Tomáš Musil

Main Research Interests

• representations of meaning
• philosophy of language
• neural machine translation

Projects

Current (as co-investigator)

• TAČR – EduPo
• GAČR – Identification and Prevention of Unwanted Gender Bias in Neural Language Models
• GAČR – SEEM-CZ: Epistemic and Evidential Markers in Czech
• LUSyD: Language Understanding: from Syntax to Discourse

Past (as primary investigator)

• GAUK – Independent component analysis of continuous word representations

Past (as co-investigator)

• TAČR – THEaiTRE
• GAUK – Developing Derivational Networks for Multiple Languages
• GAČR – Linguistic Structure Representation in Neural Networks
• Neural Monkey
• CEMI
• QT21
• ELITR
• GAUK – Using Language Knowledge in Scene Text Recognition

Curriculum Vitae

Education

• pursuing a PhD. in Computational Linguistics, Charles University, Faculty of Mathematics and Physics (since 2017)
• Masters degree in Artificial Intelligence (2014 – 2017), Charles University, Faculty of Mathematics and Physics
• Bachelor degree in Computer Science (2010 – 2014), Charles University, Faculty of Mathematics and Physics
• pursuing a Masters degree in Philosophy, Charles University, Faculty of Arts

Teaching

ZS 2024/2025:

• NPFL130 Filosofie jazyka a NLP
• NPFL129 Introduction to Machine Learning

LS 2023/2024:

• NPFL140 Large Language Models

ZS 2023/2024:

• NPFL130 Filosofie jazyka a NLP
• NPFL129 Introduction to Machine Learning

ZS 2022/2023:

• NPFL130 Filosofie jazyka a NLP
• NMIN111 Programování 1 pro matematiky

ZS 2021/2022:

• NPFL130 Filosofie jazyka a NLP
• Programování 1 a Algoritmizace

ZS 2020/2021:

• NPFL130 Filosofie jazyka a NLP

LS 2019/2020:

• NMIN112 Programování 2 pro matematiky

ZS 2019/2020:

• NMIN111 Programování 1 pro matematiky

Nápady na ročníkové projekty a bakalářské práce:

• Detektor chybějících slov.

Selected Bibliography

• Google Scholar
• ORCID: 0000-0002-4013-560X
• Scopus ID: 55949677700
• Researcher ID: P-5094-2017

Musil, Tomáš. “Examining Structure of Word Embeddings with PCA.” In Text, Speech, and Dialogue, edited by Kamil Ekštein, 211–223. Cham: Springer International Publishing, 2019. https://doi.org/10.1007/978-3-030-27947-9_18.

Musil, Tomáš, Jonáš Vidra, and David Mareček. “Derivational Morphological Relations in Word Embeddings.” In Proceedings of the 2019 ACL Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP, 173–180. Florence, Italy: Association for Computational Linguistics, 2019. https://doi.org/10.18653/v1/W19-4818.