Mathias Humbert

Mathias Humbert is an Associate Professor at the University of Lausanne, with affiliations at the Department of Information Systems in the Faculty of Business and Economics. Previously, he held roles as a Scientific Project Manager at the Cyber-Defence Campus, Senior Data Scientist at the Swiss Data Science Center (SDSC) at ETHZ and EPFL, and Postdoctoral Researcher at CISPA in Saarbrücken.

He earned his Ph.D. in 2015 from EPFL (Switzerland) after completing B.Sc./M.Sc. studies at EPFL and UC Berkeley. His research focuses on privacy, cybersecurity, and machine learning, particularly examining privacy risks in MLaaS, online social networks, wearable devices, and spectrum monitoring, while developing novel privacy-preserving frameworks for biomedical data and social graphs.

• Key research areas: Privacy in data sharing, interdependent privacy, genomic privacy, location privacy, and graph-based machine learning
• Notable contributions: GraphEraser for graph unlearning, KGP Meter for genomic privacy awareness, and SVT² for differential privacy in methylation data

His recent publications explore machine unlearning vulnerabilities, privacy risks in DNA methylation data, and usability challenges in web security mechanisms, with a focus on empirical studies and cryptographic solutions. He received a Distinguished Paper Award at NDSS 2019 for his work on MBeacon and has contributed extensively to privacy research across ACM CCS, IEEE EuroS&P, and USENIX Security venues.