1. F. Bullo. Contraction Theory for Dynamical Systems. Kindle Direct Publishing, 1.3 edition, 2026. ISBN: 979-8836646806. [bibtex-entry]

1. S. Betteti. Associative Memory and Recurrent Neural Networks: A Dynamical Systems Approach. PhD thesis, Information Engineering Department, Università di Padova, Italy, February 2026. Keyword(s): Contraction Theory, Network Systems, Machine Learning, Neural Networks, Theoretical Neuroscience. [bibtex-entry]

1. L. Cothren, F. Bullo, and E. Dall'Anese. Online Feedback Optimization and Singular Perturbation via Contraction Theory. SIAM Journal on Control and Optimization, 2026. Note: To appear. Keyword(s): Contraction Theory. [bibtex-entry]



2. E. M. H. Ekanayake, A. R. Venkatakrishnan, F. Bullo, and N. Shukla. Mind the Gap: Where Analog Ising Machines Cease to Minimize the Ising Hamiltonian. Technical Report, 2026. Note: Submitted. [bibtex-entry]



3. Y. Kawano, S. Betteti, A. Davydov, and F. Bullo. Incremental input-to-state stability and equilibrium tracking for stochastic contracting dynamics. IEEE Transactions on Automatic Control, 2026. Note: Submitted. Keyword(s): Contraction Theory. [bibtex-entry]



4. Y. Kawano and F. Bullo. Contraction Theory for Incremental Input-to-State Stability. Automatica, 2026. Note: Submitted. Keyword(s): Contraction Theory. [bibtex-entry]



5. Y. Kawano and F. Bullo. Contractivity of Multi-Stage Runge--Kutta Dynamics. Automatica, 2026. Note: Submitted. Keyword(s): Contraction Theory. [bibtex-entry]



6. R. Ofir, F. Bullo, and M. Margaliot. A Sufficient Condition for 2-Contraction of a Feedback Interconnection. IEEE Transactions on Automatic Control, 71(2):1207-1214, 2026. Keyword(s): Contraction Theory. [bibtex-entry]



7. A. Ogranovich, T. Guo, A. R. Venkatakrishnan, M. Shapiro, F. Bullo, and F. Pasqualetti. Oscillator-Based Associative Memory with Exponential Capacity: Theory, Algorithms, and Hardware Implementation. IEEE Transactions on Control of Network Systems, March 2026. [bibtex-entry]



8. A. V. Proskurnikov and F. Bullo. Regular Pairings for Non-Quadratic Lyapunov Functions and Contraction Analysis. SIAM Journal on Control and Optimization, 64(1):496-521, 2026. Keyword(s): Contraction Theory. [bibtex-entry]

1. V. Centorrino, F. Rossi, F. Bullo, and G. Russo. Proximal Gradient Dynamics and Feedback Control for Equality-Constrained Composite Optimization. In European Control Conference, Reykjavík, Iceland, July 2026. Note: To appear. [bibtex-entry]



2. E. Demirci, F. Bullo, A. Swami, and A. K. Singh. FlowSymm: Physics Aware, Symmetry Preserving Graph Attention for Network Flow Completion. In International Conference on Learning Representations, 2026. Note: To appear. [bibtex-entry]



3. Z. Marvi, F. Bullo, and A. G. Alleyne. Safe Control of Sampled-Data Systems via Discretized Parametric Contracting Dynamics. In American Control Conference, New Orleans, LA, May 2026. Note: To appear. [bibtex-entry]



4. A. N. Montanari, F. Bullo, D. Krotov, and A. E. Motter. Energy-Based Dynamical Models for Neurocomputation, Learning, and Optimization. In American Control Conference, New Orleans, LA, May 2026. [bibtex-entry]



5. A. K. Musaffar, A. Gokhale, S. Zeng, R. Tadayon, X. Yan, A. K. Singh, and F. Bullo. Learning to Lie: Adversarial Attacks on Human-AI Teams and LLMs. In International Conference on Learning Representations, 2026. Note: To appear. [bibtex-entry]

1. A. K. Musaffar, A. K. Singh, and F. Bullo. Detection of Adversarial Intent in Human-AI Teams Using LLMs. ICLR Workshop - From Human Cognition to AI Reasoning: Models, Methods, and Applications, April 2026. [bibtex-entry]

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