
John Chiotellis
PhD StudentTechnische Universität MünchenDepartment of Computer Science
Informatik 9
Boltzmannstrasse 3
85748 Garching
Germany
Tel: +49-89-289-17752
Fax: +49-89-289-17757
Office: 02.09.058
Mail: ioannis.chiotellis@in.tum.de
Find me on github.
Research Interests
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.
Brief Bio
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.
Publications
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Conference and Workshop Papers
2018
[] Incremental Semi-Supervised Learning from Streams for Object Classification , In International Conference on Intelligent Robots and Systems (IROS), 2018. ([code])
2016
[] Learning to Drive using Inverse Reinforcement Learning and Deep Q-Networks , In , NIPS Workshops, 2016. ([arxiv])
[] Non-Rigid 3D Shape Retrieval via Large Margin Nearest Neighbor Embedding , In European Conference on Computer Vision (ECCV), 2016. ([code])
Teaching
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)