The Chair of Cyber-Physical-Systems
The Chair of Cyber-Physical-Systems at the Montanuniversität Leoben in Austria is headed by Prof. Elmar Rueckert.
The group’s research topics are autonomous systems, machine and deep learning, embedded smart sensing systems, and computational models.
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AI & Robotics Positions and Topics
The chair is offering a number of open positions and student thesis topics in AI and robotics.
Also check our wiki, which offers numerous public posts on open source code repositories or tutorials.
Latest news
News
April 17, 2019
Gründungssitzung Grundlagen von KI Systemen
Fachausschusses FA1.60 zu Grundlagen lernender intelligenter Systeme, Gründungsmitglieder: Barbara Hammer (Universität Bielefeld), Elmar Rückert (gewählter Vorsitzender), Georg Schildbach (Universität zu Lübeck), Gerhard Neumann (Universität Tübingen), Heinz Koeppl (Technische Universität Darmstadt),..Read MoreJanuary 5, 2019
Best Paper Award
for the paper: Learning to Categorize Bug Reports with LSTM Networks, by Gondaliya, Kaushikkumar D; Peters, Jan; Rueckert, Elmar. In Proceedings of the International Conference on Advances in System Testing and Validation Lifecycle (VALID)., pp…Read MoreDecember 21, 2018
Conference paper accepted at BIOSIGNALS 2019
Rottmann, N; Bruder, R; Schweikard, A; Rueckert, E. (2019). Cataglyphis ant navigation strategies solve the global localization problem in robots with binary sensors, Proceedings of the International Conference on Bio-inspired Systems and..Read MoreOctober 9, 2018
Journal Paper Accepted at Neural Networks
Daniel Tanneberg, Jan Peters, Elmar Rueckert Intrinsic Motivation and Mental Replay enable Efficient Online Adaptation in Stochastic Recurrent Networks accepted (Oct, 9th 2018) at Neural Networks – Elsevier with an Impact Factor..Read MoreJuly 31, 2018
Conference paper accepted at VAILD 2018
Gondaliya, D. Kaushikkumar; Peters, J.; Rueckert, E. (2018). Learning to categorize bug reports with LSTM networks: An empirical study on thousands of real bug reports from a world leading software..Read MoreJuly 18, 2018
Journal Paper Accepted at JMLR – Journal of Machine Learning Research.
Adrian Šošić, Elmar Rueckert, Jan Peters, Abdelhak M. Zoubir, Heinz Koeppl Inverse Reinforcement Learning via Nonparametric Spatio-Temporal Subgoal Modeling accepted (Oct, 8th 2018) at Journal of Machine Learning Research (JMLR).February 1, 2018
1st day as Assistant Professor
September 18, 2017
Invited Talk at the ICDL Conference, Lisbon, Portugal
Home – Background Slideshow Title: Experience Replay and Intrinsic Motivation in Neural Motor Skill Learning ModelsSeptember 18, 2017
3 HUMANOIDS Papers Accepted
Rueckert, E.; Nakatenus, M.; Tosatto, S.; Peters, J. (2017). Learning Inverse Dynamics Models in O(n) time with LSTM networks. Tanneberg, D.; Peters, J.; Rueckert, E. (2017). Efficient Online Adaptation with..Read MoreSeptember 1, 2017
CoRL Paper accepted
Tanneberg, D.; Peters, J.; Rueckert, E. (2017). Online Learning with Stochastic Recurrent Neural Networks using Intrinsic Motivation Signals, Proceedings of the Conference on Robot Learning (CoRL).August 4, 2017
W1 Juniorprofessorship with tenure track at University Lübeck
With February 1st, 2018 I will work as professor for robotics at the university Lübeck.February 28, 2017
Invited Talk at University Lübeck
Title: Neural models for robot motor skill learning. Abstract: The challenges in understanding human motor control, in brain-machine interfaces and anthropomorphic robotics are currently converging. Modern anthropomorphic robots with their compliant..Read MoreJanuary 31, 2017
Invited Talk at the Frankfurt Institute for Advanced Studies (FIAS), Germany
Learning to Plan through Reinforcement Learning in Spiking Neural Networks Abstract: Movement planing is a fundamental skill that is involved in many human motor control tasks. While the hippocampus plays a..Read MoreNovember 18, 2016
Invited Talk at the Institute of Neuroinformatics (INI), Zurich, Switzerland
Probabilistic computational models of human motor control for robot learning.November 14, 2016
Invited Talk at the Albert-Ludwigs-Universität Freiburg, Germany
Neural models for brain-machine interfaces and anthropomorphic roboticsMore news on Professor Rueckert’s page.