World's Best Scientists 2026 revealed!
Giuseppe De Nicolao

Giuseppe De Nicolao

D-Index & Metrics

Engineering and Technology

D-Index
51
Citations
11155
World Ranking
3814
National Ranking
104

Giuseppe De Nicolao 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 Giuseppe De Nicolao sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 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: 118 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: 60 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: 242 publications — 62nd percentile

62% of scientists in this discipline score the same or lower.

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

Giuseppe De Nicolao 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 Giuseppe De Nicolao sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 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: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 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: 95 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: 25 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: 51 D-Index — 62nd percentile

62% of scientists in this discipline score the same or lower.

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

Overview

Giuseppe De Nicolao is affiliated with the University of Pavia in Italy and specializes primarily in Engineering, with a focus on Control and Systems Engineering, Electrical and Electronic Engineering, and Modeling and Simulation. Their research spans several subfields and topics, highlighting involvement in interdisciplinary areas including Infectious Diseases, Artificial Intelligence, and epidemiological modeling.

The scientist has contributed extensively to research on COVID-19 epidemiological studies and SARS-CoV-2-related work. Their scientific interests are reflected in areas such as Energy Load and Power Forecasting, Control Systems and Identification, Fault Detection and Control Systems, Statistical and Numerical Algorithms, and Opinion Dynamics and Social Influence.

Recent papers authored or co-authored by Giuseppe De Nicolao include:

  • Modeling vaccination rollouts, SARS-CoV-2 variants and the requirement for non-pharmaceutical interventions in Italy, 2021, Nature Medicine
  • Endpoints and design of clinical trials in patients with decompensated cirrhosis: Position paper of the LiverHope Consortium, 2020, Journal of Hepatology
  • Opinion Dynamics in Social Networks: The Effect of Centralized Interaction Tuning on Emerging Behaviors, 2020, IEEE Transactions on Computational Social Systems
  • Identification of AC Distribution Networks With Recursive Least Squares and Optimal Design of Experiment, 2021, IEEE Transactions on Control Systems Technology
  • Diabetes-associated genetic variation in TCF7L2 alters pulsatile insulin secretion in humans, 2020, JCI Insight

Frequent co-authors in their body of work include:

  • Paolo Bolzern
  • Patrizio Colaneri
  • Tianshi Chen
  • Alessandro Chiuso
  • Lennart Ljung

The scientist has published numerous articles in notable venues, with recurring contributions to arXiv (Cornell University), Epidemiology Biostatistics and Public Health, Automatica, International Journal of Oil Gas and Coal Technology, and Advanced Sensor Research.

In addition to journal articles, Giuseppe De Nicolao has authored works within the Communications and Control Engineering series, notably the book "Regularized System Identification" published in 2022.

Best Publications

  • Survey Kernel methods in system identification, machine learning and function estimation: A survey

    Gianluigi Pillonetto;Francesco Dinuzzo;Tianshi Chen;Giuseppe De Nicolao

  • A new kernel-based approach for linear system identification

    Gianluigi Pillonetto;Giuseppe De Nicolao

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

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

  • Model predictive control of type 1 diabetes: an in silico trial.

    Lalo Magni;Davide M. Raimondo;Luca Bossi;Chiara Dalla Man

  • Fully Integrated Artificial Pancreas in Type 1 Diabetes: Modular Closed-Loop Glucose Control Maintains Near Normoglycemia

    Marc Breton;Anne Farret;Daniela Bruttomesso;Stacey Anderson

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

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

  • Brief paper: Markov Jump Linear Systems with switching transition rates: Mean square stability with dwell-time

    Paolo Bolzern;Patrizio Colaneri;Giuseppe De Nicolao

  • Robust model predictive control for nonlinear discrete-time systems

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

  • Nonparametric input estimation in physiological systems: problems, methods, and case studies

    Giuseppe de Nicolao;Giovanni Sparacino;Claudio Cobelli

  • Multinational study of subcutaneous model-predictive closed-loop control in type 1 diabetes mellitus: summary of the results.

    Boris Kovatchev;Claudio Cobelli;Eric Renard;Stacey Anderson

  • Stochastic stability of Positive Markov Jump Linear Systems

    Paolo Bolzern;Patrizio Colaneri;Giuseppe De Nicolao

  • Evaluating the efficacy of closed-loop glucose regulation via control-variability grid analysis.

    Lalo Magni;Davide M. Raimondo;Chiara Dalla Man;Marc Breton

  • Prediction error identification of linear systems: A nonparametric Gaussian regression approach

    Gianluigi Pillonetto;Alessandro Chiuso;Giuseppe De Nicolao

  • Modular Closed-Loop Control of Diabetes

    S. D. Patek;L. Magni;E. Dassau;C. Hughes-Karvetski

  • Stability and Robustness of Nonlinear Receding Horizon Control

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

  • Model predictive control of glucose concentration in type I diabetic patients: An in silico trial

    L. Magni;D.M. Raimondo;C. Dalla Man;G. De Nicolao

  • The Periodic Riccati Equation

    Sergio Bittanti;Patrizio Colaneri;Giuseppe De Nicolao

  • The difference periodic Ricati equation for the periodic prediction problem

    S. Bittanti;P. Colaneri;G. De Nicolao

  • Neural Network Incorporating Meal Information Improves Accuracy of Short-Time Prediction of Glucose Concentration

    C. Zecchin;A. Facchinetti;G. Sparacino;G. De Nicolao

  • Closed-Loop Artificial Pancreas Using Subcutaneous Glucose Sensing and Insulin Delivery and a Model Predictive Control Algorithm: Preliminary Studies in Padova and Montpellier

    Daniela Bruttomesso;Anne Farret;Silvana Costa;Maria Cristina Marescotti

  • Vaccination and SARS-CoV-2 variants: how much containment is still needed? A quantitative assessment.

    Giulia Giordano;Marta Colaneri;Alessandro Di Filippo;Franco Blanchini

Frequent Co-Authors

Patrizio Colaneri
Patrizio Colaneri Polytechnic University of Milan
Claudio Cobelli
Claudio Cobelli University of Padua
Lalo Magni
Lalo Magni University of Pavia
Gianluigi Pillonetto
Gianluigi Pillonetto University of Padua
Riccardo Bellazzi
Riccardo Bellazzi University of Pavia
Angelo Avogaro
Angelo Avogaro University of Padua
Giovanni Sparacino
Giovanni Sparacino University of Padua
Francis J. Doyle
Francis J. Doyle Brown University
Alessandro Chiuso
Alessandro Chiuso University of Padua
Sergio Bittanti
Sergio Bittanti Polytechnic University of Milan

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