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Prof. Dr. Thomas Ott

Prof. Dr. Thomas Ott

Prof. Dr. Thomas Ott
ZHAW Life Sciences und Facility Management
Fachstelle Bio-Inspired Modeling & Learning Systems
Einsiedlerstrasse 31a
8820 Wädenswil

+41 (0) 58 934 56 84
thomas.ott@zhaw.ch

Persönliches Profil

Leitungsfunktion

  • Stv. Institutsleitung Institut für Angewandte Simulation
  • Leitung Bio-Inspired Modeling & Learning Systems

Tätigkeit an der ZHAW als

Dozent (Institut für Angewandte Simulation)


Lectures:

Physik für Umweltingenieure II (BSc UI)
D3: Modelling and Exploration of Multivariate Data (Module Coordinator, MSc Life Sciences)
Neural Networks and Deep Learning (Module Coordinator, MSc Applied Computational Life Sciences)




http://www.zhaw.ch/ias

Arbeits- und Forschungsschwerpunkte, Spezialkenntnisse

Bio-inspired Computing, Applied Neuroinformatics (Pattern Recognition, Machine Learning), Modelling of Complex Systems
Forecast methodologies for traffic and logistics

Aus- und Fortbildung

Kantonsschule Schaffhausen
Dipl.phys. ETH
Dr.sc. ETH
Certificate: International PhD program in neuroscience
CAS Hochschuldidaktik und weitere Didaktikfortbildungen
CAS Management & Leadership

Mitglied in Netzwerken

Projekte

Publikationen

Beiträge in wissenschaftlicher Zeitschrift, peer-reviewed Buchbeiträge, peer-reviewed Konferenzbeiträge, peer-reviewed Weitere Publikationen Mündliche Konferenzbeiträge und Abstracts Publikationen vor Tätigkeit an der ZHAW

Publication List (Thomas Ott)


2016:
Peer-reviewed Journals:

Ott, Thomas; Schüle, Martin; Held, Jenny; Albert, Carlo; Stoop, Ruedi (2016).
Clustered Multidimensional Scaling with Rulkov Neurons.
Proceedings of NOLTA (International Symposium of Nonlinear Theory and Its Applications) 389-392


Christen M, Narvaez D, Tanner C, Ott T: Mapping Values: Using Thesauruses to Reveal Semantic Structures of Cultural Moral Differences. Cognitive Systems Research, 40 59-74 (2016).



2015:

Peer-reviewed Journals:

Christen, Markus; Niederberger, Thomas; Ott, Thomas; Aryobsei, Suleiman; Hofstetter, Reto (2015). Micro-text Classification between Small and Big Data.Nonlinear Theory and Its Applications, IEICE, Vol.E6-N, 4.

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


Miscellaneous:

Kauf, Peter; Ott, Thomas; Dorndorf, Ulrich (2015). Bessere Absatzprognosen: Eine Frage der Faktoren. Logistics Innovation





2014:

Peer-reviewed Conference Proceedings:

Ott, Thomas; Eggel, Thomas; Christen, Markus (2014). Generating Low-Dimensional Denoised Representations of Nonlinear Data with Superparamagnetic Agents. Proceedings of NOLTA 2014, pp. 180-183.

Nef, Annina; Glüge Stefan; Ott, Thomas; Kauf, Peter (2014). Causality Detection in Complex Time Dependent Systems Examplified in Financial Time Series. Proceedings of NOLTA 2014, pp. 176-179.


Glüge, Stefan; Pomati, Francesco; Albert, Carlo; Kauf, Peter; Ott, Thomas (2014). The Challenge of Clustering Flow Cytometry Data from Phytoplankton in Lakes. In: Mladenov, V. M.; Ivanov, P. C. (Hg.). CCIS 438. NDES 2014. (379 - 386). Cham: Springer International Publishing Switzerland .

Jackson , Clare; Bruckmann, Dirk; Ott, Thomas; Weidmann, Ulrich (2014). Improving the Forecast of Freight Transport Demand Using Machine Learning and Time Series Analysis. Conference Paper, 14th Swiss Transport Research Conference

Book:

Burkhard, Marcel; Ott, Thomas; Stoop, Norbert; Kauf, Peter; Jackson, Clare Estelle; Frei, Simone; Ruesch, Martin; Hegi, Philipp; Moreni, Gianni; Koy, Thorsten (2014). Stauprognoseverfahren und -systeme: Forschungsprojekt ASTRA 2011/010. Bezug: VSS .


2013:
Peer-reviewed Journals:

Savi, Daniel; Kasser, Ueli; Ott, Thomas (2013). Depollution benchmarks for capacitors, batteries and printed wiring boards from waste electrical and electronic equipment (WEEE). Waste Management, 33 2737-2743.

Christen M, Ott T, Schwarz D: A new measure for party coherence: applying a physics-based concept to the swiss party system, 2003-2008. Advances in Complex Systems (in press).

Christen M, Ott T: Quantified coherence of moral beliefs as a predictive factor for moral agency. In: Musschenga B et al.: What makes us moral?. Library of Ethics and Applied Philosophy, Springer (in press).

Takamaru, Yuji; Uwate, Yoko; Ott, Thomas; Nishio, Yoshifumi (2013). Dependence of Clustering Patterns on Density of Chaotic Circuits in Networks. Journal of Signal Processing, 17, 4. 103-106.

Peer-reviewed Conference Proceedings:

Uwate, Yoko; Ott, Thomas; Nishio, Yoshifumi (2013). Clustering phenomena in coupled chaotic circuits with different coupling strength. Circuit Theory and Design (ECCTD), 2013

Niederberger, Thomas; Ott, Thomas; Albert, Carlo; Pomati, Francesco (2013). A Sequential Classification Concept using Flawed Training Data - An Application to Flow Cytometry. NDES 2013 (Extended Abstract & Talk)

Ott, Thomas; Christen , Markus; Niederberger, Thomas; Aebersold, Reto; Suleiman, Aryobsei; Hofstetter, Reto (2013). A Semi-Supervised Learning System for Micro-Text Classification. NDES 13 (extended abstract & talk)


Miscellaneous:
S. Köhler, T. Ott: Einflussfaktoren auf das Patientenaufkommen in Notfallstationen.Transfer 1 (2013)

Koller, Christoph; Ott, Thomas; Kellenberger, Remo; Meyer, Thalia (2013). PV-Tracking-System auf dem Skilift in Tenna: Eine erste Auswertung. In: Programm Photovoltaik Ausgabe 2013. Ueberblicksbericht, Liste der Projekte, Jahresberichte der Beauftragten 2012 (251-256). Programm Photovoltaik, Ausgabe 2013. Bern: BFE.



2012:

Peer-reviewed Conference Proceedings:
T. Niederberger, N. Stoop, M. Christen, T. Ott; Hebbian Principal Component Clustering for Information Retrieval on a Crowdsourcing Platform. Proceedings of NDES2012.

Y. Takamaru, Y. Uwate, T. Ott, Y. Nishio; Clustering Phenomena of Coupled Chaotic Circuits for Large Scale Networks. Proceedings of NDES2012.

Y. Takamaru, Y. Uwate, T. Ott, Y. Nishio; Clustering phenomena considering the density of coupled chaotic circuits networks. APCCAS 2012: 647-650

T. Shima, Y. Uwate, T. Ott, Y. Nishio; Investigation of synchronization for social network with local bridge via coupled Rulkov maps. APCCAS 2012: 499-502

Miscellaneous:

Krüsi, B.O.; Lustenberger, P.I.; Hepenstrick, D.; Ott, T. (2012). iGräser - das innovative und benutzerfreundliche mobile Gräserbestimmungs-Tool fürs iPhone. Ingenieurbiologie, 2012, 3. 61-71.


U. Mürset, T. Ott, C. Wäfler; Objektive Beurteilung von Wein mit NIR-Spektroskopie. Newsletter Transfer 1, 2012

T. Ott, B.O. Krüsi; Zukünftige Bestimmungsschlüssel denken mit. TRANSFER, 2012, 3. 6


2011:
Miscellaneous:
M. Christen, T. Ott, D. Schwarz; Spaltpilz in den Parteien.
NZZ-Beitrag zu Parteienanalyse mittels natur-inspirierter Methoden,
NZZ am Sonntag, 5.6. 2011
www.cogitofoundation.ch/pdf/2010/NZZaS_2011-06-05.pdf


Peer-reviewed Conference Proceedings:

T.Ott, T. Niederberger, O. Merlo; Predator-Prey Dynamics in Hopfield-type Networks.
Proceedings of NOLTA (Nonlinear Theory and Applications) 2011

R.L. Stoop, T. Ott, F. Gomez, R. Stoop; Biased Clustering Due to Intrinsic Nonlinear Dynamics Structures. Proceedings of NOLTA (Nonlinear Theory and Applications) 2011

2010:
Peer-reviewed Conference Proceedings:

T. Ott and M. Mürset; Data Clustering based on Hebbian Learning in Inhomogeneous Coupled Map Lattices.
Proceedings of NDES Dresden, 2010.

Miscellaneous:
T. Ott; Clusteranalysen - vielseitig und interdisziplinär. In
Transfer 2, 2010.


2009:
Peer-reviewed Journals:
F. Landis, T.Ott and R.Stoop; Self-organizing Integrate-and-Fire Networks for Data Clustering and Image Segmentation.
Journal of Neural Computation 2009.


Peer-reviewed Conference Proceedings:

T. Ott and M. Mürset; Semi-Supervised Classifiaction with Single-Layer Isingtrons.
Proceedings of NDES 2009.

M.Schüle, T.Ott and R.Stoop; Computing with Probabilistic Cellular Automata.
Proceedings of the 19th International Conference on Artificial Neural Networks (ICANN 2009).

M. Christen, T. Starostina, D. Schwarz and T. Ott; A spin-based measure of the coherence of belief-systems - Theory and Application.
Proceedings of NDES 2009.

Miscellaneous:
T. Ott; Simulation: Ein vielseitiges Werkzeug. In
Technische Rundschau online, 2009.

T. Ott and M. Mürset; Das Isingtron: Ein neuartiges Klassifikationswerkzeug. In
Transfer 2, 2009.

2008:
Peer-reviewed Conference Proceedings:

M. Schuele, T. Ott and R. Stoop; Global Dynamics of Finite Cellular Automata.
Springer LNCS proceedings of ICANN, 2008.

T. Jasa, T. Lanz, T. Ott and R. Stoop; Sequential Superparamagnetic Clustering
as a Predictor of Visual Fixations. Proc. of NOLTA ’08 Budapest, 2008.

Miscellaneous:
T. Ott; Statistische Studie zum Elektroschrott-Recycling in der Schweiz. In
Transfer 2, 2008.


2007:

Peer-reviewed Conference Proceedings:

T. Ott, M. Schuele and R. Stoop; Message Passing in Neural Networks. Proc.
of NDES’07, 2007.

Dissertation:
T. Ott; Self-organised Clustering as a Basis for Cognition and Machine Intelligence. Dissertation ETH , 2007 .


2006:

Peer-reviewed Journals:

T. Ott and R. Stoop; Benefits and Pitfalls of Belief Propagation-mediated Superparamagnetic Clustering. Physical Review E 74 (4): 042103, 2006.

M. Christen, A. Nicol, K. Kendrick, T. Ott and R. Stoop; Odour Encoding
in Olfactory Neuronal Networks Beyond Synchronisation. Neuroreport, 17 (14):
1499-1503, 2006.

M. Christen, A. Kohn, T. Ott and R. Stoop; Measuring Spike Pattern Reliability
with the Lempel-Ziv Distance. Journal of Neuroscience Methods, 156: 342-350,
2006.

Peer-reviewed Conference Proceedings:

T. Ott and R. Stoop; The Neurodynamics of Belief Propagation on Binary Markov
Random Fields. Advances in Neural Information Processing Systems NIPS
’06, 2006.

R. Stoop and T. Ott; Towards a Quantitative Theory of Biocomputation. Proc.
of NOLTA ’06 Bologna, 2006.

N. Stoop, T. Ott and R. Stoop; Loopy Belief Propagation: Benefits and Pitfalls
on Ising-like Systems. Proc. of NOLTA ’06 Bologna, 2006.

T. Ott, A. Kern and R. Stoop; Faster Spike Sorting with Belief Propagation.
Proc. of NOLTA ’06 Bologna, 2006.

A. Kern, T. Ott and R. Stoop; Acoustic Source Separation by Atomic Signal
Decomposition. Proceedings of NOLTA ’06 Bologna, 2006.

A. Kern, T. Ott and R. Stoop; Source Separation by Atomic Signal Decomposition.
Proc. of NDES’06, p. 77-80, 2006.

T. Ott, M. Christen and R. Stoop; An Unbiased Clustering Algorithm Based
on Self-organisation processes in Spiking Neural Networks. Proc. of NDES’06,
p. 143-146, 2006.

Y. Uwate, T. Ott, R. Stoop and Y. Nishio; Performance of Feedforward Neural
Network with External Influence Function for Back Propagation Learning. RISP
InternationalWorkshop on Nonlinear Circuits and Signal Processing (NCSP’06), 2006.



2005:

Peer-reviewed Journals:

T. Ott, A. Kern, W.-H. Steeb and R. Stoop; Sequential Clustering: Tracking
Down the Most Natural Clusters. Journal of Statistical Mechanics: theory and
experiment: P11014, 2005.

M. Christen, T. Ott, A. Kern, N. Stoop and R. Stoop; Periodic Economic Cycles:
The Effect of Evolution and Control. Journal of Statistical Mechanics: theory
and experiment: P11013, 2005.

Peer-reviewed Conference Proceedings:

T. Ott, M. Frey, R. Stoop; Criticality and Computation in Random Threshold
Networks with Noise. Proc. of NOLTA 2005 Bruges, 2005.

T. Ott, J. Dauwels and R. Stoop; Sequential Clustering by Loopy Belief Propagation.
Proc. of ECCTD 2005 Cork, 2005.


2004:

Peer-reviewed Journals:

T. Ott, A. Kern, A. Schuffenhauer, M. Popov, P. Acklin, E. Jacoby and R.
Stoop; Sequential Superparamagnetic Clustering for Unbiased Classification of
High-dimensional Chemical Data. Journal of Chemical Information and Computer
Sciences, 44 (4): 1358-1364, 2004.

J.-J. van der Vyver, M. Christen, N. Stoop, T. Ott, W.-H. Steeb and R. Stoop;
Towards Genuine Machine Autonomy. Robotics and Autonomous Systems, 46
(3): 151-157, 2004.

Peer-reviewed Conference Proceedings:

T. Ott and R. Stoop; Human-like Perception Using Sequential Superparamagnetic
Clustering. Proceedings of NOLTA’04 Fukuoka, 2004.

T. Ott, W.-H. Steeb and R. Stoop; The Stochastic Network Approach to Clustering.
Proc. of NOLTA’04 Fukuoka, 2004.

M. Christen, T. Ott and R. Stoop; Spike Train Clustering Using a Lempel-Ziv
Complexity-based Distance Measure. Proc. of NOLTA’04 Fukuoka, 2004.

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