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Applied Mathematician | Software Engineer

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Short bio

Born in Uruguay (Montevideo, 1988), I graduated in Physics from Univ. de la República (Facultad de Ciencias), and in Electrical Engineering (Facultad de Ingeniería). I moved to France for a PhD in Mathematics and Informatics (Univ. Joseph Fourier), writing a thesis on the quantum random walk, a mathematical model of particular interest in Quantum Computing, under the supervision of Pablo Arrighi and Alain Joye.

I'm a former post-doc researcher at VERIMAG laboratory of Université Grenoble Alpes (2016-2017) under the supervision of Oded Maler and Goran Frehse. VERIMAG is a leading French research center in embedded systems, which include avionics/aeronautics, space, transport, automotive, telecommunications, smart cards and consumer electronics domains.

Interests

I'm passionate about Applied Mathematics, Mathematical Engineering and Modeling and Simulations.

In particular, I focus on developing innovative numerical tools that impact decisions regarding reliability, correctness and safety of systems. I specialize on formal verification of Cyber-Physical Systems (CPS), hybrid dynamical systems, correct-by-design systems, and robustness analysis of neural networks. Besides, I'm also interested in applied category theory for the engineering sciences.

You can find a list of my publications following this link.

Contact

You can chat with me in Gitter, Discourse, Slack, Zulip. My email is mforets at gmail.com.


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Marcelo Forets's Projects

carlin icon carlin

Carleman linearization of polynomial differential equations in SageMath.

cddlib.jl icon cddlib.jl

cdd wrapper module for Julia. cdd is a library for polyhedra manipulation such as double description and Fourier-Motzkin elimination

cheatcube icon cheatcube

A linux commands cheatsheet that can be folded as a cube.

cursoanle icon cursoanle

Notas del Curso "Análisis No Lineal de Estructuras" de la Facultad de Ingeniería, Universidad de la República

diffequncertainty.jl icon diffequncertainty.jl

Uncertainty quantification for scientific machine learning (SciML) and differential equations

escritoire icon escritoire

sandbox for numerical experiments, code snippets, notebooks, ...

expokit.jl icon expokit.jl

Julia implementations of some routines contained in EXPOKIT

fastexpm.jl icon fastexpm.jl

Implementation of a fast exponential matrix for large matrices (full and sparse)

fnc icon fnc

Fundamentals of Numerical Computation text (Julia version)

fourieranalysis.jl icon fourieranalysis.jl

A Julia package for the Fourier analysis of Multivariate Data in the Frequency and Time-Frequency Domain

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