Dr. Martin Schüle
Dr. Martin Schüle
ZHAW
School of Life Sciences and Facility Management
FG Digital Environment and Sustainability
Schloss
8820 Wädenswil
Work at ZHAW
Position
Head Research AI & Computational Environment
Teaching
- Neural Networks and Deep Learning
- Advanced Deep Learning
Professional development teaching
Projects
- Investor and Stakeholder Tools for Tracking Companies’ Climate Commitments, Greenwashing and ESG Trends / Team member / Project ongoing
- Maximizing the Benefits of Organic Fertilizers: A Data-Driven Approach to Improve Efficiency and Reduce Pollution / Project leader / Project completed
- Employing Natural Language Processing to identify inconsistencies in companies’ non-financial communication / Team member / Project completed
- An integrated modelling and learning framework for real-time online decision assistance in Swiss agriculture / Project leader / Project completed
- Radiosands / Team member / Project completed
- A cloud-based IoT approach for food safety and quality prediction / Team member / Project completed
- Predicting investor behaviour in European bond markets through machine learning / Team member / Project completed
- Dayzzi - Next Generation: Neural Recommendation System / Team member / Project completed
- European government bond dynamics and stability policies: taming contagion risks / Team member / Project completed
- Efficient Urban Pluvial Flood Simulation / Project leader / Project completed
- Monitoring der Lebensmitteltemperatur / Team member / Project completed
- Comprehensive Sales Forecasting for Supply Chain Optimization in Food Industry / Team member / Project completed
- Multi-Asset Investment Process using Bayes Ensembles of Trading Models / Team member / Project completed
Publications
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Schwendner, Peter; Schüle, Martin; Hillebrand, Martin,
2019.
Sentiment analysis of European bonds 2016 - 2018.
Frontiers in Artificial Intelligence.
2(20).
Available from: https://doi.org/10.3389/frai.2019.00020
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Schwendner, Peter; Schüle, Martin; Ott, Thomas; Hillebrand, Martin,
2015.
European government bond dynamics and stability policies : taming contagion risks.
Journal of Network Theory in Finance.
1(4), pp. 1-25.
Available from: https://doi.org/10.21314/JNTF.2015.012
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Uwate, Yoko; Schüle, Martin; Ott, Thomas; Noshio, Yoshifumi,
2020.
Echo state network with chaos noise for time series prediction [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. 274.
-
Schüle, Martin,
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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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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Kaufmann, Moritz; Schüle, Martin; Smits, Theo; Pothier, Joël,
2020.
Typing plasmids with distributed sequence representation [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. 200-210.
Lecture Notes in Computer Science ; 12294.
Available from: https://doi.org/10.1007/978-3-030-58309-5_16
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Ott, Thomas; Schüle, Martin; Fellermann, Harold; Uwate, Yoko,
2018.
Structural evolution in networks of coupled maps with asymmetric influence amplification [paper].
In:
2018 International Symposium on Nonlinear Theory and Its Applications (NOLTA2018), Tarragona, Spain, 2-6 September 2018.
pp. 546-549.
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Schüle, Martin; Ott, Thomas,
2018.
Synchronization in cellular automata : the learning approach [paper].
In:
2018 International Symposium on Nonlinear Theory and Its Applications (NOLTA2018), Tarragona, Spain, 2-6 September 2018.
-
Ott, Thomas; Schüle, Martin; Held, Jenny; Albert, Carlo; Stoop, Ruedi,
2016.
Clustered multidimensional scaling with Rulkov neurons [paper].
In:
2016 International Symposium on Nonlinear Theory and Its Applications.
Nonlinear Theory and Applications 2016 (NOLTA), Yugawara, Japan, 27-30 November 2016.
IEICE.
pp. 389-392.
Available from: https://doi.org/10.21256/zhaw-3532
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Schüle, Martin; Ott, Thomas; Schwendner, Peter,
2016.
Forecasting correlation structures [paper].
In:
Proceedings of the 2016 international symposium on nonlinear theory and its applications.
2016 International Symposium on Nonlinear Theory and Its Applications (NOLTA2016), Yugawara, Japan, 27-30 November 2016.
IEICE.
-
Schüle, Martin,
2018.
Introduction to artificial neural network theory : lecture notes.
-
Schwendner, Peter; Schüle, Martin; Hillebrand, Martin,
2019.
Correlation influence networks for sentiment analysis in European sovereign bonds.
In:
Financial Revolution - Sentiment Analysis, AI and Machine Learning, London, United Kingdom, 25-26 June 2019.
-
Ott, Thomas; Glüge, Stefan; Schüle, Martin; Hill, Christopher,
2018.
A dynamic network approach for the analysis of pathogen transmission chains.
In:
The 26th Nonlinear Dynamics of Electronic Systems Conference, (NDES 2018), Acireale, 11-13 June 2018.
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Schüle, Martin; Ott, Thomas; Schwendner, Peter,
2018.
Influence networks in financial markets : forecast scenarios.
In:
NDES 2018, 26th Nonlinear Dynamics of Electronic Systems Conference, Acireale, Italy, June, 11-13 2018.
-
Schwendner, Peter; Schüle, Martin; Hillebrand, Martin,
2018.
Correlation influence networks for sentiment analysis in European sovereign bonds.
In:
Financial Revolution - Sentiment Analysis, AI and Machine Learning, Zürich, Switzerland, 30 October 2018.
-
Schwendner, Peter; Schüle, Martin; Ott, Thomas; Hillebrand, Martin,
2018.
Sentiment in European sovereign bonds.
In:
3rd European COST Conference on Mathematics for Industry in Switzerland, Winterthur, 6 September 2018.
Available from: https://www.zhaw.ch/storage/engineering/institute-zentren/iamp/sp_acss/Schwendner_20180906.pdf
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Schüle, Martin; Ott, Thomas; Schwendner, Peter,
2017.
Forecasting correlation structures.
In:
NDES 2017, 25th Nonlinear Dynamics of Electronic Systems Conference, Zernez, 5-7 June 2017.
Available from: https://www.ini.uzh.ch/~lorimert/NDES2017/assets/NDES2017_programme_booklet.pdf
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Schwendner, Peter; Schüle, Martin; Hillebrand, Martin,
2017.
Network analytics of sovereign bond dynamics.
In:
Frankfurt Summit on Network Analysis, Frankfurt, Germany, 26 October 2017.
-
Schwendner, Peter; Schüle, Martin; Hillebrand, Martin,
2017.
Sovereign bond network dynamics.
In:
Mathfinance Conference, Frankfurt, Germany, 20-21 April 2017.
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Hillebrand, Martin; Ott, Thomas; Schüle, Martin; Schwendner, Peter,
2016.
European government bond dynamics and stability policies.
In:
ADEMU Workshop on Risk-Sharing Mechanisms for the European Union, Fiesole, Italy, 20-21 May 2016.
-
Schüle, Martin; Schwendner, Peter,
2016.
European government bond dynamics and stability policies : taming contagion risks.
In:
9th Financial Risks International Forum, Paris, France, 21 March 2016.
-
Schwendner, Peter; Schüle, Martin; Hillebrand, Martin,
2015.
European government bond dynamics and stability policies : taming contagion risks.
In:
Financial Risk and Network Theory, Cambridge, United Kingdom, 9 September 2015.
Available from: https://www.jbs.cam.ac.uk/fileadmin/user_upload/research/centres/risk/downloads/150909_slides_schwendner.pdf