Alexandre P.

Background

About Alexandre P.

I have always felt a keen interest in the tremendous advance Nature has upon us and in how it could be mimicked to enhance our technologies. How do we learn? How do we memorize? How complex thoughts emerge from such a structure? What are the underlying mechanisms of the super-efficiency of our brains? After graduating in Applied Mathematics from Centrale Paris (newly CentraleSupélec) where I specialized in Machine Learning/Optimization/Signal processing (see detail below), I decided to do a PhD in computational neurosciences. During my 3 years of PhD at MIND (Inria), I leveraged the ability of large language models to build meaningful representations of words to better understand how the human brain processes language. I have developed a profound expertise in Machine/Deep Learning models, encompassing their design, implementation, and training. I have successfully worked with various models including GloVe, LSTM, transformers, and diffusion models. Moreover, I possess a comprehensive understanding of the entire pipeline, from initial design to seamless implementation and deployment.