Machine learning touches every aspect of Spotify’s business. It is used to help listeners discover content via recommendations and search, generate playlists, extract audio content-rich signals for cataloging and other content-based applications, understanding voice commands, serve ads, develop business metrics and optimization algorithms, create music with AI-assisted tools, and more. Central to these endeavors is a commitment to cultivate expertise in the latest approaches as we advance the state of the art in machine learning methodology and applications. Of particular interest are approaches in reinforcement learning, approximate inference, graphical models, causal inference, deep learning, time series modeling, and meta-model learning.
Marco De Nadai, Francesco Fabbri, Paul Gigioli, Alice Wang, Ang Li, Fabrizio Silvestri, Laura Kim, Shawn Lin, Vladan Radosavljevic, Sandeep Ghael, David Nyhan, Hugues Bouchard, Mounia Lalmas-Roelleke, Andreas Damianou
Andreas Damianou, Francesco Fabbri, Paul Gigioli, Marco De Nadai, Alice Wang, Enrico Palumbo, Mounia Lalmas
Zhenwen Dai, Federico Tomasi, Sina Ghiassian
