- R&D of new algorithms (machine learning and deep learning) to improve our products.- Medical Image Processing and Labelling.- Exploratory Data Analysis, Data Cleaning, and Data Preprocessing.- Analysis and Development of clinical studies.- Integration of our products in real clinical workflows.

I compared state-of-the-art deep generative models (deep learning) for image generation. This ended up being my Bachelor Thesis. The models used in the comparison: autoregressive, flow-based, GANs, and VAEs. One can find the pytorch code on my personal Github.

I helped them with basic data science techniques: optimization of stock, prediction of prices, etc. We used very simple regression and classification models such as random forests, logistic regression, support vector machines, etc.

I taught classes of around 30 industrial engineering students: geometry, linear algebra, and calculus.