The Middleware 2018 will feature two outstanding keynotes.

Anne-Marie Kermarrec — Recommenders in practice: Debunking some myths

Abstract: Recommenders are the most prominent way to provide personalization in most applications. Highly popularized by Amazon and Netflix, they are now pivotal in almost all applications out there. While most research on recommenders have focused on improving the quality of the results (aka precision) so far, building an operational end efficient recommender goes far beyond. Recommenders come with many challenges beyond quality. One of the most crucial is their ability to scale to a large number of users and a growing volume of dynamic data to provide real-time recommendations, thus introducing many system challenges. Another challenge is related to privacy awareness: while recommenders rely on the very fact that users give away information about themselves, this potentially raises some privacy concerns. In this talk, I will focus on the challenges associated to building efficient, scalable and privacy-aware recommenders.

Bio: Anne-Marie Kermarrec is a senior researcher at Inria, France where she led a research group on large-scale distributed systems from 2006 to 2015. She is currently the CEO of the Mediego startup that she founded in April 2015. Mediego provides online predictive marketing services that directly leverage her recent research. She is also affiliated with EPFL, Switzerland. Before that, after her PhD thesis at University of Rennes in 1996, she 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 from the French Academy of Science in 2011 and the Innovation price in 2017. She is a member of the European Academy since 2013. She was named a 2016 ACM Fellow for contributions to large-scale distributed computing. Her research interests are in large-scale distributed systems and recommenders. She published more than 200 academic papers and received several best papers awards including the Test of time award at ACM/IEEE/ICIP Middleware conference in 2014 for her work on gossip-based peer sampling.