Hey there, I’m Theodoros (Theodore) Vasiloudis and I’m a Machine Learning researcher at the Swedish Institute for Computer Science in Stockholm. My main research interests include large-scale machine learning, graph processing, and natural language processing. I also contribute to the Apache Flink distributed processing engine, and am one of the core developers of its Machine Learning library, FlinkML.

I completed my Master’s Degree in Machine Learning at the Royal Institute of Technology, KTH. My thesis work was performed at Spotify AB, under the supervision of Hedvig Kjellström, KTH and Boxun Zhang, Spotify. My work centered on context-aware recommendation systems, and investigating how do contextual variables such as time affect user choice. You can read my thesis here.

I am a graduate of Aristotle University of Thessaloniki, school of Computer Science. During my studies I followed the Software Engineering track and focused on Machine Learning and Data Science courses which lead to a thesis on the subject of multi-label classification using Bayes networks, working with the Machine Learning and Knowledge Discovery group of the school, under the supervision of Dr. Grigorios Tsoumakas.

In addition to my studies I was an active member of the student organisation Board of European Students of Technology (BEST) which has helped me gain experience in working in a multicultural environment, being in contact with company and state representatives, and managing a team of people from diverse backgrounds and organising local and international events.