Technical University of Munich

I am interested in Artificial Intelligence, Machine Learning and Robotics. In particular, I think a lot about

• metric learning - because everything is relative,
• space partitioning - because you have to divide to conquer,
• reinforcement learning - because you have to act if you want to change the future.

For the last part, I consider how agents integrate information over time, reason and make intelligent decisions.

I received my B.Sc. in Computer Science from the Technical Educational Institute of Athens in 2012 and my M.Sc. in Computer Science (Robotics, Cognition, Intelligence) from the Technical University of Munich in 2015. Since October 2015, I am a PhD student in the Computer Vision Research Group, headed by Prof. Dr. Daniel Cremers at TUM.

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Conference and Workshop Papers
2020
[]		Effective Version Space Reduction for Convolutional Neural Networks (Liu, Jiayu, Chiotellis, Ioannis, Triebel, Rudolph and Cremers, Daniel), In European Conference on Machine Learning and Data Mining (ECML-PKDD), 2020. ([arxiv]) [bibtex]
2018
[]		Incremental Semi-Supervised Learning from Streams for Object Classification (I. Chiotellis, F. Zimmermann, D. Cremers and R. Triebel), In International Conference on Intelligent Robots and Systems (IROS), 2018. ([code]) [bibtex] [pdf]
2016
[]		Learning to Drive using Inverse Reinforcement Learning and Deep Q-Networks (S. Sharifzadeh, I. Chiotellis, R. Triebel and D. Cremers), In , NIPS Workshops, 2016. ([arxiv]) [bibtex] [pdf]
[]		Non-Rigid 3D Shape Retrieval via Large Margin Nearest Neighbor Embedding (I. Chiotellis, R. Triebel, T. Windheuser and D. Cremers), In European Conference on Computer Vision (ECCV), 2016. ([code]) [bibtex] [pdf]

Winter 2018 - Lecture (tutorial)
Machine Learning for Robotics and Computer Vision (IN2357) (2h + 2h, 5ECTS)

Summer 2018 - Lecture (tutorial)
Machine Learning for Robotics and Computer Vision (IN2357) (2h + 2h, 5ECTS)

Winter 2017 - Lecture (tutorial)
Machine Learning for Robotics and Computer Vision (IN3200) (2h + 2h, 5ECTS)

Summer 2017 - Lecture (tutorial)
Machine Learning for Robotics and Computer Vision (IN3200) (2h + 1h, 4ECTS)

Winter 2016 - Lecture (tutorial)
Machine Learning for Robotics and Computer Vision (IN3200) (2h + 1h, 4ECTS)

Summer 2016 - Lecture (tutorial)
Machine Learning for Robotics and Computer Vision (IN3200) (2h + 1h, 4ECTS)

Summer 2016 - Practical Course
Machine Learning for Applications in Computer Vision (IN2106) (6h, 10 ECTS)

Winter 2015 - Lecture (tutorial)
Machine Learning for Robotics and Computer Vision (IN3200) (2h + 1h, 4ECTS)