I'm a master student in Data Science currently researching matrix/tensor factorization methods for learning latent spaces and their applications in uncovering patterns of genetic variation and gene expression in multiple human tissues. Before I started working on my thesis I attended courses on data analysis, machine learning, data mining, deep learning, reinforcement learning, statistical methods and mathematics. Recently I also participated in Google Summer of Code 2020 where I expanded the unumpy library, a generic backend system for the core NumPy API specification.

I would like to use the skills that I've learned so far to help in projects that can have a positive impact, while also improving those skills.