Dr. Mark Cieliebak

Dr. Mark Cieliebak

Dr. Mark Cieliebak
ZHAW School of Engineering
Steinberggasse 13
8400 Winterthur

+41 (0) 58 934 72 39
mark.cieliebak@zhaw.ch

Persönliches Profil

Leitungsfunktion

  • Stv. Schwerpunktleitung Distributed Software Systems (DSS)

Tätigkeit an der ZHAW als

Dozent für Datenanalyse und Software Engineering

http://www.zhaw.ch/~ciel

Lehrtätigkeit in der Weiterbildung

Arbeits- und Forschungsschwerpunkte, Spezialkenntnisse

Software Engineering, Entwicklungsprozesse, Social Media, Data Mining, Algorithmen und Komplexität

Aus- und Fortbildung

Dr. sc. tech, ETH Zürich, 2003
Dipl. Informatiker, Universität Dortmund, 1999

Beruflicher Werdegang

Leiter IT und Entwicklung, Netbreeze GmbH, 2007-2012
Software Ingenieur, sd&m AG, 2005-2007
Algorithmiker, Prolim GmbH, 2005
Postdoc, Universität Santiago de Chile, 2004

Projekte

Projektleitung

Mitarbeit an folgenden Projekten

Publikationen

Monographien und Herausgeberschaften

Schutzbach, Daniel; Uzdilli, Fatih; Cieliebak, Mark (Hg.). ().

Back to the Future

. Time-Travelling-Debugger als Alternative zu klassischen Debuggern.

Frankfurt am Main: Software & Support Media GmbH.

Beiträge, peer-reviewed

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Fully Convolutional Neural Networks for Newspaper Article Segmentation

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In: Proceedings of the 14th IAPR International Conference on Document Analysis and Recognition (ICDAR). Kyoto, Japan: CPS. Peer reviewed.

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Swiss-Chocolate: Combining Flipout Regularization and Random Forests with Artificially Built Subsystems to Boost Text-Classification for Sentiment

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Proceedings of the International Workshop on Semantic Evaluation (SemEval-2015) Peer reviewed.

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Toward Automatic Data Curation for Open Data

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ERCIM News, 100. 32-33. Peer reviewed.

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JOINT_FORCES: Unite Competing Sentiment Classifiers with Random Forest

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Proceedings of the International Workshop on Semantic Evaluation (SemEval-2014) Peer reviewed.

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Meta-Classifiers Easily Improve Commercial Sentiment Detection Tools

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Proceedings of the 9th International Conference on Language Resources and Evaluation (LREC 2014) Peer reviewed.

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Swiss-Chocolate: Sentiment Detection using Sparse SVMs and Part-Of-Speech n-Grams

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Proceedings of the International Workshop on Semantic Evaluation (SemEval-2014) Peer reviewed.

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Applied Data Science in Europe

: Challenges for Academia in Keeping Up with a Highly Demanded Topic.

European Computer Science Summit Peer reviewed.

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Potential and Limitations of Commercial Sentiment Detection Tools

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Proceedings of the First International Workshop on Emotion and Sentiment in Social and Expressive Media: approaches and perspectives from AI (ESSEM 2013) , 1096 47/58. Peer reviewed.

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Distributed Computing by Mobile Robots: Gathering

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SIAM Journal on Computing, 41, 4. 829/879. Peer reviewed.

Beiträge, nicht peer-reviewed

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PANOPTES

: Automated Article Segmentation of Newspaper Pages for "Real Time Print Media Monitoring“.

Proceedings of SGAICO Annual Assembly and Workshop 2015

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Flip your classroom – But be aware!

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Lifelong Learning in Europe (LLinE), 4.