Nathan Bigaud
About Nathan Bigaud
Nathan Bigaud is a Junior Researcher specializing in Federated Learning at Inria, where he investigates privacy attacks in cross-silo federated learning systems. He holds multiple master's degrees in fields such as Econometrics, Artificial Intelligence, and International Political Economy, and has worked in various research and consulting roles across Europe and Africa.
Work at Inria
Nathan Bigaud has been employed at Inria as a Junior Researcher in the field of Federated Learning since 2022. His research focuses on investigating privacy attacks specifically within cross-silo federated learning systems. He works under the supervision of Aurélien Bellet and Marc Tommasi at the INRIA Magnet Lab. His role involves exploring innovative solutions to enhance privacy and security in federated learning frameworks.
Education and Expertise
Nathan Bigaud has a diverse educational background. He studied at Classes préparatoires Stanislas, where he completed a Khâgne B/L in Social Sciences and Humanities from 2012 to 2014. He holds a Master's degree in Econometrics and Quantitative Economics from Université Paris-Saclay, obtained in 2018. He also earned a Master's degree in Artificial Intelligence from PSL Research University in 2022, and a Master's degree in International Political Economy (Research) from The London School of Economics and Political Science in 2016. Additionally, he has a Bachelor's degree in Economics and Sociology from École normale supérieure Paris-Saclay.
Professional Experience
Before joining Inria, Nathan Bigaud accumulated a range of professional experiences. He worked as a Research Analyst at France Stratégie / Services du Premier ministre for two months in 2017. He served as a Consultant at Dalberg from 2018 to 2020 in Paris, and later as a Data Scientist at Dalberg Data Insights in Nairobi from 2020 to 2021. He also held the position of Junior Policy Adviser at the Delegation of the European Union to the United Nations from 2016 to 2017.
Research Focus
At Inria, Nathan Bigaud's research is centered on privacy issues in federated learning systems. His work specifically addresses privacy attacks within cross-silo federated learning environments. This area of research is critical as it seeks to improve the security and confidentiality of data shared across different entities while maintaining the utility of machine learning models.
GitHub Contributions
Nathan Bigaud is active on GitHub under the handle Nathan-bk. His GitHub profile indicates his involvement in coding and software development projects, showcasing his technical skills and contributions to the field of research and technology. This platform allows him to collaborate with others and share his work within the coding community.