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Vision Transformers for Analyzing High-Resolution Pathology Images

Master Thesis Transformers are powerful models that can capture long-range dependencies between data using an attention mechanism. However, applying transformers to medical problems poses challenges due to the high-resolution and complexity of pathology images, as well as the scarcity and noise of labels. In this…

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Movie Recommendation System in Spark for Big Data

Systems for Data Science, 100/100, 2021 Developed and deployed a movie recommendation system in Scala with Spark. The movie recommender is modeled with an approximate k-NN system that can predict efficiently over several machines the best movie for a user. The personalized recommender is implemented…

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Robust Journey Planning for CFF Zurich

Labs in Data Science, 100/100, Best Class Project, 2021 Developed and deployed a journey planner using Spark to compute and visualize the best transportation and path using Zurich Transportation System. Using CFF data, we built a predictive model that solved efficiently the transportation problem. Given…

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Higgs Boson Challenge: Prediction of generated Higgs Bosons

Machine Learning, 100/100, 2020 The task of the Challenge was to predict whether a collision event can generate a Higgs boson, an elementary particle in the Standard Model of physics, or not. In fact, scientists cannot really observe this particle, but only its decay signature…

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A photo from Raphaël’s collection