Dr. Martin Schüle

Personal profile

Management role

Head of Research/Focus Area, Digital Environment

Position at the ZHAW

Senior Researcher & Lecturer
Head Research Group Digital Environment

www.zhaw.ch/de/lsfm/institute-zentren/ias/

Professional development teaching

• CAS in Digital Life Sciences
• Natural Language Processing Fundamentals

Expertise and research interests

Bio-inspired Computing, Deep Learning, Machine Learning, Modelling of Complex Systems, Cellular Automata Modelling and Theory, Nonlinear Dynamics, Philosophy of Science

Educational background

PhD, ETH Zurich
Physics Diploma, ETH Zurich
CAS Hochschuldidaktik (ZHAW)

Professional milestones

2013-2014 Postdoc, IHPST, Paris, France
2012-2013 Postdoc, Faculty of Informatics, Università della Svizzera italiana

Membership of networks

Deutsche Physikalische Gesellschaft

Projects

• Investor and Stakeholder Tools for Tracking Companies’ Climate Commitments, Greenwashing and ESG Trends / Team member / Project ongoing
• 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

• 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

• 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

• 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.

• 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

• 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

• 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.

• 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

• 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.

• 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

• 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

• 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.

• 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

Publications before appointment at the ZHAW

M. Schüle, Computational Universality and the Edge of Chaos: the Cellular Automata Case, Proceedings of the 7th AISB Symposium on Computing and Philosophy, University of London, England
M. Schüle, Natural Computation, PhD-Thesis 2012, ETH Zurich.
M. Schüle, R. Stoop, A Full Computation-relevant Topological Dynamics Classification of
Elementary Cellular Automata, Chaos, Volume 22(4), 043143, 2012.
M. Schüle, R. Stoop, The Dynamic Behaviour of a Simple Symbolic Dynamics Model of
Locally Coupled Oscillators, Proceedings of NOLTA 2011.
M. Schüle, T. Ott, R. Stoop, Computing with Probabilistic Cellular Automata, Lecture Notes
in Computer Science, Volume 5769/2009, p. 525-533, 2009.
M. Schüle, T. Ott, R. Stoop, Global Dynamics of Finite Cellular Automata, Lecture Notes in Computer Science, Volume 5163, p. 71-78, 2008.
Y. Ortiz, M. Schüle, Limited Rationality and Strategic Interaction: A Probabilistic Multi- Agent Model, working paper at the Swiss National Bank Study Center Gerzensee.
T. Ott, M. Schüle, R. Stoop, Message Passing in Neural Networks, Proceedings of NDES 2007.

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