Prof. Dr. Stefan Wermter

• Neural Networks, Artificial Intelligence, Hybrid Knowledge Processing, Neurocognitive Robotics, Multimodal Integration, Data Mining, Machine Learning.

• My objective is to research into neural knowledge technology for intelligent systems. Our approaches are often motivated by nature, e.g. from biology, cognition and neuroscience. We want to study and understand nature-inspired, in particular hybrid neural and symbolic representations, in order to build next-generation systems, for instance adaptive interactive knowledge discovery systems, continually learning multimodal neural agents, and neuroscience-inspired robots.

• Diplom, Department of Computer Science, University of Dortmund, Germany (1987)
• Award Fellowship of the German Academic Exchange Service, Department of Computer Science, University of Massachusetts at Amherst, USA (1987-1988)
• Research Assistant, Department of Computer Science, University of Massachusetts, USA (1988-1989)
• Master of Science, Department of Computer Science, University of Massachusetts, USA (1989)
• Research Associate and Lecturer, Department of Computer Science, University of Dortmund, Germany (1990-1991)
• PhD, Department of Computer Science, University of Hamburg, Germany (1993)
• Research Scientist, Department of Computer Science, University of Hamburg, Germany; leading working group on hybrid neural processing (1991-1997)
• Visiting Research Scientist, International Computer Science Institute, Berkeley, California, USA (1997)
• Higher Doctorate (Habilitation), Department of Computer Science, University of Hamburg, Germany. Learning of robust language processing in hybrid neural architectures (1998)
• Professor of Computer Science, Chair for Intelligent Systems, School of Computing and Technology, University of Sunderland, England (1998-2010)
• Professor of Computer Science, Chair for Knowledge Technology,  Department of Computer Science, University of Hamburg, Germany (2010-)

I have coordinated and participated in a number of projects, including:

• SOcial Cognitive Robotic Agents in The European Society (SOCRATES)
• Transregio-Sonderforschungsbereich TRR 169 Cross-Modal Learning (CML)
• European Training Network: Safety Enables Cooperation in Uncertain Robotic Environments (SECURE)
• Learning Conversational Action Repair for Intelligent Robots (LeCAREbot)
• LingoRob - Learning Language in Developmental Robots
• Ideomotor Transfer for Active Self-emergence (IDEAS)
• KI-SIGS: AI Space for Intelligent Health Systems - AP390.1: Detection of Whole-body Posture and Movement
• The Neural Microcircuits of Problem-solving and Goal-directed Behavior
• Topological Deep Multiple Timescale Recurrent Neural Network for Cognitive Learning and Memory Modelling towards Human-level Synthetic Intelligence (NeuroSynthelligence)
• Neural Network-based Robotic Grasping via Curiosity-driven Reinforcement Learning (NeuralGrasp)
• Bio-inspired Indoor Robot Navigation (BIONAV)
• Neural-Network-based Action-Object Semantics for Assistive Robotics
• Echo State Networks for Developing Language Robots (EchoRob)
• Cooperating Robots (CoRob)
• Gestures and Reference Instructions for Deep robot learning (GRID)
• Teaching With Interactive Reinforcement Learning (TWIRL)
• Cognitive Assistive Systems (CASY)
• Cross-modal Interaction in Natural and Artificial Cognitive Systems (CINACS)
• Robotics for the Development of Cognition (RobotDoc)
• Knowledgeable SErvice Robots for Aging (KSERA)
• What it means to communicate (NESTCOM)
• Midbrain Computational and Robotic Auditory Model for focused Hearing (MiCRAM)
• Biomimetic Multimodal Learning in a Mirror Neuron-based Robot (MirrorBot)
• Emerging computational neural architectures based on neuroscience (EmerNet)
• Experimental and Neurocomputational Investigations of Cognitive Systems (ENICS)
• Towards helpdesk automation using scanning language understanding and hybrid neural language techniques (HelpNet)
• Localising and Tracking Sound in a neurally inspired robot (TRACKBOT)
• European Network Robotics Network of Excellence (Partner member in EURON2)
• Hybrid neural intelligent agents (HyNeT)
• Hybrid systems and hybrid Methodology (HyM)
• Hybrid neural spoken language systems (SCREEN)
• Hybrid neural, rule-based and case-based eValuation (HyValue)
• Formal unification for language processing (Vesuv)

A list of current and recent project can be found at the Project page of the Knowledge Technology research group.

• Associate Editor for 8th Joint IEEE International Conference on Development and Learning and on Epigenetic Robotics (ICDL-EPIROB 2018), Tokyo.
• Associate Editor of Transaction on Neural Networks and Learning Systems
• Associate Editor of Hybrid Intelligent Systems
• Associate Editor of Connection Science
• Associate Editor of Knowledge and Information Systems
• Editorial Board and Action Editor of Neural Networks until 2014
• Editorial Board of Cognitive Systems Research
• Editorial Board of International Journal of Computational Intelligence and Applications
• Editorial Board of Neural Computing Surveys
• Editorial Board of Neural Information Processing - Letters and Reviews
• Editorial Board of International Journal of Computational Intelligence
• Editorial Board of Cognitive Computation
• Board of European Neural Network Society (elected for 2007-2016 period)
• Member of IEEE Autonomous Mental Development Technical Committee (AMDTC)
• Member of the EPSRC College Prioritization Panel of Engineering and Physical Sciences Research Council 2006-2010
• Award Chair for the World Conference on Computational Intelligence (WCCI 2022)
• Recent Programme Committees

If you are looking for an interesting Postdoc or PhD research project, e.g. PhD around the following research topics, you could email(%20wermter"AT"informatik.uni-hamburg.de). Sometimes there are a restricted number of PhD studentships available on related and other topics. Furthermore, research / training opportunities exist from the EU for European researchers as Marie Curie Fellowships at different levels: predoc, postdoc, or advanced senior researcher. We are interested to host researchers who would like to strengthen the research in our team.

I have taught mainly in the areas of:

• Neural Networks
• Bioinspired Artificial Intelligence
• Knowledge Processing
• Machine Learning
• Knowledge-based Systems
• Information Systems
• Intelligent Systems
• Hybrid Neural Symbolic Systems
• Natural Language Processing
• Automatic Knowledge Acquisition
• Cognitive Robotics

• 2019 Workshop on Personal Robotics and Secure Human-Robot Collaboration (at ICDL-EPIROB 2019), organized by Angelo Cangelosi, Stefan Wermter, Alban Lafraquiere, Sven Magg; Oslo, Norway.
• 2018 Workshop on Intelligent Assistive Computing (at IEEE WCCI 2018), organised by Pablo Barros, Francisco Cruz, German I. Parisi, Bruno Fernandes; Rio de Janeiro, Brazil.
• 2018 One-Minute Gradual-Emotion Behavior Challenge (OMG-Emotion), organised by Pablo Barros, Egor Lakomkin, Henrique Siqueira, Alexander Sutherland, Stefan Wermter
• 2018 Workshop on Personal Robots for Exercising (at HRI Conference 2018), organised by Sascha Griffiths, Stefan Wermter, Sebastian Schneider, Britta Wrede, Carlos A. Cifuentes G.; Chicago, IL, USA.
• 2017 Workshop on Computational Models for Crossmodal Learning (at IEEE ICDL-EPIROB 2017), organised by Pablo Barros, German I. Parisi, Doreen Jirak and Bruno Fernandes; Lisbon, Portugal.
• 2017 Workshop towards Intelligent Social Robots: Social Cognitive Systems in Smart Environments (at RO-MAN 2017), organised by Amir Aly, Sascha Griffiths, Verena Nitsch, Tadahiro Taniguchi, Stefan Wermter, Adriana Tapus; Lisbon, Portugal.
• 2016 Workshop on Bio-inspired Social Robot Learning in Home Scenarios (on IROS 2016), organised by Francisco Cruz, Jimmy Baraglia, Stefan Wermter, Yukie Nagai, Daejeon, KR
• 2014 International Conference on Artificial Neural Networks, organised by General Chair Stefan Wermter, the Program Co-Chairs and Local Organising Committee, Hamburg, DE
• 2012 Postgraduate Conference on Robotics and Development of Cognition (RobotDoC-PhD), organised by Angelo Cangelosi, Francesca Stramandinoli, Stefan Wermter, Lausanne, CH
• 2009 Meeting of Natural Computing Application Forum: Intelligent Robotics, organised by Stefan Wermter, Michael Knowles, Martin Page, Sunderland, UK
• 2008 International Workshop on Minds, brains, networks, communication and robots, organised by Stefan Wermter, Vittorio Gallese, Friedemann Pulvermueller, Edinburgh, Scotland
• 2007 International Workshop on what it means to communicate based on neural, cognitive and computational evidence, organised by Stefan Wermter, Vittorio Gallese, Friedemann Pulvermueller, Porto, Portugal
• 2005 International AI Workshop on Neurobotics, Ulm, Germany organised by Guenther Palm, Stefan Wermter, Mark Elshaw, Ulm, Germany
• 2000 International Workshop on Current Computational Architectures Integrating Neural Networks and Neuroscience, organized by Stefan Wermter, David Willshaw, Durham, UK
• 1999 EmerNet International Workshop on Emergent Neural Computational Architectures based on Neuroscience organized by Stefan Wermter, Jim Austin, David Willshaw, Edinburgh, Scotland
• 1999 AAAI Conference workshop on Neuroscience and Neural Computation organized by Jim Austin, Stefan Wermter, and Vasant Honavar, Orlando, USA
• 1998 Interdisciplinary conference, Hybrid Neural and Symbolic Language Processing, Invited Lecture Session, Stefan Wermter
• 1998 NIPS Conference Workshop on Neural Symbolic Integration, organised by Stefan Wermter, Ron Sun, Colorado, USA
• 1997 Workshop on Connectionist, Statistical and Symbolic Representations and Natural Language Processing, organized by Stephan Busemann, Karin Harbusch, Stefan Wermter
• 1995 International Workshop on New Approaches to Learning for Natural Language Processing, organised by Stefan Wermter, Gabriele Scheler, Ellen Riloff, Montreal, Canada

Farkaš, I., Masulli, P., Otte, S., Wermter, S. (Eds.) Artificial Neural Networks and Machine Learning Part I – ICANN 2021, 30th International Conference on Artificial Neural Networks, Springer Nature, 2021.

Farkaš, I., Masulli, P., Otte, S., Wermter, S. (Eds.) Artificial Neural Networks and Machine Learning Part II – ICANN 2021, 30th International Conference on Artificial Neural Networks, Springer Nature, 2021.

Farkaš, I., Masulli, P., Otte, S., Wermter, S. (Eds.) Artificial Neural Networks and Machine Learning Part III – ICANN 2021, 30th International Conference on Artificial Neural Networks, Springer Nature, 2021.

Farkaš, I., Masulli, P., Otte, S., Wermter, S. (Eds.) Artificial Neural Networks and Machine Learning Part IV – ICANN 2021, 30th International Conference on Artificial Neural Networks, Springer Nature, 2021.

Farkaš, I., Masulli, P., Otte, S., Wermter, S. (Eds.) Artificial Neural Networks and Machine Learning Part V – ICANN 2021, 30th International Conference on Artificial Neural Networks, Springer Nature, 2021.

Farkaš, I., Masulli, P., Wermter, S. (Eds.) Artificial Neural Networks and Machine Learning Part I – ICANN 2020, 29th International Conference on Artificial Neural Networks, Springer Nature, 2020.

Farkaš, I., Masulli, P., Wermter, S. (Eds.) Artificial Neural Networks and Machine Learning Part II – ICANN 2020, 29th International Conference on Artificial Neural Networks, Springer Nature, 2020.

Wermter, S., Weber, C., Duch, W., Honkela, T., Koprinkova-Hristova, P., Magg, S., Palm, G., Villa, A.E.P. (Eds.) Artificial Neural Networks and Machine Learning -- ICANN 2014, 24th International Conference on Artificial Neural Networks, Springer Heidelberg, 2014.

S. Wermter, M. Page, M. Knowles, V. Gallese, F. Pulvermuller and J. Taylor. Neural Network: Special Issue on What it Means to Communicate. Volume 22, Number 2, March, 2009.

Wermter S., Palm G., Elshaw M. (Eds.) Biomimetic Neural Learning for Intelligent Robots. Springer, Heidelberg, Germany. 2005.

S. Wermter S., Austin J., Willshaw D. (Eds.) Emergent Neural Computational Architectures based on Neuroscience. Springer, Heidelberg, Germany, 2001.

S. Wermter, R. Sun (Eds.) Hybrid Neural Systems. Springer Verlag, Heidelberg, 2000.

S. Wermter, E. Riloff, G. Scheler (Ed). Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing Springer Verlag, Berlin, 1996.

Wermter S. 1995. Hybrid Connectionist Natural Language Processing. Chapman and Hall, International Thomson Computer Press, London, UK, 1995.

Wermter S. Learning of Robust Language Processing in Hybrid Connectionist Architectures. Higher Doctorate (Habilitation) thesis. Department of Computer Science, University of Hamburg, Hamburg, Germany. 1998. (in German) 302pp.

Wermter S. A Hybrid Connectionist Approach for a Scanning Understanding of Natural Language Phrases. Doctoral thesis, Department of Computer Science, University of Hamburg, Hamburg, Germany. 1993.

• I served as the editor for book review articles until 2015 for the journal of Cognitive Systems Research. Further information on previous book review articles and a list of books can be found here.