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John Baillieul

· Distinguished Professor (ME, SE Appointed, ECE)

Boston University · Aeronautics and Astronautics

Active 1971–2025

h-index37
Citations8.0k
Papers33684 last 5y
Funding$100k

Academic metrics are sourced from OpenAlex and public funding records; values may differ from Google Scholar.

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About

John Baillieul has held professorial appointments in three departments at Boston University: Aerospace/Mechanical Engineering, Electrical and Computer Engineering, and Manufacturing Engineering. He is a past Chairman of Aerospace/Mechanical Engineering and also past Chairman of the Department of Manufacturing Engineering. He has served as Associate Dean for Academic Programs in the Boston University College of Engineering. After receiving his Ph.D. from Harvard University in 1975, he joined the Mathematics Department of Georgetown University. He was the Vinton Hayes Visiting Scientist in Robotics at Harvard University during the academic year 1983-84 and a visiting scientist in the Department of Electrical Engineering at MIT in 1991. Professor Baillieul has been an active member of the IEEE Control Systems Society for many years, serving in various editorial and leadership roles including Editor-in-Chief of the IEEE Transactions on Automatic Control for six years from 1992 through 1998, and holding positions such as Vice-President for Technical Activities, Vice-President for Publications, and President of the IEEE Control Systems Society. At the corporate IEEE level, his service has included roles such as TAB Transactions Chair, member at large of the Publications Services and Products Board, Chair of the PSPB Strategic Planning Committee, Chair of the PSPB Finance Committee, and IEEE Vice President of Publication Services and Products for 2007 and 2008. John Baillieul's…

Research topics

  • Computer Science
  • Artificial Intelligence
  • Information Retrieval
  • World Wide Web
  • Mathematics
  • Applied mathematics
  • Data science
  • Financial economics
  • Economics
  • Library science

Selected publications

  • Encyclopedia of Systems and Control

    Springer eBooks · 2021 · 144 citations

    1st authorCorresponding
  • Visual Navigation Using Sparse Optical Flow and Time-to-Transit

    2022 International Conference on Robotics and Automation (ICRA) · 2022 · 7 citations

    Senior authorCorresponding

    Drawing inspiration from biology, we describe the way in which visual sensing with a monocular camera can provide a reliable signal for navigation of mobile robots. The work takes inspiration from the classic paper [3] which described a behavioral strategy pursued by diving sea birds based on a visual cue called time-to-contact. A closely related concept of time-to-transit, <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\tau$</tex> , is defined, a…

  • Proportional-Integral-Derivative Control

    Encyclopedia of Systems and Control · 2021 · 4 citations

    1st authorCorresponding
  • Neuromimetic Linear Systems — Resilience and Learning

    2022 IEEE 61st Conference on Decision and Control (CDC) · 2022-12-06 · 3 citations

    articleSenior author

    Building on our recent work on neuromimetic control theory, new results on resilience and neuro-inspired quantization are reported. The term neuromimetic refers to the models having features that are characteristic of the neurobiology of biological motor control. As in previous work, the focus is on what we call overcomplete linear systems that are characterized by larger numbers of input and output channels than the dimensions of the state. The specific contributions of the present paper includ…

  • Koopman-based Deep Learning for Nonlinear System Estimation

    2024-12-16 · 2 citations

    articleSenior author

    Nonlinear differential equations are encountered as models of fluid flow, spiking neurons, and many other systems of interest in the real world. Common features of these systems are that their behaviors are difficult to describe exactly and invariably unmodeled dynamics present challenges in making precise predictions. In this paper, we present a novel data-driven linear estimator based on Koopman operator theory to extract meaningful finite-dimensional representations of complex non-linear syst…

Recent grants

Frequent coauthors

  • Thomas Siegert

    University of West Florida

    144 shared
  • Gianluca Setti

    King Abdullah University of Science and Technology

    143 shared
  • Mary Ward-Callan

    Institute of Electrical and Electronics Engineers

    143 shared
  • Dawn Melley

    131 shared
  • Konstantinos Karachalios

    Institute of Electrical and Electronics Engineers

    129 shared
  • Karen Hawkins

    Xi'an Jiaotong University

    125 shared
  • Kevin Lisankie

    Institute of Electrical and Electronics Engineers

    113 shared
  • Vaishali Damle

    113 shared

Education

  • Ph.D., Electrical Engineering and Computer Science

    Massachusetts Institute of Technology

    1990
  • M.S., Electrical Engineering and Computer Science

    Massachusetts Institute of Technology

    1985
  • B.S., Electrical Engineering and Computer Science

    University of California, Berkeley

    1983

Awards & honors

  • Fellow, International Federation of Automatic Control (IFAC)…
  • Fellow, Society for Industrial and Applied Mathematics (SIAM…
  • Inaugural recipient of the BU Charles DeLisi Award (2008)
  • Fellow, IEEE (1993)

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