World's Best Scientists 2026 revealed!

D-Index & Metrics

Mathematics

D-Index
41
Citations
5953
World Ranking
1939
National Ranking
14

Electronics and Electrical Engineering

D-Index
40
Citations
5641
World Ranking
4554
National Ranking
75

Research.com Recognitions

  • 2020 - IEEE Control Systems Award “For contributions to optimal filtering, stochastic control, stochastic realization theory, and system identification.”
  • 2020 - Member of Academia Europaea
  • 2010 - Fellow of the International Federation of Automatic Control (IFAC)
  • 2010 - SIAM Fellow For contributions to systems and control.
  • 1989 - IEEE Fellow For contributions to filtering and estimation, stochastic control, and stochastic theory.
  • 1964 - Fellow of the American Association for the Advancement of Science (AAAS)
  • Foreign Member, Chinese Academy of Sciences
  • Foreign Member, Chinese Academy of Sciences
  • Foreign Member, Chinese Academy of Sciences
  • Foreign Member, Chinese Academy of Sciences
  • Foreign Member, Chinese Academy of Sciences
  • Foreign Member, Chinese Academy of Sciences
  • Foreign Member, Chinese Academy of Sciences
  • Foreign Member, Chinese Academy of Sciences

Overview

Anders Lindquist is affiliated with the Royal Institute of Technology in Sweden. Their research spans several main fields, primarily Engineering and Computer Science. Within these domains, their work focuses notably on Control and Systems Engineering and Artificial Intelligence, alongside contributions to Statistical and Nonlinear Physics, Computer Networks and Communications, and Applied Mathematics.

Their scholarly output includes 29 publications in Engineering and 26 in Computer Science, reflecting a significant engagement with these disciplines. The subfields where Anders Lindquist has contributed include:

  • Control and Systems Engineering
  • Artificial Intelligence
  • Statistical and Nonlinear Physics
  • Computer Networks and Communications
  • Applied Mathematics

Key topics addressed in their research cover diverse areas within control theory and data analysis. These topics include:

  • Control Systems and Identification
  • Target Tracking and Data Fusion in Sensor Networks
  • Fault Detection and Control Systems
  • Neural Networks and Applications
  • Gaussian Processes and Bayesian Inference
  • Sparse and Compressive Sensing Techniques
  • Gene Regulatory Network Analysis

Anders Lindquist has published extensively across several venues. Their frequent publication outlets include:

  • arXiv (Cornell University)
  • Automatica
  • IEEE Transactions on Automatic Control
  • IFAC-PapersOnLine
  • Systems & Control Letters

Noteworthy recent papers illustrate the breadth of their research topics and collaborators:

  • Synchronization of nonlinear delayed semi-Markov jump neural networks via distributed delayed impulsive control, 2023, Systems & Control Letters
  • Non-Gaussian Bayesian filtering by density parametrization using power moments, 2023, Automatica
  • Identification of low rank vector processes, 2023, Automatica
  • The Covariance Extension Equation: A Riccati-Type Approach to Analytic Interpolation, 2021, IEEE Transactions on Automatic Control
  • A non-Gaussian Bayesian filter using power and generalized logarithmic moments, 2024, Automatica

Their frequent co-authors include Guangyu Wu, Wenqi Cao, Giorgio Picci, and Yufang Cui, indicating established collaborative relationships in research work.

Among the recognitions awarded to Anders Lindquist are membership in the Academia Europaea (2020) and Fellowship of the IEEE (1989), SIAM (2010), IFAC (2010), and AAAS (1964). They received the IEEE Control Systems Award in 2020 "for contributions to optimal filtering, stochastic control, stochastic realization theory, and system identification," and they hold the distinction of being a Foreign Member of the Chinese Academy of Sciences.

Best Publications

  • On the partial realization problem

    William B. Gragg;Anders Lindquist

  • A generalized entropy criterion for Nevanlinna-Pick interpolation with degree constraint

    C.I. Byrnes;T.T. Georgiou;A. Lindquist

  • Kullback-Leibler approximation of spectral density functions

    T.T. Georgiou;A. Lindquist

  • A new approach to spectral estimation: a tunable high-resolution spectral estimator

    C.L. Byrnes;T.T. Georgiou;A. Lindquist

  • On the Stochastic Realization Problem

    Anders Lindquist;Giorgio Picci

  • Canonical correlation analysis, approximate covariance extension, and identification of stationary time series

    Anders Lindquist;Giorgio Picci

  • A Convex Optimization Approach to the Rational Covariance Extension Problem

    Christopher I. Byrnes;Sergei V. Gusev;Anders Lindquist

  • A complete parameterization of all positive rational extensions of a covariance sequence

    C.I. Byrnes;A. Lindquist;S.V. Gusev;A.S. Matveev

  • Linear Stochastic Systems

    Anders Lindquist;Giorgio Picci

  • Realization Theory for Multivariate Stationary Gaussian Processes

    Anders Lindquist;Giorgio Picci

  • Survey on the State of Systems and Control

    Vincent D. Blondel;Michel Gevers;Anders Lindquist

  • Linear Stochastic Systems: A Geometric Approach to Modeling, Estimation and Identification

    Anders Lindquist;Giorgio Picci

  • From Finite Covariance Windows to Modeling Filters: A Convex Optimization Approach

    Christopher I. Byrnes;Sergei V. Gusev;Anders Lindquist

  • A New Algorithm for Optimal Filtering of Discrete-Time Stationary Processes

    Anders Lindquist

  • Generalized interpolation in H-infinity with a complexity constraint

    Christopher I. Byrnes;Tryphon T. Georgiou;Anders Lindquist;Alexander Megretski

  • Matrix-valued Nevanlinna-Pick interpolation with complexity constraint: an optimization approach

    A. Blomqvist;A. Lindquist;R. Nagamune

  • Cepstral coefficients, covariance lags, and pole-zero models for finite data strings

    C.I. Ryrnes;P. Enqvist;A. Lindquist

  • On Feedback Control of Linear Stochastic Systems

    Anders Lindquist

  • On the partial stochastic realization problem

    C.I. Byrnes;A. Lindquist

  • On minimal splitting subspaces and markovian representations

    Anders Lindquist;Giorgio Picci;Guy Ruckebusch

  • Theory and Applications of Nonlinear Control Systems

    Christopher I. Byrnes;Anders Lindquist

Frequent Co-Authors

Christopher I. Byrnes
Christopher I. Byrnes Washington University in St. Louis
Tryphon T. Georgiou
Tryphon T. Georgiou University of California, Irvine
Bo Wahlberg
Bo Wahlberg Royal Institute of Technology
Michel Gevers
Michel Gevers Université Catholique de Louvain
Alexey S. Matveev
Alexey S. Matveev Saint Petersburg State University
Vincent D. Blondel
Vincent D. Blondel Université Catholique de Louvain
Uwe D. Hanebeck
Uwe D. Hanebeck Karlsruhe Institute of Technology

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