UCR

Fabio Pasqualetti

Professor, University of California at Riverside

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  Year
2024 | 2023 | 2022 | 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
G. Baggio
D. S. Bassett
R. Betzel
G. Bianchin
A. Bicchi
F. Bullo
R. Carli
F. Celi
J. Cortés
F. Dörfler
A. Franchi
P. Frasca
A. Gasparri
S. Grafton
A. A. Al Makdah
S. Gu
V. Gupta
V. Katewa
V. Krishnan
J. D. Medaglia
T. Menara
S. F. Muldoon
H. Mohsenian-Rad
Y. Qin
S. Zampieri
S. Zhao
Q. Zhu

Journal Articles

  1. F. Celi and A. Allibhoy and F. Pasqualetti and J. Cortés, Linear-Threshold Dynamics for the Study of Epileptic Events. IEEE Control Systems Letters, 5:1405-1410, 2020.
  2. K. P. Szymula and F. Pasqualetti and A. M. Graybiel and T. M. Desrochers and D. S. Bassett, Habit learning supported by efficiently controlled network dynamics in naive macaque monkeys. Nature Neuroscience, 2020. Submitted. [PDF]
  3. J. Stiso and M.-C. Corsi and J. Vettel and J. Garcia and F. Pasqualetti and F. de Vico-Fallani and T. Lucas and D. S. Bassett, Learning in brain-computer interface control evidenced by joint decomposition of brain and behavior. Journal of Neural Engineering, 17(4):2020. [PDF]
  4. Y. Qin and M. Cao and B. D. O. Anderson and D. S. Bassett and F. Pasqualetti, Mediated Remote Synchronization: the Number of Mediators Matters. IEEE Control Systems Letters, 5(3):767-772, 2020. [PDF]
  5. V. Krishnan and F. Pasqualetti, Data-Driven Attack Detection for Linear Systems. IEEE Control Systems Letters, 5(2):671-676, 2020. [PDF]
  6. P. Srivastava and E. Nozari and J. Z. Kim and H. Ju and D. Zhou and C. Becker and F. Pasqualetti and D. S. Bassett, Models of communication and control for brain networks: distinctions, convergence, and future outlook. Network Neuroscience, 4(4):2020. [PDF]
  7. S. P. Patankar and J. Z. Kim and F. Pasqualetti and D. S. Bassett, Path-dependent connectivity, not modularity, consistently predicts controllability of structural brain networks. Network Neuroscience, 2020. In press. [PDF]
  8. J. K. Brynildsen and K. D. Mace and E. J. Cornblath and C. Weidler and F. Pasqualetti and D. S. Bassett and J. A. Blendy, Gene coexpression patterns predict opiate-induced brain state transitions. Proceedings of the National Academy of Sciences, 141:110277, 2020. [PDF]
  9. T. Menara and G. Baggio and D. S. Bassett and F. Pasqualetti, Conditions for Feedback Linearization of Network Systems. IEEE Control Systems Letters, 4(3):578-583, 2020. [PDF]
  10. T. M. Karrer and J. Z. Kim and J. Stiso and A. E. Kahn and F. Pasqualetti and U. Habel and D. S. Bassett, A practical guide to methodological considerations in the controllability of structural brain networks. Journal of Neural Engineering, 17(026031):2020. [PDF]
  11. Z. Cui and J. Stiso and G. L. Baum and J. Z. Kim and D. R. Roalf and R. F. Betzel and S. Gu and Z. Lu and C. H. Xia and R. Ciric and T. M. Moore and R. T. Shinohara and K. Ruparel and C. Davatzikos and F. Pasqualetti and R. E. Gur and R. C. Gur and D. S. Bassett and T. D. Satterthwaite, Optimization of Energy State Transition Trajectory Supports the Development of Executive Function During Youth. eLife, 9:e53060, 2020. [PDF]
  12. F. Pasqualetti and S. Zhao and C. Favaretto and S. Zampieri, Fragility Limits Performance in Complex Networks. Scientific Reports, 10(1774):2020. [PDF]
  13. E. Tang and G. L. Baum and D. R. Roalf and T. D. Satterthwaite and F. Pasqualetti and D. S. Bassett, Control of brain network dynamics across diverse scales of space and time. Physical Review E, 101(6):2020.
  14. R. Anguluri and V. Katewa and F. Pasqualetti, Centralized versus Decentralized Detection of Attacks in Stochastic Interconnected Systems. IEEE Transactions on Automatic Control, 65(9):3903-3910, 2020. [PDF]
  15. Y-C. Liu and G. Bianchin and F. Pasqualetti, Secure Trajectory Planning Against Undetectable Spoofing Attacks. Automatica, 112:108655, 2020. [PDF]
  16. V. Katewa and F. Pasqualetti, On the real stability radius of sparse systems. Automatica, 113:108685, 2020. [PDF]
  17. T. Menara and G. Baggio and D. S. Bassett and F. Pasqualetti, Stability Conditions for Cluster Synchronization in Networks of Heterogeneous Kuramoto Oscillators. IEEE Transactions on Control of Network Systems, 7(1):302-314, 2020. [PDF]

Conference Articles

  1. 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]
  2. G. Bianchin and F. Pasqualetti, Routing Apps May Cause Oscillatory Congestions in Traffic Networks. IEEE Conf. on Decision and Control, Jeju Island, Republic of Korea, pages 253-260, December 2020. [PDF]
  3. 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]
  4. G. Baggio and F. Pasqualetti, Learning Minimum-Energy Controls from Heterogeneous Data. American Control Conference, Denver, CO, USA, July 2020. [PDF]
  5. 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]

Book Chapters

  1. V. Katewa and C.-Z. Bai and V. Gupta and F. Pasqualetti, Detection of Attacks in Cyber-Physical Systems: Theory and Applications. Safety, security, and privacy for cyber-physical systems. Ed. by A. Teixeira and R. Ferrari. Springer Nature, 2020.

Fabio Pasqualetti - University of California at Riverside