My name is Luiz Chamon. I am a postdoc at the Simons Institute of the University of California, Berkeley. I study the theoretical underpinnings of constrained learning and its applications in signal processing, control, and machine learning.
I will be starting my own research group at the ELLIS-SimTech unit of the University of Stuttgart in October 2022. More information on projects soon, but if you're interested in working with me: let me know!
May 30th, 2022 – I will be moving to the University of Stuttgart in October 2022.
May 15th, 2022 – "Probabilistically Robust Learning: Balancing Average- and Worst-case Performance" was accepted at ICML 2022 (arXiv).
April 27th, 2022 – I gave a talk on Learning under requirements at the ELLIS-SimTech unit of the University of Stuttgart [youtube].
Feb 4th, 2022 – I was invited to participate of Caltech's 2022 Young Investigators Lecture series. My talk is scheduled for April 7th.
Feb 3rd, 2022 – "Safe policies for reinforcement learning via primal-dual methods" was accepted for publication on the IEEE TAC (paper).
December 10th, 2021 – New preprint: "Transferability properties of graph neural networks" (arXiv).
September 29th, 2021 – "Adversarial Robustness with Semi-Infinite Constrained Learning" was accepted at NeurIPS 2021 (arXiv).
August 24th, 2021 – "Graphon signal processing" was published on the IEEE TSP (paper).
July 1st, 2021 – I am joining UC Berkeley as a postdoc of the Collaboration on the Theoretical Foundations of Deep Learning.
April 1st, 2021 – I will be giving an invited seminar at Microsoft Research.
March 23rd, 2021 – "Approximately supermodular scheduling subject to matroid constraints" was accepted for publication in IEEE TAC (arXiv).
March 10th, 2021 – New preprint: "Constrained learning with non-convex losses" (arXiv).
February 26th, 2021 – New papers accepted at ACC 2021:
February 25th, 2021 – New preprint: "State augmented constrained reinforcement learning: Overcoming the limitations of learning with rewards" (arXiv).
February 1st, 2021 – I will be giving an invited seminar at the Massachusetts Institute of Technology (EECS).
January 8th, 2021 – I will be giving an invited seminar at the Johns Hopkins Mathematical Institute for Data Science (MINDS).
January 6th, 2021 – I will be giving an invited seminar at the Toyota Technological Institute at Chicago (TTIC).
December 15th, 2020 – Check out my papers at IEEE CDC this week:
December 5th, 2020 – Check out my papers at NeurIPS next week:
December 3rd, 2020 – I've released the first version of csl, a python package for constrained learning. You can get the package on GitHub and check out applications in fairness and robustness in the documentations.
April 1st, 2020 – New preprint: "Graphon signal processing" submitted to IEEE TSP (arXiv).
March 20th, 2020 – "Functional nonlinear sparse models" was accepted for publication on IEEE TSP (arXiv).
February 7th, 2020 – Patent "Sparse cascaded-integrator-comb filters" with Analog Devices is out.
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