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Home / Nathalie Risso

Nathalie Risso

Short Bio

Nathalie Risso received her B.S. Degree in Electronics Engineering from Universidad de Concepcion, Chile, in 2007, and her M.S. Degree in Electrical and Computer Engineering from the University of Arizona, in 2015.  She is currently a Ph.D. candidate in Electrical and Computer Engineering in the area of control systems at the University of Arizona. Her research interests include control systems design, cyber-physical systems and system identification.

 

 

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Recent Publications

  • Model Predictive Control of Hybrid Dynamical Systems
  • Traffic Density with Multi-Mode Control Barrier Functions at Scale
  • Uncertainty-Aware Resource Allocation for Multi-Path Programs with In-Kernel Predictions
  • Neural Hybrid Equations: Models, Basic Properties, and Approximation Results
  • A Hybrid Systems Model of Feedback Optimization for Linear Systems: Convergence and Robustness
  • On Input-to-State Stability for a Class of Stochastic Hybrid Systems
  • Observer Design for Hybrid Systems with Partially Affine Forms and Known Jump Times: Applications to Walking Robots
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News

  • Promoted to Full Professor!
  • Our journal article "Forward Invariance of Sets for Hybrid Dynamical Systems" was published in IEEE Transactions on Automatic Control in 2018 as Full Paper

    New Journal Article

  • Jun Chai receives a PhD from the University of California, Santa Cruz
  • Dawn Hustigs-Schultz receives 2018 ARCS Foundation Fellowship
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Disclaimer

Research supported by NSF, ARO, AFOSR, Mathworks, and Honeywell.  Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the funding sources.

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