# Raphaël Attias > Software Engineer L4 @ Databricks || Master in Data Science @ EPFL Location: New York, New York, United States Profile: https://flows.cv/raphal 🌟 website: raphaelattias.com ## Work Experience ### Software Engineer L4 @ Databricks Jan 2024 – Present | New York, New York, United States ### Software Engineer L3 @ Databricks Jan 2023 – Jan 2024 | Amsterdam, North Holland, Netherlands ### Visiting Postgraduate Researcher @ Harvard University Jan 2022 – Jan 2023 | Boston, Massachusetts, United States • Develop advanced Machine Learning methods to analyze slide pathology images. • Build REST API for finding regions of interest in Whole Slide Images. • Deployed API on Harvard Cluster to be called by labs and IoT devices. • Motivated Self-Supervised Learning for detecting regions of interest in an unlabeled set of slide images. • Extend the existing framework by implementing and testing Graph Neural Networks, Vision Transformers, and other state-of-the-art models using Pytorch. ### Software Developer @ University of Geneva Jan 2022 – Jan 2022 | Geneva, Switzerland • Developed in Python a web library for understanding energy needs with graph modeling. • Contributed to an existing framework by adding key features when handling networks and geodata. ### Software & Research Intern @ NEC Laboratories America, Inc. Jan 2022 – Jan 2022 | Princeton, New Jersey, États-Unis Implemented and researched the various techniques of data augmentation to improve results on a complex multi-class segmentation problem. In the Medical Machine Learning department, I motivated the use of GANs to produce new samples for cancer cell detection. ### Teacher Assistant for Machine Learning @ Ecole polytechnique fédérale de Lausanne Jan 2021 – Jan 2022 | Lausanne, Vaud, Suisse Teacher assistant for the Master class of Machine Learning CS-433 taught by Prof. Jaggi and Prof. Flammarion for more than 500 students. Graded student projects, helped write the final exam, maintained weekly TA session to provide help to the students. ### Research Assistant @ Ecole polytechnique fédérale de Lausanne Jan 2021 – Jan 2022 | Lausanne, Vaud, Switzerland Researched 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. I used D-Cliques (Bellet et al. 2021) as a recent approach to coordinate and structure a network for Decentralized Federated Learning. ### Machine Learning Intern @ Arcanite Jan 2021 – Jan 2021 | Lausanne et périphérie During this internship I had the opportunity to work on state-of-the-art deep learning models, for generating handwritten words indistinguishable from real words. I worked on reimplementing a recent research paper on cGAN by writing a understand and usable library in Pytorch Lightning. ### Machine Learning Consultant @ EnergyByte Jan 2020 – Jan 2021 | Melbourne, Victoria, Australia With my Machine Learning team we successfully deployed a CNN Model developed for the edge detection of rooftops from satellites images. This tool will be used for better understanding energy needs in Australian cities. ## Education ### Master's degree in Data Science EPFL ### Master's Thesis in Biomedical Informatics Harvard University ### Bachelor's degree in Mathematics EPFL ## Contact & Social - LinkedIn: https://linkedin.com/in/raphael-attias - Website: https://raphaelattias.com --- Source: https://flows.cv/raphal JSON Resume: https://flows.cv/raphal/resume.json Last updated: 2026-04-05