Computer Vision

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…

Towards Robust and Adaptable Diagnosis of Pneumonia from Chest X-ray Data

Visual Intelligence, 90/100, 2021 Artificial intelligence (AI) researchers and radiologists have recently reported AI systems that accurately diagnose pneumonia from a chest X-Ray images using deep neural networks when trained on a sufficient large and homogeneous amount of labelled images. However, the robustness and adaptability…

Detecting Rooftop Area for installing PV modules with Deep Learning

Machine Learning, 100/100, 2021 Won the 2nd place for best project presentation, presented at the CISBAT 2021 and published in the Journal of Physics. With Prof. Castello, we worked on Deep-learning for the detection of available for solar panel installation from satellite images. This computer…

Data Science

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…

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…

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…

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…

Federated Learning

Exploration of D-Cliques Variations and Edges Cases for Decentralized Federated Learning

Research Project, 90/100, 2021Researched the decentralized implementation of a Federated Learning algorithm in the Scalable Computing Systems Laboratory at EPFL. Supervised by Prof. Karmarec, I explored and identify the computational implications of a Decentralized approach to a state-of-the-art topology (D-Cliques) in a research environment. D-Cliques…

GANs

Towards Robust and Adaptable Diagnosis of Pneumonia from Chest X-ray Data

Visual Intelligence, 90/100, 2021 Artificial intelligence (AI) researchers and radiologists have recently reported AI systems that accurately diagnose pneumonia from a chest X-Ray images using deep neural networks when trained on a sufficient large and homogeneous amount of labelled images. However, the robustness and adaptability…

Machine Learning

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…

Exploration of D-Cliques Variations and Edges Cases for Decentralized Federated Learning

Research Project, 90/100, 2021Researched the decentralized implementation of a Federated Learning algorithm in the Scalable Computing Systems Laboratory at EPFL. Supervised by Prof. Karmarec, I explored and identify the computational implications of a Decentralized approach to a state-of-the-art topology (D-Cliques) in a research environment. D-Cliques…

Towards Robust and Adaptable Diagnosis of Pneumonia from Chest X-ray Data

Visual Intelligence, 90/100, 2021 Artificial intelligence (AI) researchers and radiologists have recently reported AI systems that accurately diagnose pneumonia from a chest X-Ray images using deep neural networks when trained on a sufficient large and homogeneous amount of labelled images. However, the robustness and adaptability…

Reinforcement Learning for moon landing in OpenGym

Artificial Neural Networks, 90/100, 2021 Artificial intelligence (AI) researchers and radiologists have recently reported AI systems that accurately diagnose pneumonia from a chest X-Ray images using deep neural networks when trained on a sufficient large and homogeneous amount of labelled images. However, the robustness and…

Detecting Rooftop Area for installing PV modules with Deep Learning

Machine Learning, 100/100, 2021 Won the 2nd place for best project presentation, presented at the CISBAT 2021 and published in the Journal of Physics. With Prof. Castello, we worked on Deep-learning for the detection of available for solar panel installation from satellite images. This computer…

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…

Medical

Towards Robust and Adaptable Diagnosis of Pneumonia from Chest X-ray Data

Visual Intelligence, 90/100, 2021 Artificial intelligence (AI) researchers and radiologists have recently reported AI systems that accurately diagnose pneumonia from a chest X-Ray images using deep neural networks when trained on a sufficient large and homogeneous amount of labelled images. However, the robustness and adaptability…

Natural Language Processing

Self-Supervised

Towards Robust and Adaptable Diagnosis of Pneumonia from Chest X-ray Data

Visual Intelligence, 90/100, 2021 Artificial intelligence (AI) researchers and radiologists have recently reported AI systems that accurately diagnose pneumonia from a chest X-Ray images using deep neural networks when trained on a sufficient large and homogeneous amount of labelled images. However, the robustness and adaptability…

A photo from Raphaël’s collection