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Publications of year 2022
Books and proceedings
  1. F. Bullo and S. L. Smith. Lectures on Robotic Planning and Kinematics. Unpublished Manuscript, 2022. 
    @Book{ fb-sls:22,
author = {F. Bullo and S. L. Smith},
title = {Lectures on Robotic Planning and Kinematics},
year = 2022,
nopublisher = {Unpublished Manuscript (under contract with SIAM)},
publisher = {Unpublished Manuscript},
nonote = {To appear} 
}


Thesis
  1. K. D. Smith. Control and Estimation in Network Systems. PhD thesis, Electrical and Computer Engineering Department, University of California at Santa Barbara, December 2022. Keyword(s): Contraction Theory, Network Systems, Power Networks. 
    @PhDThesis{ kds:22,
author = {K. D. Smith},
title = {Control and Estimation in Network Systems},
school = {Electrical and Computer Engineering Department, University of California at Santa Barbara},
year = 2022,
month = dec,
pdf = {http://motion.me.ucsb.edu/pdf/phd-kds-dec22.pdf},
keywords = {Contraction Theory, Network Systems, Power Networks} 
}


Articles in journal, book chapters
  1. O. Askarisichani, F. Bullo, N. E. Friedkin, and A. K. Singh. Predictive Models for Human-AI Nexus in Group Decision-Making. Annals of the New York Academy of Sciences, 1514(1):70-81, 2022. 
    @Article{ oa-fb-nef-aks:21h,
author = {O. Askarisichani and F. Bullo and N. E. Friedkin and A. K. Singh},
title = {Predictive Models for Human-{AI} Nexus in Group Decision-Making},
journal = {Annals of the New York Academy of Sciences},
year = 2022,
volume = 1514,
number = 1,
pages = {70-81},
doi = {10.1111/nyas.14783},
nonote = {https://en.wikipedia.org/wiki/Annals_of_the_New_York_Academy_of_Sciences} 
}


  2. C. Beck, F. Bullo, G. Como, K. Drakopoulos, D. H. Nguyen, C. Nowzari, V. M. Preciado, and S. Sundaram. Special Issue on Mathematical Modeling, Analysis, and Control of Epidemics. SIAM Journal on Control and Optimization, 60(2):Si-Sii, 2022. 
    @Article{ cb-fb-etal:22b,
fullauthor = {Carolyn Beck and Francesco Bullo Giacomo Como and Kimon Drakopoulos and Dang H. Nguyen and Cameron Nowzari and Victor M. Preciado and Shreyas Sundaram},
author = {C. Beck and F. Bullo and G. Como and K. Drakopoulos and D. H. Nguyen and C. Nowzari and V. M. Preciado and S. Sundaram},
title = {Special Issue on Mathematical Modeling, Analysis, and Control of Epidemics},
year = 2022,
volume = 60,
number = 2,
pages = {Si-Sii},
journal = sicon,
doi = {10.1137/22N975470} 
}


  3. P. Cisneros-Velarde and F. Bullo. Multi-group SIS Epidemics with Simplicial and Higher-Order Interactions. IEEE Transactions on Control of Network Systems, 9(2):695-705, 2022. 
    @Article{ pcv-fb:20d,
author = {P. Cisneros-Velarde and F. Bullo},
title = {Multi-group {SIS} Epidemics with Simplicial and Higher-Order Interactions},
year = 2022,
doi = {10.1109/TCNS.2021.3124269},
journal = tcns,
volume = 9,
number = 2,
pages = {695-705},
pdf = {https://arxiv.org/pdf/2005.11404.pdf} 
}


  4. P. Cisneros-Velarde, S. Jafarpour, and F. Bullo. Contraction Theory for Dynamical Systems on Hilbert Spaces. IEEE Transactions on Automatic Control, 67(12):6710-6715, 2022. Keyword(s): Contraction Theory. 
    @Article{ pcv-sj-fb:20c,
author = {P. Cisneros-Velarde and S. Jafarpour and F. Bullo},
title = {Contraction Theory for Dynamical Systems on {Hilbert} Spaces},
journal = tac,
year = 2022,
volume = 67,
number = 12,
pages = {6710-6715},
doi = {10.1109/TAC.2021.3133270},
nofunding = {HDTRA1-19-1-0017},
pdf = {https://arxiv.org/pdf/2010.01219.pdf},
keywords = {Contraction Theory} 
}


  5. P. Cisneros-Velarde, S. Jafarpour, and F. Bullo. Distributed and Time-Varying Primal-Dual Dynamics via Contraction Analysis. IEEE Transactions on Automatic Control, 67(7):3560-3566, 2022. Keyword(s): Contraction Theory. 
    @Article{ pcv-sj-fb:19r,
author = {P. Cisneros-Velarde and S. Jafarpour and F. Bullo},
title = {Distributed and Time-Varying Primal-Dual Dynamics via Contraction Analysis},
journal = tac,
year = 2022,
volume = 67,
number = 7,
pages = {3560-3566},
pdf = {https://arxiv.org/pdf/2003.12665},
doi = {10.1109/TAC.2021.3103865},
keywords = {Contraction Theory} 
}


  6. A. Davydov, S. Jafarpour, and F. Bullo. Non-Euclidean Contraction Theory for Robust Nonlinear Stability. IEEE Transactions on Automatic Control, 67(12):6667-6681, 2022. Keyword(s): Contraction Theory. 
    @Article{ ad-sj-fb:20o,
author = {A. Davydov and S. Jafarpour and F. Bullo},
title = {{Non-Euclidean} Contraction Theory for Robust Nonlinear Stability},
journal = tac,
year = 2022,
volume = 67,
number = 12,
pages = {6667-6681},
doi = {10.1109/TAC.2022.3183966},
pdf = {https://arxiv.org/pdf/2103.12263.pdf},
keywords = {Contraction Theory} 
}


  7. R. Delabays, S. Jafarpour, and F. Bullo. Multistabilities and Anomalies in Oscillator Models of Lossy Power Grids. Nature Communications, 13:5238, 2022. 
    @Article{ rd-sj-fb:22d,
author = {R. Delabays and S. Jafarpour and F. Bullo},
title = {Multistabilities and Anomalies in Oscillator Models of Lossy Power Grids},
journal = naturecomm,
doi = {10.1038/s41467-022-32931-8},
year = 2022,
volume = 13,
pages = 5238,
pdf = {https://arxiv.org/pdf/2202.02439.pdf} 
}


  8. S. Jafarpour, P. Cisneros-Velarde, and F. Bullo. Weak and Semi-Contraction for Network Systems and Diffusively-Coupled Oscillators. IEEE Transactions on Automatic Control, 67(3):1285-1300, 2022. Keyword(s): Contraction Theory. 
    @Article{ sj-pcv-fb:19q,
author = {S. Jafarpour and P. Cisneros-Velarde and F. Bullo},
title = {Weak and Semi-Contraction for Network Systems and Diffusively-Coupled Oscillators},
journal = tac,
year = 2022,
pdf = {http://arxiv.org/pdf/2005.09774},
doi = {10.1109/TAC.2021.3073096},
volume = 67,
number = 3,
pages = {1285-1300},
keywords = {Contraction Theory} 
}


  9. S. Jafarpour, E. Y. Huang, K. D. Smith, and F. Bullo. Flow and Elastic Networks on the $n$-Torus: Geometry, Analysis and Computation. SIAM Review, 64(1):59-104, 2022. 
    @Article{ sj-eyh-kds-fb:18j,
author = {S. Jafarpour and E. Y. Huang and K. D. Smith and F. Bullo},
oldtitle = {Multistable Synchronous Power Flows: {F}rom Geometry to Analysis and Computation},
title = {Flow and Elastic Networks on the $n$-Torus: {Geometry,} Analysis and Computation},
journal = sirev,
year = 2022,
volume = 64,
number = 1,
doi = {10.1137/18M1242056},
pages = {59-104},
pdf = {https://arxiv.org/pdf/1901.11189.pdf} 
}


  10. S. Jafarpour, V. Purba, S. V. Dhople, B. B. Johnson, and F. Bullo. Singular Perturbation and Small-signal Stability for Inverter Networks. IEEE Transactions on Control of Network Systems, 9(2):979-992, 2022. 
    @Article{ sj-vp-svd-bbj-fb:17j,
author = {S. Jafarpour and V. Purba and S. V. Dhople and B. B. Johnson and F. Bullo},
title = {Singular Perturbation and Small-signal Stability for Inverter Networks},
year = 2022,
journal = tcns,
doi = {10.1109/TCNS.2021.3084444},
volume = 9,
number = 2,
pages = {979-992},
pdf = {https://arxiv.org/pdf/1902.02478.pdf},
abtract = {This paper considers the small-signal stability of electrical networks composed dominantly of three-phase grid-following inverters. We identify a suitable time-scale decomposition for the inverter dynamics and, using singular perturbation theory, we obtain an analytic sufficient condition for the small-signal stability of the network. In contrast to the alternative of performing an eigenvalue analysis of the full-order network dynamics, our analytic sufficient condition has the benefit of reducing computational complexity and yielding insights on the role of network topology and constitution as well as inverter filter and control parameters on small-signal stability. Our numerical analysis for an inverter network with radial topology validates the approach and illustrates that, in a wide parametric regime, our analytic condition coincides with the exact stability threshold.} 
}


  11. W. Liu, J. Sun, G. Wang, F. Bullo, and J. Chen. Resilient Control under Quantization and Denial-of-Service: Co-designing a Deadbeat Controller and Transmission Protocol. IEEE Transactions on Automatic Control, 67(8):3879-3891, 2022. 
    @Article{ wl-js-gw-fb-jc:21a,
title = {Resilient Control under Quantization and Denial-of-Service: Co-designing a Deadbeat Controller and Transmission Protocol},
author = {W. Liu and J. Sun and G. Wang and F. Bullo and J. Chen},
fullauthor = {Wenjie Liu and Jian Sun and Gang Wang and Francesco Bullo and Jie Chen},
year = 2022,
journal = tac,
volume = 67,
number = 8,
pages = {3879-3891},
pdf = {https://arxiv.org/abs/2103.11862},
doi = {10.1109/TAC.2021.3107145} 
}


  12. W. Mei, F. Bullo, G. Chen, J. M. Hendrickx, and F. Dorfler. Rethinking the Micro-Foundation of Opinion Dynamics: Rich Consequences of the Weighted-Median Mechanism. Physical Review Research, 4(2):023213, 2022. 
    @Article{ wm-fb-gc-jh-fd:18q,
title = {Rethinking the Micro-Foundation of Opinion Dynamics: {Rich} Consequences of the Weighted-Median Mechanism},
author = {W. Mei and F. Bullo and G. Chen and J. M. Hendrickx and F. Dorfler},
year = 2022,
journal = prr,
doi = {10.1103/physrevresearch.4.023213},
volume = 4,
number = 2,
pages = 023213,
oldabstract = {Public opinion formation faces unprecedented challenges such as radicalization, echo chambers, and opinion manipulations. Mathematical modeling plays a fundamental role in understanding how social influence shapes individuals' opinions. Although most opinion dynamics models assume that individuals update their opinions by averaging others' opinions, we point out that this taken-for-granted mechanism features a non-negligible unrealistic implication. By resolving the shortcomings of weighted averaging in the framework of cognitive dissonance theory and network games, we derive a new micro-foundation of opinion dynamics, which happens to be the weighted-median mechanism. Empirical validation indicates that the weighted-median mechanism significantly outperforms the weighted-averaging mechanism in predicting individual opinion shifts. Compared with some widely-studied averaging-based models, the weighted-median model, despite its simplicity in form, replicates more realistic features of opinion dynamics, and exhibits richer phase-transition behavior depending on more delicate and robust network structures. Our new model provides an untouched perspective on the study of opinion formation processes and broadens the applicability of opinion dynamics models.} 
}


  13. R. Ofir, F. Bullo, and M. Margaliot. Minimum Effort Decentralized Control Design for Contracting Network Systems. IEEE Control Systems Letters, 6:2731-2736, 2022. Keyword(s): Contraction Theory. 
    @Article{ ro-fb-mm:22h,
author = {R. Ofir and F. Bullo and M. Margaliot},
title = {Minimum Effort Decentralized Control Design for Contracting Network Systems},
year = 2022,
volume = 6,
pages = {2731-2736},
journal = lcss,
pdf = {https://arxiv.org/pdf/2203.10392.pdf},
keywords = {Contraction Theory},
doi = {10.1109/LCSYS.2022.3176196} 
}


  14. K. D. Smith, S. Jafarpour, and F. Bullo. Transient Stability of Droop-Controlled Inverter Networks with Operating Constraints. IEEE Transactions on Automatic Control, 67(2):633-645, 2022. 
    @Article{ kds-sj-fb:18f,
author = {K. D. Smith and S. Jafarpour and F. Bullo},
title = {Transient Stability of Droop-Controlled Inverter Networks with Operating Constraints},
journal = tac,
year = 2022,
volume = 67,
number = 2,
pages = {633-645},
pdf = {http://arxiv.org/pdf/1907.05532},
doi = {10.1109/TAC.2021.3053552} 
}


  15. K. D. Smith, S. Jafarpour, A. Swami, and F. Bullo. Topology Inference with Multivariate Cumulants: The Möbius Inference Algorithm. IEEE/ACM Transactions on Networking, 30(5):2102-2116, 2022. 
    @Article{ kds-sj-fb-as:20e,
author = {K. D. Smith and S. Jafarpour and A. Swami and F. Bullo},
title = {Topology Inference with Multivariate Cumulants: {The} {M\"obius} Inference Algorithm},
journal = {IEEE/ACM Transactions on Networking},
year = 2022,
volume = 30,
number = 5,
pages = {2102-2116},
doi = {10.1109/TNET.2022.3164336},
pdf = {https://arxiv.org/pdf/2005.07880.pdf} 
}


  16. Y. Tian, P. Jia, A. Mirtabatabaei, L. Wang, N. E. Friedkin, and F. Bullo. Social Power Evolution in Influence Networks with Stubborn Individuals. IEEE Transactions on Automatic Control, 67(2):574-588, 2022. 
    @Article{ yt-pj-am-lw-nef-fb:19c,
author = {Y. Tian and P. Jia and A. Mirtabatabaei and L. Wang and N. E. Friedkin and F. Bullo},
title = {Social Power Evolution in Influence Networks with Stubborn Individuals},
journal = tac,
year = 2022,
volume = 67,
number = 2,
pages = {574-588},
pdf = {https://arxiv.org/pdf/1901.08727.pdf},
doi = {10.1109/TAC.2021.3052485} 
}


  17. R. Yan, X. Duan, Z. Shi, Y. Zhong, and F. Bullo. Matching-Based Capture Strategies for 3D Heterogeneous Multiplayer Reach-Avoid Differential Games. Automatica, 140:110207, 2022. 
    @Article{ ry-xd-zs-yz-fb:19o,
author = {R. Yan and X. Duan and Z. Shi and Y. Zhong and F. Bullo},
title = {Matching-Based Capture Strategies for {3D} Heterogeneous Multiplayer Reach-Avoid Differential Games},
fullauthor = {Rui Yan and Xiaoming Duan and Zongying Shi and Yisheng Zhong and Francesco Bullo},
journal = automatica,
year = 2022,
volume = 140,
pages = 110207,
doi = {10.1016/j.automatica.2022.110207},
pdf = {https://arxiv.org/pdf/1909.11881} 
}


  18. R. Yan, X. Duan, Z. Shi, Y. Zhong, J. R. Marden, and F. Bullo. Policy Evaluation and Seeking for Multi-Agent Reinforcement Learning via Best Response. IEEE Transactions on Automatic Control, 67(4):1898-1913, 2022. 
    @Article{ ry-xd-zs-yz-jrm-fb:20g,
author = {R. Yan and X. Duan and Z. Shi and Y. Zhong and J. R. Marden and F. Bullo},
fullauthor = {Rui Yan and Xiaoming Duan and Zongying Shi and Yisheng Zhong and Jason R. Marden and Francesco Bullo},
title = {Policy Evaluation and Seeking for Multi-Agent Reinforcement Learning via Best Response},
journal = tac,
doi = {10.1109/TAC.2021.3085171},
year = 2022,
volume = 67,
number = 4,
pages = {1898-1913},
pdf = {https://arxiv.org/pdf/2006.09585.pdf} 
}


Conference articles
  1. V. Centorrino, F. Bullo, and G. Russo. Contraction Analysis of Hopfield Neural Networks with Hebbian Learning. In IEEE Conf. on Decision and Control, Cancun, Mexico, December 2022. Keyword(s): Contraction Theory, Neural Networks. 
    @InProceedings{ vc-fb-gr:22g,
author = {V. Centorrino and F. Bullo and G. Russo},
title = {Contraction Analysis of {Hopfield} Neural Networks with {Hebbian} Learning},
year = 2022,
month = dec,
booktitle = cdc,
address = cancun,
pdf = {http://arxiv.org/abs/2204.05382},
arxivdoi = {10.48550/arXiv.2204.05382},
doi = {10.1109/CDC51059.2022.9993009},
keywords = {Contraction Theory, Neural Networks} 
}


  2. P. Cisneros-Velarde and F. Bullo. A Contraction Theory Approach to Optimization Algorithms from Acceleration Flows. In International Conference on Artificial Intelligence and Statistics, May 2022. Keyword(s): Contraction Theory. 
    @InProceedings{ pcv-fb:21d,
author = {P. Cisneros-Velarde and F. Bullo},
title = {A Contraction Theory Approach to Optimization Algorithms from Acceleration Flows},
year = 2022,
month = may,
booktitle = {International Conference on Artificial Intelligence and Statistics},
pdf = {https://arxiv.org/pdf/2105.08832.pdf},
oldurl = {https://arxiv.org/pdf/2105.08832.pdf},
doi = {10.48550/arXiv.2105.08832},
keywords = {Contraction Theory} 
}


  3. A. Davydov, S. Jafarpour, M. Abate, F. Bullo, and S. Coogan. Comparative Analysis of Interval Reachability for Robust Implicit and Feedforward Neural Networks. In IEEE Conf. on Decision and Control, Cancun, Mexico, 2022. Keyword(s): Contraction Theory, Neural Networks. 
    @InProceedings{ ad-sj-ma-fb-sc:21z,
author = {A. Davydov and S. Jafarpour and M. Abate and F. Bullo and S. Coogan},
title = {Comparative Analysis of Interval Reachability for Robust Implicit and Feedforward Neural Networks},
year = 2022,
booktitle = cdc,
address = cancun,
pdf = {https://arxiv.org/abs/2204.00187},
doi = {10.1109/CDC51059.2022.9993217},
keywords = {Contraction Theory, Neural Networks} 
}


  4. A. Davydov, S. Jafarpour, A. V. Proskurnikov, and F. Bullo. Non-Euclidean Monotone Operator Theory with Applications to Recurrent Neural Networks. In IEEE Conf. on Decision and Control, Cancun, Mexico, December 2022. Keyword(s): Contraction Theory, Neural Networks. 
    @InProceedings{ ad-sj-avp-fb:21j,
author = {A. Davydov and S. Jafarpour and A. V. Proskurnikov and F. Bullo},
title = {Non-{Euclidean} Monotone Operator Theory with Applications to Recurrent Neural Networks},
year = 2022,
month = dec,
booktitle = cdc,
address = cancun,
arxivdoi = {10.48550/arXiv.2204.01877},
doi = {10.1109/CDC51059.2022.9993197},
keywords = {Contraction Theory, Neural Networks} 
}


  5. A. Davydov, A. V. Proskurnikov, and F. Bullo. Non-Euclidean Contractivity of Recurrent Neural Networks. In American Control Conference, Atlanta, USA, pages 1527-1534, May 2022. Keyword(s): Contraction Theory, Neural Networks. 
    @InProceedings{ ad-avp-fb:21k,
author = {A. Davydov and A. V. Proskurnikov and F. Bullo},
title = {{Non-Euclidean} Contractivity of Recurrent Neural Networks},
booktitle = acc,
address = {Atlanta, USA},
month = may,
year = 2022,
pages = {1527-1534},
keywords = {Contraction Theory, Neural Networks},
pdf = {https://arxiv.org/abs/2110.08298},
doi = {10.23919/ACC53348.2022.9867357} 
}


  6. S. Jafarpour, M. Abate, A. Davydov, F. Bullo, and S. Coogan. Robustness Certificates for Implicit Neural Networks: A Mixed Monotone Contractive Approach. In Learning for Dynamics and Control Conference, June 2022. Keyword(s): Contraction Theory, Neural Networks. 
    @InProceedings{ sj-ma-ad-fb-sc:21y,
author = {S. Jafarpour and M. Abate and A. Davydov and F. Bullo and S. Coogan},
title = {Robustness Certificates for Implicit Neural Networks: {A} Mixed Monotone Contractive Approach},
year = 2022,
month = jun,
booktitle = l4dc,
oldnote = {(accepted for oral presentation)},
oldurl = {http://arxiv.org/abs/2112.05310.pdf},
pdf = {http://arxiv.org/abs/2112.05310.pdf},
doi = {10.48550/arXiv.2112.05310},
keywords = {Contraction Theory, Neural Networks} 
}


  7. S. Jafarpour, A. Davydov, M. Abate, F. Bullo, and S. Coogan. Robust Training and Verification of Implicit Neural Networks: A Non-Euclidean Contractive Approach. In ICML Workshop on Formal Verification of Machine Learning, July 2022. Keyword(s): Contraction Theory. 
    @InProceedings{ sj-ad-ma-fb-sc:22m,
author = {S. Jafarpour and A. Davydov and M. Abate and F. Bullo and S. Coogan},
title = {Robust Training and Verification of Implicit Neural Networks: A Non-{Euclidean} Contractive Approach},
year = 2022,
month = jul,
booktitle = {ICML Workshop on Formal Verification of Machine Learning},
doi = {10.48550/arXiv.2208.03889},
keywords = {Contraction Theory},
oldurl = {https://icml.cc/virtual/2022/workshop/13473} 
}


  8. K. D. Smith, F. Seccamonte, A. Swami, and F. Bullo. Physics-Informed Implicit Representations of Equilibrium Network Flows. In Advances in Neural Information Processing Systems, November 2022. Keyword(s): Contraction Theory. 
    @InProceedings{ kds-fs-as-fb:21n,
author = {K. D. Smith and F. Seccamonte and A. Swami and F. Bullo},
title = {Physics-Informed Implicit Representations of Equilibrium Network Flows},
year = 2022,
month = nov,
booktitle = neurips,
keywords = {Contraction Theory},
github = {https://github.com/KevinDalySmith/implicit-flow-networks},
pdf = {https://openreview.net/pdf?id=PPlAVQDeL6} 
}


Internal reports
  1. S. Mohagheghi, J. Ma, and F. Bullo. Stable and Efficient Structures in Multigroup Network Formation. Technical report, May 2022. 
    @TechReport{ sm-jm-fb:19i,
author = {S. Mohagheghi and J. Ma and F. Bullo},
title = {Stable and Efficient Structures in Multigroup Network Formation},
year = 2022,
month = may,
pdf = {https://arxiv.org/pdf/2001.10627.pdf} 
}


Miscellaneous
  1. G. De Pasquale, K. D. Smith, F. Bullo, and M. E. Valcher. Dual Seminorms, Ergodic Coefficients, and Semicontraction Theory, 2022. Note: Available at http://arxiv.org/abs/2201.03103. Keyword(s): Contraction Theory. 
    @Misc{ gdp-kds-fb-mev:21m-arxiv,
author = {G. {De~Pasquale} and K. D. Smith and F. Bullo and M.~E. Valcher},
title = {Dual Seminorms, Ergodic Coefficients, and Semicontraction Theory},
note = {Available at \ {http://arxiv.org/abs/2201.03103}},
year = 2022,
keywords = {Contraction Theory} 
}


  2. K. D. Smith. High-Order Tomography, 2022. 
    @Misc{ kds:22,
author = {K. D. Smith},
title = {High-Order Tomography},
year = 2022 
}


  3. W. Ye, F. Bullo, N. E. Friedkin, and A. K. Singh. Modeling Human-AI Team Decision Making, 2022. Note: Available at http://arxiv.org/abs/2201.02759. 
    @Misc{ wy-fb-nef-aks:22w-old,
author = {W. Ye and F. Bullo and N. E. Friedkin and A. K. Singh},
title = {Modeling Human-{AI} Team Decision Making},
note = {Available at \ {http://arxiv.org/abs/2201.02759}},
year = 2022,
doi = {10.48550/arXiv.2201.02759} 
}



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