Pattarawat Chormai

Pattarawat Chormai

Doktorand (stellvertretender Doktorandenvertreter)
Forschungsinteressen: • deep learning and its interpretability • natural language processing • computational methods in sciences • knowledge acquisition and sampling-based decision-marking • data visualisation

 

Akademischer Werdegang

seit 2019       Doktorand, Max Planck School of Cognition, Leipzig
                        Promotionsarbeit an der Technischen Universität Berlin
                        Betreuer: Klaus-Robert Müller & Grégoire Montavon

2015–2018   Master of Science in Data Science, Technische Universität Eindhoven, Niederlande & Technische Universität Berlin
(Dual-Degree-Program der EIT Digital Master School)

2008–2012   Bachelor of Science in Information Technology, King Mongkut's Institute of Technology, Ladkrabang, Thailand

 

Lehre

2020/2021 Machine Learning (exercise grading), Technische Universität Berlin

 

Publikationen

Chormai, P., Prasertsom, P., Cheevaprawatdomrong, J., & Rutherford, A. (2020). Syllable-based neural Thai word segmentation. Proceedings of the 28th International Conference on Computational Linguistics, Barcelona, Spain. International Committee on Computational Linguistics, 4619–4637. doi:10.18653/vl/2020.coling-main.407

Rieger, L., Chormai, P., Montavon, G., Hansen, L. K., & Müller, K.-R. (2018). Structuring neural networks for more explainable predictions. In H. J. Escalante et al. (Eds.), Explainable and interpretable models in computer vision and machine learning. The Springer series on challenges in machine learning (pp. 115–131). Springer: Cham, Switzerland.

 

 

Foto: Nikolaus Brade

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