Dr. Somayeh Danafar

Dr. Somayeh Danafar

Dr. Somayeh Danafar
ZHAW Life Sciences und Facility Management

somayeh.danafar@zhaw.ch

Persönliches Profil

Tätigkeit an der ZHAW als

Research Scientist in Predictive Analytics

http://www.ias.zhaw.ch

Arbeits- und Forschungsschwerpunkte, Spezialkenntnisse

Statistical Kernel Methods, Machine Learning, Statistical Learning, Big data analysis

Aus- und Fortbildung

PhD in Machine Learning (Dalle Molle Institute for Artificial Intelligence (IDSIA) - University of Lugano (USI), Switzerland)
Master of Neural & Behavioral Sciences (International Max Planck Research School -Eberhard Karls Universität Tübingen, Germany)
Bachelors of Computer Science (Shahid Beheshti University., Iran)

Publikationen

Beiträge, peer-reviewed

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Bayesian Framework for Mobility Pattern Discovery Using Mobile Network Events

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In: Proceedings of EUSIPCO 2017. www.eusipco2017.org. Kos: EURASIP. Peer reviewed.

Publikationen vor Tätigkeit an der ZHAW

Peer-reviewed Journal Publications:

1. S. Danafar, K. Fukumizu, and F. Gomez:
Kernel-based Information Criterion.
Computer and Information Science (CIS), 8(1), 2015

2. S. Danafar, P. Rancoita, T. Glasmachers, K. Whittingstall, and J. Schmidhuber:
Testing Hypothesis by Regularized Maximum Mean Discrepancy.
International Journal of Computer and Information Technology (IJCIT) 3(2), 2014

3. S. Danafar, A. Giusti, and J. Schmidhuber:
Novel Kernel-based Recognizers of Human Actions.
EUROSIP Journal on Advances in Signal Processing, 2010

4. S. Danafar, L. Taghavi Sheikh, and A. Tavakoli Targhi:
Eye Detection Based on SVD Transforms.
International Journal of Imaging System and Technology, 16 (5), pp. 222-229, 2007

Peer-Reviewed Conference Publications:

1. S. Danafar
Mathematical Modeling of a Biological Odometry
In proceedings of the Annual Meeting of the Cognitive Science Society (CogSci), pp.1446-1451, 2012.

2. S. Danafar, A. Gretton, and J. Schmidhuber:
Characteristic Kernels on Structured Domains Excel in Robotics and Human Action Recognition.
Machine Learning and Knowledge Discovery in Databases, LNCS, Springer, pp. 264-279, European Conference on Machine Learning (ECML), 2010.

3. S. Danafar, and N. Gheissari:
Action Recognition for Surveillance Applications Using Optic Flow and SVM. Springer, pp. 457-466, Asian Conference on Computer Vision (ACCV), 2007.

4. Sh. Tabatabi, and S. Danafar:
Cognitive-functional Modeling of an Intelligent Tutoring System (GLITS).
In proceedings of International Conference on Artificial Intelligence (ICAI), pp. 83-89, 2007.

5. Sh. Tabatabi, and S. Danafar:
Cognitive-functional Modeling of an Intelligent Tutoring System (GLITS).
In proceedings of International Computer Society of Iran (CSI) Conference, pp. 223-230, 2006.

Preprints:

1. S. Danafar, K. Fukumizu, and F. Gomez:
Kernel-based Information Criterion.
arXiv:1408.5810, 2014.

2. S. Danafar, P. Rancoita, T. Glasmachers, K. Whittingstall, and J. Schmidhuber:
Testing Hypothesis by Regularized Maximum Mean Discrepancy.
arXiv:1305.0423, 2013.