World's Best Scientists 2026 revealed!
Luca Daniel

Luca Daniel

D-Index & Metrics

Engineering and Technology

D-Index
36
Citations
6021
World Ranking
8648
National Ranking
2401

Luca Daniel 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 Luca Daniel 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: 232 publications — 59th percentile

59% of scientists in this discipline score the same or lower.

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

Luca Daniel 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 Luca Daniel 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: 36 D-Index — 13th percentile

13% of scientists in this discipline score the same or lower.

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

Overview

Luca Daniel is affiliated with MIT in the United States and focuses primarily on engineering disciplines, with a specialization in electrical and electronic engineering as well as artificial intelligence and automotive engineering. Their research contributions also extend into statistical and nonlinear physics and radiology, nuclear medicine, and imaging.

The scientist's work covers various topics, including:

  • Optimal Power Flow Distribution
  • Model Reduction and Neural Networks
  • Power System Optimization and Stability
  • Adversarial Robustness in Machine Learning
  • Advanced MRI Techniques and Applications
  • Probabilistic and Robust Engineering Design
  • Electrical and Bioimpedance Tomography

Major recent publications demonstrate a focus on computational methods, electrical field applications, and robustness in machine learning models:

  • Fast and Accurate Tensor Completion With Total Variation Regularized Tensor Trains, 2020, IEEE Transactions on Image Processing
  • Metasurface Matching Layers for Enhanced Electric Field Penetration Into the Human Body, 2020, IEEE Access
  • Towards Certificated Model Robustness Against Weight Perturbations, 2020, Proceedings of the AAAI Conference on Artificial Intelligence
  • Matching Layer Design for Far-Field and Near-Field Penetration Into a Multilayered Lossy Media, 2022, IEEE Antennas and Propagation Magazine
  • Comparison and Analysis of Algorithms for Coordinated EV Charging to Reduce Power Grid Impact, 2024, IEEE Open Journal of Vehicular Technology

Frequent collaborators in their research include:

  • Samuel Chevalier
  • José E. Cruz Serrallés
  • Tsui-Wei Weng
  • Ilias I. Giannakopoulos
  • Riccardo Lattanzi

Luca Daniel has published notably in a number of venues, with repeated contributions to:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • IEEE Transactions on Power Systems
  • IEEE Access
  • IEEE Antennas and Propagation Magazine

Their work exemplifies an interdisciplinary approach combining engineering principles with the development of advanced computational techniques, focusing on both theoretical and applied aspects of electrical engineering and machine learning.

Best Publications

  • Towards Fast Computation of Certified Robustness for ReLU Networks

    Tsui-Wei Weng;Huan Zhang;Hongge Chen;Zhao Song

  • A multiparameter moment-matching model-reduction approach for generating geometrically parameterized interconnect performance models

    L. Daniel;Ong Chin Siong;L.S. Chay;Kwok Hong Lee

  • Efficient Neural Network Robustness Certification with General Activation Functions

    Huan Zhang;Tsui-Wei Weng;Pin-Yu Chen;Cho-Jui Hsieh

  • Guaranteed passive balancing transformations for model order reduction

    J.R. Phillips;L. Daniel;L.M. Silveira

  • Guaranteed passive balancing transformations for model order reduction

    Joel Phillips;Luca Daniel;L. Miguel Silveira

  • Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach

    Tsui-Wei Weng;Huan Zhang;Pin-Yu Chen;Jinfeng Yi

  • Stochastic Testing Method for Transistor-Level Uncertainty Quantification Based on Generalized Polynomial Chaos

    Zheng Zhang;T. A. El-Moselhy;I. M. Elfadel;L. Daniel

  • Efficient Neural Network Robustness Certification with General Activation Functions

    Huan Zhang;Tsui-Wei Weng;Pin-Yu Chen;Cho-Jui Hsieh

  • Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach

    Tsui-Wei Weng;Huan Zhang;Pin-Yu Chen;Jinfeng Yi

  • Towards Fast Computation of Certified Robustness for ReLU Networks

    Tsui-Wei Weng;Huan Zhang;Hongge Chen;Zhao Song

  • Design of microfabricated inductors

    L. Daniel;C.R. Sullivan;S.R. Sanders

  • A Quasi-Convex Optimization Approach to Parameterized Model Order Reduction

    Kin Cheong Sou;A. Megretski;L. Daniel

  • CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks.

    Akhilan Boopathy;Tsui-Wei Weng;Pin-Yu Chen;Sijia Liu

  • Enabling High-Dimensional Hierarchical Uncertainty Quantification by ANOVA and Tensor-Train Decomposition

    Zheng Zhang;Xiu Yang;Ivan V. Oseledets;George Em Karniadakis

  • Stable FFT-JVIE solvers for fast analysis of highly inhomogeneous dielectric objects

    Athanasios G. Polimeridis;Jorge Fernandez Villena;Luca Daniel;Jacob K. White

  • A Piecewise-Linear Moment-Matching Approach to Parameterized Model-Order Reduction for Highly Nonlinear Systems

    B.N. Bond;L. Daniel

  • Modeling and Simulation of Vanadium Dioxide Relaxation Oscillators

    Paolo Maffezzoni;Luca Daniel;Nikhil Shukla;Suman Datta

  • Parameterized model order reduction of nonlinear dynamical systems

    B. Bond;L. Daniel

  • The ultimate signal-to-noise ratio in realistic body models.

    Bastien Guérin;Jorge F. Villena;Athanasios G. Polimeridis;Elfar Adalsteinsson

  • Stable Reduced Models for Nonlinear Descriptor Systems Through Piecewise-Linear Approximation and Projection

    B.N. Bond;L. Daniel

  • Compact Modeling of Nonlinear Analog Circuits Using System Identification via Semidefinite Programming and Incremental Stability Certification

    Bradley N Bond;Zohaib Mahmood;Yan Li;Ranko Sredojevic

  • Big-Data Tensor Recovery for High-Dimensional Uncertainty Quantification of Process Variations

    Zheng Zhang;Tsui-Wei Weng;Luca Daniel

  • Guaranteed stable projection-based model reduction for indefinite and unstable linear systems

    Bradley N. Bond;Luca Daniel

  • Reduced-Order Models for Electromagnetic Scattering Problems

    Amit Hochman;Jorge Fernandez Villena;Athanasios G. Polimeridis;Luis Miguel Silveira

  • Towards Verifying Robustness of Neural Networks Against A Family of Semantic Perturbations

    Jeet Mohapatra;Tsui-Wei Weng;Pin-Yu Chen;Sijia Liu

  • POPQORN: Quantifying Robustness of Recurrent Neural Networks

    Ching-Yun Ko;Zhaoyang Lyu;Lily Weng;Luca Daniel

Frequent Co-Authors

Pin-Yu Chen
Pin-Yu Chen IBM (United States)
Sijia Liu
Sijia Liu Michigan State University
Huan Zhang
Huan Zhang University of California, Los Angeles
Cho-Jui Hsieh
Cho-Jui Hsieh University of California, Los Angeles
Lawrence L. Wald
Lawrence L. Wald Harvard University
Giuseppe Carlo Calafiore
Giuseppe Carlo Calafiore Polytechnic University of Turin
Alberto Sangiovanni-Vincentelli
Alberto Sangiovanni-Vincentelli University of California, Berkeley
Suman Datta
Suman Datta Georgia Institute of Technology

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