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Prof. Dr. Ioannis Iossifidis

Institut Informatik

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Email:
ioannis.iossifidis@hs-ruhrwest.de

Telephone:
+49 208 88254-806

Office hours:
By appointment
Occupation:
Teaching Area: Theoretical Computer Science and Artificial Intelligence

“Exploring Human Thought”

 

Prof. Dr. Ioannis Iossifidis studied Physics, specialising in Theoretical Particle Physics, at University of Dortmund and received his PhD in 2006 from the Faculty of Physics and Astronomy, Ruhr University Bochum.

At the Institute of Neuroinformatics, Prof. Iossifidis led the Autonomous Robotics research group and, together with his team, successfully participated in numerous AI-related research projects funded by the BMBF and the European Union. Since 1 October 2010, he has been a faculty member at Hochschule Ruhr West (HRW) in the Institute of Computer Science, holding the Chair of Theoretical Computer Science – Artificial Intelligence.

Prof. Iossifidis has been developing biologically inspired, anthropomorphic autonomous robotic systems for over 20 years. These systems are both the subject and the outcome of his research in computational neuroscience. Within this framework, he has developed models of information processing in the human brain and applied them to technical systems.

Key focuses of his recent research include:

  • Modelling human arm movements
  • Designing “Simulated Realities” to simulate and evaluate interactions between humans, machines, and the environment
  • Developing cortical exoprothetic components
  • Developing and applying machine learning algorithms based on deep neural architectures, which serve as a cross-cutting theme in his work

Prof. Iossifidis’ research has been supported by major funding initiatives, including:

  • BMBF projects: NEUROS, MORPHA, LOKI, DESIRE, Bernstein Focus: Neural Foundations of Learning
  • DFG: Motor-parietal cortical neuroprosthesis with somatosensory feedback for restoring hand and arm functions in tetraplegic patients
  • EU projects: Neural Dynamics (EU STREP), EUCogII, EUCogIII

His work has also been recognised as a winner in the Leitmarktwettbewerbe Gesundheit.NRW and IKT.NRW 2019 competitions.

Personal Page: iossifidis.net  

Lab Page: lab.iossifidis.net

Virtual Reality-Based Machine Learning Arm–Hand Function Evaluation and Support (VAFES) – Hochschule Ruhr West

  • Consortium Leader, Principal Investigator (PI)
  • Leitmarkt IKT.NRW (ERDF) – Funding: €2,092,917 / €898,747 (HRW share)

Smart Rehabilitation of the Upper Extremities Using an Intelligent Soft Exoskeleton (REXO)

  • Consortium Leader, Principal Investigator (PI)
  • Leitmarkt Gesundheit.NRW (ERDF) – Funding: €2,084,843 / €998,607

Motor–Parietal Cortical Neuroprosthesis with Somatosensory Feedback for Restoring Hand and Arm Functions in Tetraplegic Patients

  • Principal Investigator (PI)
  • DFG Emmy Noether Programme

Books

  • Iossifidis, Ioannis (2006a). Dynamische Systeme zur Steuerung anthropomorpher Roboter- arme in autonomen Robotersystemen. Logos Verlag Berlin, S. 160.
     
  • Prassler, Erwin, Gisbert Lawitzky, Andreas Stopp, Gerhard Grunwald, Martin Hägele, Rüdiger Dillmann und Ioannis Iossifidis (2004). Advances in Human Robot Interaction. Hrsg. von Erwin Prassler, Gisbert Lawitzky, Andreas Stopp, Gerhard Grunwald, Martin Hägele, Rüdi- ger Dillmann und Ioannis Iossifidis. Bd. 14/2004. Springer Tracts in Advanced Robotics STAR ISBN: 3-540-23211-7. Springer Press, S. 414.

Articles

  • Aline Xavier Fideˆncio, Christian Klaes, and Ioannis Iossifidis (2022). “Error-Related Potentials in Reinforcement Learning-Based Brain-Machine Interfaces”. In: Frontiers in Human Neuroscience 16. ISSN: 1662-5161
     
  • Stephan Johann Lehmler, Muhammad Saif-ur-Rehman, Tobias Glasmachers, and Ioannis Iossifidis (2022). “Deep Transfer Learning Compared to Subject-Specific Models for sEMG Decoders”. In: Journal of Neural Engineering. ISSN: 1741-2552
     
  • Omair Ali, Muhammad Saif-ur-Rehman, Susanne Dyck, Tobias Glasmachers, Ioannis Iossifidis, and Christian Klaes (Mar. 10, 2022). “Enhancing the Decoding Accuracy of EEG Signals by the Introduction of Anchored-STFT and Adversarial Data Augmentation Method”. In: Nature Scientific Reports 12.1 (1), p. 4245. ISSN: 2045-2322
     
  • Marie Dominique Schmidt, Tobias Glasmachers, and Ioannis Iossifidis (2022). “From Motion to Muscle”. arXiv: 2201.11501 [cs.LG]
     
  • Sebastian Doliwa, Andreas Erbeslo ̈h, Karsten Seidl, and Ioannis Iossifidis (2022). “Development of a Scalable Analog Front-End for Brain-Computer Interfaces”. In: 17th International Conference on PhD Research in Microelectronics and Electronics. Sardinia, Italy: IEEE
     
  • MuhammadSaif-ur-Rehman,OmairAli,SusanneDyck,RobinLienka ̈mper,MaritaMetzler,Yaroslav Parpaley, Jo ̈rg Wellmer, Charles Liu, Brian Lee, Spencer Kellis, Richard A Andersen, Ioannis Iossifidis, Tobias Glasmachers, and Christian Klaes (2020). “SpikeDeep-Classifier: A Deep-Learning Based Fully Automatic Offline Spike Sorting Algorithm”. In: Journal of Neural Engineering
     
  • MuhammadSaif-ur-Rehman,RobinLienkämper,YaroslavParpaley,JörgWellmer,CharlesLiu,Brian Lee, Spencer Kellis, Richard Andersen, Ioannis Iossifidis, Tobias Glasmachers, and Christian Klaes (2019). “SpikeDeeptector: A Deep-Learning Based Method for Detection of Neural Spiking Activity". In: Journal of Neural Engineering 16.5, p. 056003
     
  • Muhammad Ayaz Hussain, Muhammad Saif-ur-Rehman, Christian Klaes, and Ioannis Iossifidis (2020). “Comparison of Anomaly Detection between Statistical Method and Undercomplete”. In: IEEE International Congress on Big Data. Los Angeles, USA, pp. 32–38
     
  • Ioannis Iossifidis (2014b). “Simulated Framework for the Development and Evaluation of Redundant Robotic Systems”. In: International Conference on Pervasive and Embedded and Communication Systems, 2014, PECCS2014
     
  • Inaki Rano and Ioannis Iossifidis (2013). “Modeling Human Arm Motion through the Attractor Dynamics Approach”. In: 2013 IEEE International Conference on Robotics and Biomimetics, ROBIO 2013, pp. 2088–2093. ISBN: 978-1-4799-2744-9
     
  • Ioannis Iossifidis (2013). “Motion Constraint Satisfaction by Means of Closed Form Solution for Redundant Robot Arms”. In: Proc. IEEE/RSJ International Conference on Robotics and Biomimetics (RoBio2013), pp. 2106–2111. ISBN: 978-1-4799-2744-9
     
  • M.Tuma,I.Iossifidis,andG.Scho ̈ner(May2009).“TemporalStabilizationofDiscreteMovementin Variable Environments: An Attractor Dynamics Approach”. In: 2009 IEEE International Conference on Robotics and Automation. IEEE, pp. 863–868. ISBN: 978-1-4244-2788-8

  • Computational Neuroscience
  • Brain–Computer Interface: Development of cortical exoprothetic components
  • Theory of Neural Networks
  • Modelling of Human Arm Movements
  • Simulated Reality