I'm a post-doctoral researcher in the Quantum Information Theory group at Université de Genève. My current research focuses, mostly, in the interplays between machine learning and quantum physics, and in quantum nonlocality. In the past, I have also worked in quantum thermodynamics, and in quantum information aspects of quantum field theory.
There are a few things that you may find wandering around here:
- Computational appendices of research papers 🖥️: It is my belief that science should be open and reproducible (and that scientists shouldn't waste their time programming things that have already been programmed). Due to this, I always make an attempt to publishing the computer codes employed in each scientific publication I author. Examples of these computational appendices are triangle-quantum-nonlocality, private-tn, fullnn, rapid, quantum-networks-scalar-extension, gaussianotto, bayesian-dl-quantum (this last one, in GitLab).
- Teaching material 📚: of different lectures and courses I have taught. This is the case of teaching and BIST-Python-Bootcamp.
- Learning material 🔍: mostly in classical and quantum machine learning, developed while studying the subjects. Examples are ml-projects, qml-rg, and ebm-torch, which is a library written in Pytorch to train energy-based generative models.
- An Android app! 📱 which helped me retain sanity during 2020: contactdiary
- 📫 How to reach me: Drop me an email (this is easy to find in the web) or find me on Twitter or Mastodon.
- 😄 Pronouns: he/him
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent