UCR

Fabio Pasqualetti

Associate Professor, University of California at Riverside

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  Year
2021 | 2020 | 2019 | 2018 | 2017 | 2016 | 2015 | 2014 | 2013 | 2012 | 2011 | 2010 | 2009 | 2008 | 2007 | View all

  Topic
Learning for control
Cyber-physical security
Network analysis and design
Distributed control/estimation
Network neuroscience
Smart power grid
Robotic patrolling/surveillance

  Co-author
R. Anguluri
D. S. Bassett
R. Betzel
G. Bianchin
A. Bicchi
F. Bullo
R. Carli
J. Cortés
F. Dörfler
A. Franchi
P. Frasca
A. Gasparri
S. Grafton
S. Gu
V. Gupta
V. Katewa
J. D. Medaglia
T. Menara
S. F. Muldoon
H. Mohsenian-Rad
S. Zampieri
S. Zhao
Q. Zhu

Journal Articles

  1. G. Baggio and D. S. Bassett and F. Pasqualetti, Data-Driven Control of Complex Networks. Nature Communications, 12(1429):2021. [PDF]
  2. V. Krishnan and F. Pasqualetti, Data-Driven Attack Detection for Linear Systems. IEEE Control Systems Letters, 5(2):671-676, 2020. [PDF]
  3. G. Baggio and V. Katewa and F. Pasqualetti, Data-driven Minimum-Energy Controls for Linear Systems. IEEE Control Systems Letters, 3(3):589-594, 2019. [PDF]
  4. A. A. Al Makdah and V. Katewa and F. Pasqualetti, A Fundamental Performance Limitation for Adversarial Classification. IEEE Control Systems Letters, 4(1):169-174, 2019. [PDF]

Conference Articles

  1. Y. Qin and T. Menara and S. Oymak and F. Pasqualetti, Representation Learning for Stochastic Sequential Linear Bandits. IEEE Conf. on Decision and Control, Austin, TX, December 2021. Submitted.
  2. A. A. Al Makdah and V. Krishnan and F. Pasqualetti, Learning Robust Feedback Policies from Demonstrations. IEEE Conf. on Decision and Control, Austin, TX, December 2021. Submitted.
  3. A. A. Al Makdah and V. Katewa and F. Pasqualetti, Taming Adversarial Robustness via Abstaining. IEEE Conf. on Decision and Control, Austin, TX, December 2021. Submitted.
  4. V. Krishnan and F. Pasqualetti, On Direct vs Indirect Data-Driven Predictive Control. IEEE Conf. on Decision and Control, Austin, TX, December 2021. Submitted.
  5. F. Celi and G. Baggio and F. Pasqualetti, Distributed Learning of Optimal Controls for Linear Systems. IEEE Conf. on Decision and Control, Austin, TX, December 2021. Submitted.
  6. R. Anguluri and A. A. Al Makdah and V. Katewa and F. Pasqualetti, On the Robustness of Data-Driven Controllers for Linear Systems. Learning for Dynamics & Control, San Francisco, CA, USA, pages 404-412, June 2020. [PDF]
  7. G. Baggio and F. Pasqualetti, Learning Minimum-Energy Controls from Heterogeneous Data. American Control Conference, Denver, CO, USA, July 2020. [PDF]
  8. A. A. Al Makdah and V. Katewa and F. Pasqualetti, Accuracy Prevents Robustness in Perception-based Control. American Control Conference, Denver, CO, USA, July 2020. [PDF]
  9. V. Krishnan and A. A. Al Makdah and F. Pasqualetti, Lipschitz Bounds and Provably Robust Training by Laplacian Smoothing. Advances in Neural Information Processing Systems, Vancouver, Canada, pages 10924-10935, December 2020. [PDF]

Book Chapters

Fabio Pasqualetti - University of California at Riverside