Bio-Inspired Modeling & Learning Systems
Introduction - Research and Teaching
We are concerned with design and development of adaptive systems for industrial and business applications, based on our expertise on machine learning, (recurrent) neural networks and bio-inspired algorithms as well as different simulation methods. A central speciality of our group is the development and research on complex (i.e. multi-methodical) forecasting systems. The polysemy of the term «LEARNING SYSTEMS» is an inherent element of the group’s spirit. Our self-concept as a team is the concept of a learning system. We are keen to learn more about new methods and more about ourselves in research and teaching. We are involved in teaching at Bachelor’s and Master’s level as well as continuing education and we actively work on the development of novel teaching methods to learn for our students and together with our students.
Research Topics & Expertise
"Intelligence is based on learning"
Expertise
- Bio-inspired algorithms and neural networks
- Human in the loop machine learning
- Modeling of complex systems
- Self-learning systems for real world applications
- Forecasting methodologies
Topics
Our Team
Reference projects
Comprehensive Sales Forecasting for Supply Chain Optimization (CTI project)
Germ Tracking - Project Infectiology ++
Fighting bites with bytes: Promoting public health with crowdsourced tick prevention
Some Projects in a Nutshell
Current publications
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2020.
The collaborative learning cellular automata density classification problem [ paper ].
In:
Proceedings of the 2020 International Symposium on Nonlinear Theory and its Applications.
International Symposium on Nonlinear Theory and its Applications (NOLTA), Okinawa, Japan, 16–19 November 2020.
pp. 268.
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Miniussi, Myriam; Ott, Thomas ; Fellermann, Harold,
2020.
Impact of noise and network size in coupled maps with asymmetric influence amplification [ paper ].
In:
Proceedings of the NOLTA 2020 Conference.
2020 International Symposium on Nonlinear Theory and Its Applications (NOLTA2020), Online Conference, 16-19 November 2020.
pp. 282-285.
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Gygax, Gregory ; Füchslin, Rudolf Marcel ; Ott, Thomas ,
2020.
In:
Proceedings of the NOLTA 2020 Conference.
2020 International Symposium on Nonlinear Theory and Its Applications (NOLTA2020), Online Conference, 16-19 November 2020.
pp. 278-281.
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Gygax, Gregory ; Schüle, Martin ,
2020.
A hybrid deep learning approach for forecasting air temperature [ paper ].
In:
Schilling, Frank-Peter; Stadelmann, Thilo, eds. ,
Artificial Neural Networks in Pattern Recognition.
9th IAPR TC 3 Workshop on Artificial Neural Networks for Pattern Recognition (ANNPR'20), Winterthur, Switzerland, 2-4 September 2020.
Cham:
Springer.
pp. 235-246.
Lecture Notes in Computer Science ; 12294.
Available from : https://doi.org/10.1007/978-3-030-58309-5_19
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Wróbel, Anna ; Gygax, Gregory ; Schmid, Andi; Ott, Thomas ,
2020.
In:
Schilling, Frank-Peter; Stadelmann, Thilo, eds. ,
Artificial Neural Networks in Pattern Recognition.
9th IAPR TC 3 Workshop on Artificial Neural Networks for Pattern Recognition (ANNPR'20), Winterthur, Switzerland, 2-4 September 2020.
Cham:
Springer.
pp. 257-265.
Lecture Notes in Computer Science ; 12294.
Available from : https://doi.org/10.1007/978-3-030-58309-5_21
Current projects
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Detection of drone signals
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Prototypes for the Sustainable Digitisation of University Teaching
The COVID-19 Pandemy has forced higher education into fast forwarding their digitisation across the board. This creates valuable and relevant information for the sustainable digitization beyond the crisis mode. The project structures evidence-based digital teaching exsperiences and digital competences at the ...