I am currently a MSc Computer Science Student at ETH Zurich, where I focus on machine learning. I recently wrote my Master’s Thesis on pruning and generalization in deep neural networks in collaboration with Prof. Dr. Yarin Gal at the University of Oxford and Prof. Dr. Andreas Krause at ETH Zürich.
At ETH and at IBM Research, I undertook research on information retrieval and text classification for medical applications. Recently, I interned at BCG Gamma as a data scientist where I contributed to the development of a text classification algorithm for financial transactions. Before that, I worked at QantEv, an InsureTech start up which emerged from the Entrepreneur First programme. There, I designed and implemented optimal transport methods and contributed to the development of a web application.
Master's Thesis, 2020
University of Oxford
MSc in Computer Science, 2020
Exchange Programme, 2017
Imperial College London
BSc in Computer Science, 2017
In this project, we contributed an implementation of Boosting Black Box Variational Inference to the Pyro probabilistic programming library.
In this project we introduce low cost methods of improving dilated convolutions in an image segmentation application. We achieve comparable results to state-of-the-art segmentation performance while being computationally more efficient than previously proposed methods.
For this project we leverage matrix factorization and neural network methods to build a recommender system for movies.