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D-Index & Metrics

Electronics and Electrical Engineering

D-Index
71
Citations
29988
World Ranking
831
National Ranking
356

Magnus Egerstedt 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 Magnus Egerstedt sits on this spectrum.

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 publications 1,065+

This scientist: 574 publications — 89th percentile

89% of scientists in this discipline score the same or lower.

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

Magnus Egerstedt 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 Magnus Egerstedt sits on this spectrum.

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: 71 D-Index — 88th percentile

88% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2017 - Fellow of the International Federation of Automatic Control (IFAC)
  • 2012 - IEEE Fellow For contributions to hybrid and networked control, with applications in robotics

Overview

Magnus Egerstedt is affiliated with the University of California, Irvine in the United States. Their research spans the fields of Computer Science and Engineering, with numerous contributions in subfields such as Computer Networks and Communications, Control and Systems Engineering, Mechanical Engineering, Computer Vision and Pattern Recognition, and Artificial Intelligence.

The scientist's main topics of work include Distributed Control Multi-Agent Systems, Modular Robots and Swarm Intelligence, Robotic Path Planning Algorithms, Advanced Control Systems Optimization, Reinforcement Learning in Robotics, Optimization and Search Problems, and Control Systems and Identification.

Magnus Egerstedt has authored several recent papers, illustrating a focus on multirobot systems, control methodologies, and reinforcement learning in robotics. Notable recent publications include:

  • The Robotarium: Globally Impactful Opportunities, Challenges, and Lessons Learned in Remote-Access, Distributed Control of Multirobot Systems, 2020, published in IEEE Control Systems
  • Integral Control Barrier Functions for Dynamically Defined Control Laws, 2020, published in IEEE Control Systems Letters
  • Optimization-Based Distributed Flocking Control for Multiple Rigid Bodies, 2020, published in IEEE Robotics and Automation Letters
  • Safe Reinforcement Learning Using Robust Control Barrier Functions, 2022, published in IEEE Robotics and Automation Letters
  • Resilient Monitoring in Heterogeneous Multi-Robot Systems Through Network Reconfiguration, 2021, published in IEEE Transactions on Robotics

The scientist frequently publishes in the following venues:

  • IEEE Control Systems
  • IEEE Transactions on Automatic Control
  • arXiv (Cornell University)
  • IEEE Transactions on Control Systems Technology
  • IEEE Transactions on Control of Network Systems

Magnus Egerstedt has collaborated often with a number of coauthors, including Thomas Parisini, Maria Elena Valcher, Rodolphe Sepulchre, Miroslav Krstić, and Jeff S. Shamma.

Regarding book publications, the scientist has two works published by Princeton University Press under the title "Robot Ecology" in 2021.

Awards earned by Magnus Egerstedt include the IEEE Fellow distinction awarded in 2012 for contributions to hybrid and networked control with applications in robotics, as well as being named a Fellow of the International Federation of Automatic Control (IFAC) in 2017.

Best Publications

  • Graph Theoretic Methods in Multiagent Networks

    Mehran Mesbahi;Magnus Egerstedt

  • Formation constrained multi-agent control

    M. Egerstedt;Xiaoming Hu

  • Control Barrier Functions: Theory and Applications

    Aaron D. Ames;Samuel Coogan;Magnus Egerstedt;Gennaro Notomista

  • Distributed Coordination Control of Multiagent Systems While Preserving Connectedness

    Meng Ji;M. Egerstedt

  • Controllability of Multi-Agent Systems from a Graph-Theoretic Perspective

    Amirreza Rahmani;Meng Ji;Mehran Mesbahi;Magnus Egerstedt

  • Containment Control in Mobile Networks

    M. Ji;G. Ferrari-Trecate;M. Egerstedt;A. Buffa

  • Safety Barrier Certificates for Collisions-Free Multirobot Systems

    Li Wang;Aaron D. Ames;Magnus Egerstedt

  • On the regularization of Zeno hybrid automata

    Karl Henrik Johansson;Magnus Egerstedt;John Lygeros;Shankar Sastry

  • Distributed containment control with multiple stationary or dynamic leaders in fixed and switching directed networks

    Yongcan Cao;Wei Ren;Magnus Egerstedt

  • A control Lyapunov function approach to multiagent coordination

    P. Ogren;M. Egerstedt;Xiaoming Hu

  • A control Lyapunov function approach to multi-agent coordination

    P. Ogren;M. Egerstedt;X. Hu

  • Symbolic planning and control of robot motion [Grand Challenges of Robotics]

    C. Belta;A. Bicchi;M. Egerstedt;E. Frazzoli

  • Graph-theoretic connectivity control of mobile robot networks

    M. M. Zavlanos;M. B. Egerstedt;G. J. Pappas

  • Autonomous driving in urban environments: approaches, lessons and challenges

    Mark E. Campbell;Magnus Egerstedt;Jonathan P. How;Richard M Murray

  • IEEE TRANSACTIONS ON AUTOMATIC CONTROL

    P. J. Antsaklis;Elizabeth Kovács;E. Chong

  • The Robotarium: A remotely accessible swarm robotics research testbed

    Daniel Pickem;Paul Glotfelter;Li Wang;Mark Mote

  • Transition-time optimization for switched-mode dynamical systems

    M. Egerstedt;Y. Wardi;H. Axelsson

  • Control of mobile platforms using a virtual vehicle approach

    M. Egerstedt;X. Hu;A. Stotsky

  • Brief paper: Containment in leader-follower networks with switching communication topologies

    G. Notarstefano;M. Egerstedt;M. Haque

  • Nonsmooth Barrier Functions With Applications to Multi-Robot Systems

    Paul Glotfelter;Jorge Cortes;Magnus Egerstedt

  • Graph-Theoretic Connectivity Control of Mobile Robot Networks This paper develops an analysis for groups of vehicles connected by a communication network; control laws are formulated to accomplish tasks requiring rendezvous, and swarm in group formations.

    Michael M. Zavlanos;Magnus B. Egerstedt;George J. Pappas

Frequent Co-Authors

Xiaoming Hu
Xiaoming Hu Royal Institute of Technology
Aaron D. Ames
Aaron D. Ames California Institute of Technology
Mehran Mesbahi
Mehran Mesbahi University of Washington
Jeff S. Shamma
Jeff S. Shamma University of Illinois at Urbana-Champaign
Seth Hutchinson
Seth Hutchinson University of Illinois at Urbana-Champaign
Tucker Balch
Tucker Balch Emory University
Calin Belta
Calin Belta Boston University
Fumin Zhang
Fumin Zhang Georgia Institute of Technology
Antonio Bicchi
Antonio Bicchi Italian Institute of Technology
Santiago Grijalva
Santiago Grijalva Georgia Institute of Technology

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