Saber Jafarpour

Research Assistant Professor
Department of Electrical, Computer, and Energy Engineering
University of Colorado Boulder
Email:
saber.jafarpour@colorado.edu

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I am currently a Research Assistant Professor at the University of Colorado Boulder. Before that, I was a Postdoctoral Research Fellow in the Decision and Control Laboratory at the Georgia Institute of Technology working with Sam Coogan and a Postdoctoral Research Fellow with the Center for Control, Dynamical Systems, and Computation at the University of California, Santa Barbara, working with Francesco Bullo. I did my PhD in the Department of Mathematics and Statistics at Queen's University under supervison of Andrew Lewis.


Links: Google Scholar, Scopus, IEEE Xplore,
Orcid ID: 0000-0002-7614-2940,
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News:

  • July 2023: Our paper Contraction-guided adaptive partitioning for reachability analysis of neural network controlled systems is accepted for presentation at 62th IEEE Conference on Decision and Control in Marina Bay Sands, Singapore!

  • Mar. 2023: Our paper Interval Reachability of Nonlinear Dynamical Systems with Neural Network Controllers is accepted at 5th Annual Learning for Dynamics and Control Conference (L4DC)!

  • Oct. 2022: Our preprint Monotonicity and contraction on polyhedral cones is available on arXiv!

  • Aug. 2022: Our recent preprint on "network critical slowing down" is available on arXiv: Network critical slowing down: Data-driven detection of critical transitions in nonlinear networks. This is a joint work with Mohammad Pirani.

  • Aug. 2022: Our paper Comparative Analysis of Interval Reachability for Robust Implicit and Feedforward Neural Networks is accepted for presentation at 61th IEEE Conference on Decision and Control in Cancun, Mexico!

  • Aug. 2022: Our paper Non-Euclidean Monotone Operator Theory with Applications to Recurrent Neural Networks is accepted for presentation at 61th IEEE Conference on Decision and Control in Cancun, Mexico!

  • Jun. 2022: Our paper Robust Training and Verification of Implicit Neural Networks: a non-Euclidean Contractive Approach is accepted for poster presentation at the ICML workshop on Formal Verification of Machine Learning (WFVML 2022) in Baltimore, Maryland!

  • Mar 2022: Our work Robustness Certificates for Implicit Neural Networks: A Mixed Monotone Contractive Approach is accepted at 4th Learning for Dynamics and Control Conference (Oral Presentation: Top 10 precent of submitted papers)

  • Jan 2022: Our work Resilience of Input Metering in Dynamic Flow Networks is accepted for presentation at 2022 American Control Conference (ACC) in Atlanta!

  • Sep 2021: Our paper, Robust Implicit Networks via Non-Euclidean Contractions is accepted in NeurIPS 2021!.

  • Jul 2021: Our paper, Distributed and Time-Varying Primal-Dual Dynamics via Contraction Analysis, is accepted for publication in IEEE Transactions on Automatic Control.

  • Jul 2021: Our paper, From Contraction Theory to Fixed Point Algorithms on Riemannian and non-Euclidean Spaces, is accepted for 60th IEEE Conference on Decision and Control!

  • Apr 2021: We posted two manuscripts on arXiv: Non-Euclidean Contraction Theory for Robust Nonlinear Stability and Non-Euclidean Contraction Theory for Monotone and Positive Systems.

  • Apr 2021: Our paper, Flow and Elastic Networks on the n-Torus: Geometry, Analysis and Computation, is accepted for publication in SIAM Review, Research Spotlight.

  • Mar 2021: Our paper, Singular Perturbation and Small-signal Stability for Inverter Networks, is accepted for publication in IEEE Transactions on Control of Network Systems.

  • Mar 2021: Our paper, Weak and Semi-Contraction for Network Systems and Diffusively-Coupled Oscillators, is accepted for publication in IEEE Transactions on Automatic Control.