Research Areas
My research interests span a variety of topics and disciplines, from tensor network algorithms (e.g., multiscale entanglement renormalization ansatz, projected entangled-pair states) for efficiently computing characteristics of quantum many-body systems, to leveraging artificial intelligence for the reconstruction of sparsely sampled, low-energy quantum many-body wavefunctions, to highly parallelized computational models of the plasma interaction between Jupiter’s moons and the Jovian magnetospheric plasma. Recently, I’ve also been exploring how to use custom deep learning protocols, NLP models, and big data from social media platforms to generate sentiment classification tools and investment-related trade signals for publicly traded companies.
Please select one of the links below to learn more about my work in a particular subject:
Idea classification (forthcoming)