Till Plumbaum studied Computer Science at the Technische Universität Berlin, Germany, obtaining his Masters degree (“Diplom”) in 2006. He obtained his PhD in Computer Science in 2015 at the same university, in the field of adaptive systems. His thesis focuses on combining Semantic Web technologies with User Modeling techniques to improve recommender systems and personalization. The thesis shows that by leveraging information from the Social Web and transferring it into a semantic representation problems like the Cold-Start problem and Grey-Sheep problem can be minimized.
Since 2015, he is Postdoctoral Researcher at the DAI-Labor of the Technische Universität Berlin, leading the research group Information Retrieval and Machine Learning. His research interests include Lifelogging, recommender systems and personalized search.
Till Plumbaum is author of several conference and book publications and frequent reviewer of high ranked conferences including IUI and RecSys. He also organizes workshops covering topics such as Lifelogging and Personalization.