marco C. Campi D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Marco C. Campi sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 128 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 349 scientists 41 D-Index: 362 scientists 42 D-Index: 425 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 94 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 24 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 42 D-Index — 35th percentile

35% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

Research.com Recognitions

  • 2017 - Fellow of the International Federation of Automatic Control (IFAC)
  • 2012 - IEEE Fellow For contributions to stochastic and randomized methods in systems and control

Overview

Marco C. Campi is affiliated with the University of Brescia in Italy. Their research focuses primarily on the fields of Engineering, Computer Science, and Decision Sciences. Within these disciplines, their work dives deeply into several subfields including Control and Systems Engineering, Artificial Intelligence, Management Science and Operations Research, Statistics, Probability and Uncertainty, and Ocean Engineering.

Their main topics of research encompass Risk and Portfolio Optimization, Control Systems and Identification, Fault Detection and Control Systems, Probabilistic and Robust Engineering Design, Reservoir Engineering and Simulation Methods, Machine Learning and Algorithms, and Advanced Multi-Objective Optimization Algorithms.

Marco C. Campi's published work features a number of recent papers, including:

  • "The scenario approach: A tool at the service of data-driven decision making," 2021, Annual Reviews in Control
  • "Scenario optimization with relaxation: A new tool for design and application to machine learning problems," 2020, Virtual Community of Pathological Anatomy (University of Castilla La Mancha)

Frequent co-authors contributing to Marc C. Campi's research include Simone Garatti, Algo Carè, Erik Weyer, Federico Ramponi, and Balázs Csanád Csáji.

Publication venues where their work frequently appears include arXiv (Cornell University), IFAC-PapersOnLine, IEEE Transactions on Automatic Control, Annual Reviews in Control, and Virtual Community of Pathological Anatomy (University of Castilla La Mancha).

Marco C. Campi has been recognized with awards such as Fellow of the International Federation of Automatic Control (IFAC) awarded in 2017 and IEEE Fellow in 2012 for contributions to stochastic and randomized methods in systems and control.

Best Publications

  • The scenario approach to robust control design

    G.C. Calafiore;M.C. Campi

  • Brief Virtual reference feedback tuning: a direct method for the design of feedback controllers

    M. C. Campi;A. Lecchini;S. M. Savaresi

  • Uncertain convex programs: randomized solutions and confidence levels

    Giuseppe Carlo Calafiore;Marco C. Campi

  • The Exact Feasibility of Randomized Solutions of Uncertain Convex Programs

    M. C. Campi;S. Garatti

  • A Sampling-and-Discarding Approach to Chance-Constrained Optimization: Feasibility and Optimality

    Marco C. Campi;Simone Garatti

  • The scenario approach for systems and control design

    Marco C. Campi;Simone Garatti;Maria Prandini

  • Direct nonlinear control design: the virtual reference feedback tuning (VRFT) approach

    M.C. Campi;S.M. Savaresi

  • Virtual reference feedback tuning for two degree of freedom controllers

    A. Lecchini;MC Campi;SM Savaresi

  • Wait-and-judge scenario optimization

    Marco C. Campi;Simone Garatti

  • A General Scenario Theory for Nonconvex Optimization and Decision Making

    Marco Claudio Campi;Simone Garatti;Federico Alessandro Ramponi

  • Interval predictor models: Identification and reliability

    M. C. Campi;G. Calafiore;S. Garatti

  • Guaranteed non-asymptotic confidence regions in system identification

    M. C. Campi;E. Weyer

  • Finite sample properties of system identification methods

    M.C. Campi;E. Weyer

  • Convergence and exponential convergence of identification algorithms with directional forgetting factor

    S. Bittanti;P. Bolzern;M. Campi

  • An Application of the Virtual Reference Feedback Tuning Method to a Benchmark Problem

    Marco C. Campi;Andrea Lecchini;Sergio M. Savaresi

  • Modulating robustness in control design: Principles and algorithms

    S. Garatti;M. C. Campi

  • The exact feasibility of randomized solutions of robust convex programs

    M. C. Campi;Simone Garatti

  • Sign-Perturbed Sums: A New System Identification Approach for Constructing Exact Non-Asymptotic Confidence Regions in Linear Regression Models

    Balázs Csanád Csáji;Marco Claudio Campi;Erik Weyer

  • Virtual reference feedback tuning (VRFT): a new direct approach to the design of feedback controllers

    M.C. Campi;A. Lecchini;S.M. Savaresi

  • ADAPTIVE CONTROL OF LINEAR TIME INVARIANT SYSTEMS: THE "BET ON THE BEST" PRINCIPLE ∗

    S. Bittanti;M. C. Campi

  • Finite sample properties of system identification methods

    E. Weyer;M.C. Campi

Frequent Co-Authors

Sergio Bittanti
Sergio Bittanti Polytechnic University of Milan
Giuseppe Carlo Calafiore
Giuseppe Carlo Calafiore Polytechnic University of Turin
Sergio M. Savaresi
Sergio M. Savaresi Polytechnic University of Milan
P. R. Kumar
P. R. Kumar Texas A&M University
Le Xie
Le Xie Texas A&M University
Joao P. Hespanha
Joao P. Hespanha University of California, Santa Barbara
Matthew R. James
Matthew R. James Australian National University
Christos G. Cassandras
Christos G. Cassandras Boston University
Toshiharu Sugie
Toshiharu Sugie Kyoto University
Maurice Heemels
Maurice Heemels Eindhoven University of Technology

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