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Jeremy Coulson

Jeremy Coulson

Mark and Jenny Brandemuehl Assistant Professor
gscholar website
lab website

Jeremy Coulson is an Assistant Professor in Electrical and Computer Engineering at the University of Wisconsin–Madison. He received his PhD from the Automatic Control Laboratory at ETH Zurich in 2022. He received his MASc in Mathematics & Engineering in 2017 and his B.Sc.Eng degree in Mechanical Engineering & Applied Mathematics in 2015, both from Queen’s University.

His research interests lie at the intersection of control, systems theory, and optimization while addressing important engineering challenges in domains ranging from robotics to energy systems. In particular, he is interested in data-driven control, where he studies fundamental questions arising when using data for modelling, prediction, control, and decision-making for complex systems

Department

Electrical & Computer Engineering

Contact

2554, Engineering Hall
1415 Engineering Dr
Madison, WI
p: (608) 890-3593

  • PhD 2022, ETH Zurich
  • MASc 2017, Queen’s University
  • BASc 2015, Queen’s University

  • systems and control theory
  • data-driven control
  • optimization
  • machine learning
  • robotics

  • 2022 IEEE Control Systems Society Swiss Chapter, Best Young Author Journal Paper Award
  • 2022 ETH-Zurich, ETH Medal (awarded for outstanding doctoral thesis)
  • 2022 ETH-Zurich, KITE Award (top 3 finalist)
  • 2019 European Control Conference, Best Student Paper Award
  • 2017 NSERC, NSERC PGS-D
  • 2016 Queen's University, Herman K. Walter Graduate Award
  • 2016 Queen's University, Christopher Knapper Award (Nominated)
  • 2016 Ontario Graduate Scholarship
  • 2015 Applied Mathematics and Engineering program, Queen's University, Keyser Prize
  • 2015 Queen's University, NSERC Alexander G. Bell Canada Graduate Scholar
  • 2015 Tri-Council Recipient Recognition Award
  • 2014 Applied Mathematics and Engineering, Queen's University, Nellie & Ralph Jeffery Award in Mathematics

  • Berberich, J., Iannelli, A., Padoan, A., Coulson, J., D"orfler, Florian,, & Allg"ower, Frank, (2023). A quantitative and constructive proof of Willems' fundamental lemma and its implications. In 2023 American Control Conference (ACC) (pp. 4155–4160).
  • Padoan, A., Coulson, J., & D"orfler, Florian, (2023). Controller implementability: a data-driven approach. In 2023 62nd IEEE Conference on Decision and Control (CDC) (pp. 6098–6103).
  • Padoan, A., Coulson, J., van Waarde, H. J., Lygeros, J., & D"orfler, Florian, (2022). Behavioral uncertainty quantification for data-driven control. In 2022 IEEE 61st Conference on Decision and Control (CDC) (pp. 4726–4731).
  • Coulson, J., van Waarde, H. J., Lygeros, J., & D"orfler, Florian, (2022). A quantitative notion of persistency of excitation and the robust fundamental lemma. IEEE Control Systems Letters, 7, 1243--1248.
  • D"orfler, Florian,, Coulson, J., & Markovsky, I. (2022). Bridging direct and indirect data-driven control formulations via regularizations and relaxations. IEEE Transactions on Automatic Control, 68(2), 883--897.
  • Didier, A., Parsi, A., Coulson, J., & Smith, R. S. (2021). Robust adaptive model predictive control of quadrotors. In 2021 European Control Conference (ECC) (pp. 657–662).
  • Elokda, E., Coulson, J., Beuchat, P. N., Lygeros, J., & D"orfler, Florian, (2021). Data-enabled predictive control for quadcopters. International Journal of Robust and Nonlinear Control, 31(18), 8916--8936.
  • Huang, L., Coulson, J., Lygeros, J., & D"orfler, Florian, (2021). Decentralized data-enabled predictive control for power system oscillation damping. IEEE Transactions on Control Systems Technology, 30(3), 1065--1077.
  • Coulson, J., Lygeros, J., & D"orfler, Florian, (2021). Distributionally robust chance constrained data-enabled predictive control. IEEE Transactions on Automatic Control, 67(7), 3289--3304.
  • Huang, L., Coulson, J., Lygeros, J., & D"orfler, Florian, (2019). Data-enabled predictive control for grid-connected power converters. In 2019 IEEE 58th Conference on Decision and Control (CDC) (pp. 8130–8135).

  • COMP SCI 524 - Introduction to Optimization (Spring 2025)
  • E C E 399 - Independent Study (Spring 2025)
  • E C E 524 - Introduction to Optimization (Spring 2025)
  • E C E 699 - Advanced Independent Study (Spring 2025)
  • E C E 790 - Master's Research (Spring 2025)
  • E C E 890 - Pre-Dissertator's Research (Spring 2025)
  • I SY E 524 - Introduction to Optimization (Spring 2025)
  • E C E 399 - Independent Study (Fall 2024)
  • E C E 717 - Linear Systems (Fall 2024)
  • E C E 790 - Master's Research (Fall 2024)
  • E C E 890 - Pre-Dissertator's Research (Fall 2024)
  • E C E 790 - Master's Research (Summer 2024)
  • E C E 399 - Independent Study (Spring 2024)
  • E C E 699 - Advanced Independent Study (Spring 2024)
  • E C E 790 - Master's Research (Spring 2024)
  • E C E 821 - Optimal Control and Variational Methods (Spring 2024)
  • E C E 399 - Independent Study (Fall 2023)
  • E C E 699 - Advanced Independent Study (Fall 2023)
  • E C E 717 - Linear Systems (Fall 2023)
  • E C E 890 - Pre-Dissertator's Research (Fall 2023)