Yannick Bouillard
About Yannick Bouillard
Yannick Bouillard is a Machine Learning Engineer with a background in Biomedical Engineering and Data Sciences. He currently works at Inria, where he develops federated learning applications to improve clinical trial studies while ensuring data protection.
Work at Inria
Yannick Bouillard has been employed at Inria as a Machine Learning Engineer since 2020. In this role, he focuses on developing and implementing machine learning solutions that address complex challenges in various domains. His work includes the deployment of federated learning applications aimed at enhancing clinical trial studies. Bouillard is involved in ensuring secure data transmission across hospital networks, utilizing established protocols to maintain data integrity and confidentiality.
Education and Expertise
Yannick Bouillard holds a degree in Biomedical Engineering from Université de Technologie de Compiègne (UTC), where he studied from 2014 to 2017. He furthered his education at CentraleSupélec, obtaining a Specialized Master in Computer Science and Data Sciences from 2018 to 2019. His academic background provides a strong foundation in both biomedical applications and data science, equipping him with the skills necessary for his current role in machine learning.
Background
Before joining Inria, Yannick Bouillard worked as a Data Scientist at Air Liquide Medical Systems for six months in 2019. His experience in this position contributed to his understanding of data analysis and its applications in the medical field. This role, combined with his educational background, has shaped his career trajectory towards machine learning and data protection in healthcare.
Achievements in Federated Learning
Yannick Bouillard has developed a federated learning application specifically aimed at enhancing clinical trial studies by leveraging data from multiple regional hospitals. He has implemented advanced data protection mechanisms, including Secure Multi-Party Computation (SMPC), differential privacy, and homomorphic encryption. These innovations are critical in ensuring the security and privacy of sensitive medical data during the analysis process.
Data Protection Mechanisms
In his role at Inria, Yannick Bouillard has been responsible for implementing robust data protection mechanisms within federated learning applications. He has utilized techniques such as Secure Multi-Party Computation (SMPC), differential privacy, and homomorphic encryption to safeguard data. Additionally, he ensures secure data transmission across hospital networks by employing protocols like SSL/TLS and WSS, which are essential for maintaining the confidentiality of patient information.