I am PhD student at the Max Planck Institute for Intelligent Systems and ETH Zurich as part of the Max Planck ETH Center for Learning Systems program. In particular, I am pursuing my PhD under the supervision of Dr. Andreas Geiger and Prof. Dr. Luc van Gool.
My research interests revolve around Computer Vision and Machine Learning and I am particularly interested in the development of methods capable of describing semantic content.
Doctor of Philosophy (Ph.D.) (April 2017 - now)
Max Planck Institute for Intelligent Systems and ETH Zurich as part of the Max Planck ETH Center for Learning Systems
Diploma in Electrical and Computer Engineering (September 2009 - December 2015)
Department of Electrical and Computer Engineering of Aristotle University of Thessaloniki, in Greece
In Proceedings of the 2016 ACM on Multimedia Conference, pages: 332,336, ACM Multimedia Conference, October 2016 (inproceedings)
This paper introduces fsLDA, a fast variational inference method for supervised LDA, which overcomes the computational limitations of the original supervised LDA and enables its application in large-scale video datasets. In addition to its scalability, our method also overcomes the drawbacks of standard, unsupervised LDA for video, including its focus on dominant but often irrelevant video information (e.g. background, camera motion). As a result, experiments in the UCF11 and UCF101 datasets show that our method consistently outperforms unsupervised LDA in every metric. Furthermore, analysis shows that class-relevant topics of fsLDA lead to sparse video representations and encapsulate high-level information corresponding to parts of video events, which we denote "micro-events".
Our goal is to understand the principles of Perception, Action and Learning in autonomous systems that successfully interact with complex environments and to use this understanding to design future systems