World's Best Scientists 2026 revealed!
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Electronics and Electrical Engineering
USA
2026

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
98
Citations
34829
World Ranking
209
National Ranking
101

Lorenz T. Biegler 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 Lorenz T. Biegler 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: 446 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: 604 publications — 90th percentile

90% of scientists in this discipline score the same or lower.

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

Lorenz T. Biegler 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 Lorenz T. Biegler sits on this spectrum.

30 D-Index: 178 scientists 31 D-Index: 257 scientists 32 D-Index: 263 scientists 33 D-Index: 263 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: 98 D-Index — 97th percentile

97% 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

  • 2026 - Research.com Electronics and Electrical Engineering in United States Leader Award
  • 2025 - Research.com Electronics and Electrical Engineering in United States Leader Award
  • 2017 - Fellow of the International Federation of Automatic Control (IFAC)
  • 2014 - SIAM Fellow For contributions in large-scale nonlinear optimization theory and algorithms, particularly IPOPT, and their novel application to flowsheet optimization, process control, data reconciliation, and complex process applications.
  • 2013 - Member of the National Academy of Engineering For contributions in large-scale nonlinear optimization theory and algorithms for application to process optimization, design and control.

Overview

Lorenz T. Biegler is affiliated with Carnegie Mellon University in the United States and has produced significant research in the field of engineering, particularly focused on control and systems engineering.

Their work spans multiple subfields of study, including:

  • Control and Systems Engineering
  • Mechanical Engineering
  • Computational Theory and Mathematics
  • Aerospace Engineering
  • Materials Chemistry

The primary topics of their research cover:

  • Advanced Control Systems Optimization
  • Process Optimization and Integration
  • Fault Detection and Control Systems
  • Advanced Multi-Objective Optimization Algorithms
  • Carbon Dioxide Capture Technologies
  • Advanced Optimization Algorithms Research
  • Control Systems and Identification

Among the recent papers authored or co-authored by Lorenz T. Biegler are the following:

  • "The IDAES process modeling framework and model library-Flexibility for process simulation and optimization," 2021, published in Journal of Advanced Manufacturing and Processing
  • "Formulating data-driven surrogate models for process optimization," 2023, Computers & Chemical Engineering
  • "A perspective on nonlinear model predictive control," 2021, Korean Journal of Chemical Engineering
  • "Heat exchanger network synthesis with detailed exchanger designs-2. Hybrid optimization strategy for synthesis of heat exchanger networks," 2020, AIChE Journal
  • "Predicting the performance of an industrial furnace using Gaussian process and linear regression: A comparison," 2023, Computers & Chemical Engineering

Frequent collaborators in their research include:

  • Miguel Zamarripa
  • Saif R. Kazi
  • Robert Parker
  • Sakshi Naik
  • Debangsu Bhattacharyya

Publication venues where their work regularly appears include:

  • Computers & Chemical Engineering
  • AIChE Journal
  • IFAC-PapersOnLine
  • Journal of Process Control
  • Industrial & Engineering Chemistry Research

Lorenz T. Biegler has been recognized by professional organizations with several awards, including:

  • Fellow of the International Federation of Automatic Control (IFAC), 2017
  • SIAM Fellow, 2014, for contributions in large-scale nonlinear optimization theory and algorithms, particularly IPOPT, applied to flowsheet optimization, process control, data reconciliation, and complex process applications
  • Member of the National Academy of Engineering, 2013, acknowledging contributions in large-scale nonlinear optimization theory and algorithms for process optimization, design, and control

Best Publications

  • On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming

    Andreas Wächter;Lorenz T. Biegler

  • Systematic methods for chemical process design

    L.T. Biegler;I.E. Grossmann;A.W. Westerberg

  • Systematic Methods of Chemical Process Design

    Lorenz T. Biegler;Ignacio E. Grossmann;Arthur W. Westerberg

  • Nonlinear programming : concepts, algorithms, and applications to chemical processes

    Lorenz T. Biegler

  • An algorithmic framework for convex mixed integer nonlinear programs

    Pierre Bonami;Lorenz T. Biegler;Andrew R. Conn;GéRard CornuéJols

  • Retrospective on optimization

    Lorenz T. Biegler;Ignacio E. Grossmann

  • Large-scale nonlinear programming using IPOPT: An integrating framework for enterprise-wide dynamic optimization

    Lorenz T. Biegler;Victor M. Zavala

  • An overview of simultaneous strategies for dynamic optimization

    Lorenz T. Biegler

  • Line Search Filter Methods for Nonlinear Programming: Motivation and Global Convergence

    Andreas Wächter;Lorenz T. Biegler

  • On the optimization of differential-algebraic process systems

    J. E. Cuthrell;L. T. Biegler

  • Advances in simultaneous strategies for dynamic process optimization

    Lorenz T. Biegler;Arturo M. Cervantes;Andreas Wächter

  • Solution of dynamic optimization problems by successive quadratic programming and orthogonal collocation

    Lorenz T. Biegler

  • The advanced-step NMPC controller: Optimality, stability and robustness

    Victor M. Zavala;Lorenz T. Biegler

  • Simultaneous optimization and solution methods for batch reactor control profiles

    J.E. Cuthrell;L.T. Biegler

  • Optimization of a Pressure-Swing Adsorption Process Using Zeolite 13X for CO2 Sequestration

    Daeho Ko;Ranjani Siriwardane;Lorenz T. Biegler

  • Simultaneous dynamic optimization strategies: Recent advances and challenges

    Shivakumar Kameswaran;Lorenz T. Biegler

  • Accurate solution of differential-algebraic optimization problems

    Jeffery S. Logsdon;Lorenz T. Biegler

  • Convergence rates for direct transcription of optimal control problems using collocation at Radau points

    Shivakumar Kameswaran;Lorenz T. Biegler

  • Quadratic programming methods for reduced Hessian SQP

    C. Schmid;L.T. Biegler

  • Simultaneous strategies for data reconciliation and gross error detection of nonlinear systems

    I.B. Tjoa;L.T. Biegler

  • Large-Scale PDE-Constrained Optimization: An Introduction

    Lorenz T. Biegler;Omar Ghattas;Matthias Heinkenschloss;Bart van Bloemen Waanders

  • Data reconciliation and gross‐error detection for dynamic systems

    João S. Albuquerque;Lorenz T. Biegler

  • Assessment and Future Directions of Nonlinear Model Predictive Control

    Rolf Findeisen;Frank Allgöwer;Lorenz T. Biegler

  • Lyapunov stability of economically oriented NMPC for cyclic processes

    Rui Huang;Eranda Harinath;Lorenz T. Biegler

  • Line Search Filter Methods for Nonlinear Programming: Local Convergence

    Andreas Wächter;Lorenz T. Biegler

  • Large-Scale Inverse Problems and Quantification of Uncertainty

    Lorenz Biegler;George Biros;Omar Nabih Ghattas;Matthias Heinkenschloss

  • Constraint handing and stability properties of model-predictive control

    Nuno M. C. de Oliveira;Lorenz T. Biegler

  • A Superstructure-Based Optimal Synthesis of PSA Cycles for Post-Combustion CO2 Capture

    Anshul Agarwal;Lorenz T. Biegler;Stephen E. Zitney

  • Optimization approaches to nonlinear model predictive control

    L.T. Biegler;J.B. Rawlings

  • Contamination Source Determination for Water Networks

    Carl D. Laird;Carl D. Laird;Lorenz T. Biegler;Lorenz T. Biegler;Bart G. van Bloemen Waanders;Bart G. van Bloemen Waanders;Roscoe A. Bartlett;Roscoe A. Bartlett

  • Numerical Experience with a Reduced Hessian Methodfor Large Scale Constrained Optimization

    Lorenz T. Biegler;Jorge Nocedal;Claudia Schmid;David Ternet

Frequent Co-Authors

Myung S. Jhon
Myung S. Jhon Carnegie Mellon University
Guy A. Dumont
Guy A. Dumont University of British Columbia
Nae-Eung Lee
Nae-Eung Lee Sungkyunkwan University
Geun Young Yeom
Geun Young Yeom Sungkyunkwan University
James B. Rawlings
James B. Rawlings University of California, Santa Barbara
Youqing Shen
Youqing Shen Zhejiang University

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