Research interestsWithin the framework of my employement at LSU Health New Orleans, I am currently focusing my research on CA1 pyramidal neurons, and performing simulations in collaboration with experimentalists who make measurements on rat cells. The goal is to build a neuron model that reproduces the mechanisms taking place in the real neurons, and be able to make predictions on the response of rat neurons to various stimulii. For this, I use the Neuron software which provides a simulation environment for modeling networks of neurons.
When I was a PhD student, my research focused on the study of strongly correlated systems, such as high-temperature superconductors and ultra-cold atomic gases on optical lattices. These systems can be described by different forms of the Hubbard model. I specialized in exact simulations of this Hubbard model using quantum Monte Carlo (QMC) methods, in particular the SGF algorithm that I developed. I occasionally write SGF codes for my collaborators or use them myself to study some models of current interest.
I am also interested in Machine Learning, in particular Neural Networks and Reinforcement Learning. Machine Learning has broad applications, ranging from producing unbeatable computer chess players to predicting the Stock Market. My goal is to try to find ways of using Machine Learning in order to solve some Hubbard models that are currently impossible to solve exactly with other methods. As an illustration of Machine Learning, check my video where I designed and programmed a simple robot that learns how to crawl.
I am also insterested in the foundations of Electromagnetism, Special and General Relativity, Quantum Mechanics, and the search of a unifying theory.
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