Anne-Marie Kermarrec
Nationality: French
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Anne-Marie Kermarrec (CV) is Professor at EPFL
since January 2020. Before that she was the CEO of the Mediego startup that she founded in April 2015. Mediego provides content personalization services for online publishers. She was a Research Director at Inria, France from 2004 to 2015. She got a Ph.D. thesis from University of Rennes (France), and has been with Vrije Universiteit, NL and Microsoft Research Cambridge, UK. Anne-Marie received an ERC grant in 2008 and an ERC Proof of Concept in 2013. She received the Montpetit Award in 2011 and the Innovation Award in 2017 from the French Academy of Science. She has been elected to the European Academy in 2013 and named ACM Fellow in 2016. She was elected at the French Academy of Science in 2024. Her research interests are in large-scale distributed systems,
epidemic algorithms,
peer to peer networks and system support for machine learning.
Google Scholar: https://scholar.google.com/citations?user=aIAy-qcAAAAJ
DBLP: https://dblp.org/pers/k/Kermarrec:Anne=Marie.html
Education
Computer Science
|1993 – 1996 University of Rennes 1, France
Computer Science
| Habilitation à diriger les recherches2002 – 2002 University of Rennes 1, France
Awards
Elected Fellow of Association for Computing Machinery (ACM)
2017
Elected Member of the Academia Europaea
Academia Europaea
2013
Elected ELLIS Fellow
ELLIS Society
2024
Chevalier de la Légion d' Honneur
French Governement
2019
Innovation Award from the French Academy of Science/Dassault Systems/Inria
French Academy of Science
2017
Google Focused Award
2013
Montpetit Award
French Academy of Science Award
2011
ACM EuroSys Lifetime Achievement Award
ACM EuroSys
2025
Elected Member at the French Academy of Science
French Academy of Science
2024
Teaching & PhD
PhD Students
Mathis Benjamin Manuel Randl, Milos Vujasinovic, Diana Andreea Petrescu, Rishi Sharma, Akash Balasaheb Dhasade, Sami Omar Charles Abuzakuk
Past EPFL PhD Students
Courses
Systems for data management and data science
CS-460
This is a course for students who want to understand modern large-scale data analysis systems and database systems. The course covers fundamental principles for understanding and building systems for managing and analyzing large amounts of data. It covers a wide range of topics and technologies.
Topics in Machine Learning Systems
CS-723
This course will cover the latest technologies, platforms and research contributions in the area of machine learning systems. The students will read, review and present papers from recent venues across the systems for ML spectrum.