جستجوی استاد راهنمای دانشگاهی

• Linguistics
• Natural Language Processing
• Computational Linguistics
• +۲ مورد دیگر

Milan Kuchtiak is a researcher at the Institute of Formal and Applied Linguistics (UFAL), Faculty of Mathematics and Physics, Charles University in Prague. His work bridges theoretical linguistics with practical computational applications in language technology. His research spans core areas of modern linguistics: Natural Language Processing for machine translation and text analysis Computational modeling of linguistic structures Formal grammatical frameworks Applied language resource development These interests drive innovations in human-language technology interfaces and multilingual systems. UFAL operates as a dynamic research hub where theoretical linguistics converges with computer science to solve real-world language challenges across European and global contexts.

• Computational Linguistics
• Morphology
• Grammar
• +۷ مورد دیگر

Jiří Hana is a researcher at the Institute of Formal and Applied Linguistics (UFAL), Faculty of Mathematics and Physics, Charles University in Prague. His work focuses on computational linguistics, particularly resource-light morphological analysis, learner corpora, and grammar modeling for morphologically complex languages like Czech and Russian. Key Research Areas : Computational morphology, learner corpus annotation, grammar models for fusional languages, tagset design, and natural language processing. Grants & Support : Funded by the U.S. NSF (award #0916280) and the Czech Republic Grant Agency (P406/10/P328). Publication Trends : His recent work (2017–2020) emphasizes syntactic annotation of non-native Czech within Universal Dependencies frameworks, leveraging learner corpora for language acquisition research, and developing tools like feat and law for morphological disambiguation. Advising Roles : Supervised 9 students (2011–2024) on projects spanning text classification, error detection, quote attribution, and multilingual learning through audiovisual input. Tools & Contributions : Developed the Russian positional tagset (2010), feat (layered error annotation), and law (manual morphological disambiguation).

Jana Strakováمشاهده پروفایل

پژوهشگر

• Natural Language Processing
• Deep Learning
• Multilingual Text Processing
• +۳ مورد دیگر

Jana Straková is a researcher at the Institute of Formal and Applied Linguistics (ÚFAL) within the Faculty of Mathematics and Physics at Charles University in Prague. Her work focuses on advancing natural language processing techniques for multilingual applications, particularly in deep learning architectures for linguistic analysis. Her research interests span Natural Language Processing , Deep Learning , and Multilingual Text Processing with specialization in named entity recognition, dependency parsing, and morphological analysis. She has pioneered neural network approaches for tasks like diacritics restoration and grammar error correction, with particular emphasis on Czech language processing while extending methodologies to Latin and other languages. Analysis of her publication record from 2019-2025 reveals consistent innovation in NLP tool development, particularly the NameTag and UDPipe systems. Her work demonstrates strong integration of contextual embeddings with linguistic resources, showing increasing focus on cross-lingual transfer and historical language processing in recent years. As part of the ÚFAL research group, she collaborates extensively with Milan Straka and Jan Hajič on developing open-source NLP pipelines. Her projects include creating large-scale datasets like CWRCzech for web relevance ranking and advancing ontology engineering through LLM-augmented approaches.

• Dependency Syntax
• Morphological Analysis
• Computational Linguistics
• +۷ مورد دیگر

Daniel Zeman is an Associate Professor at the Institute of Formal and Applied Linguistics (ÚFAL), Faculty of Mathematics and Physics, Charles University in Prague. His work focuses on computational linguistics, particularly morphological analysis and dependency syntax of natural languages. He co-leads the Universal Dependencies project, a major international effort to create cross-linguistically consistent treebank annotation that has become a de-facto standard in the field, currently covering 148 languages with biannual releases. Dr. Zeman's research interests include: Computational models of morphology and syntax Multilingual approaches working across typologically different languages Cross-lingual techniques supporting disadvantaged languages with limited resources Harmonized data resources for multilingual processing Deep syntactic relations, semantic roles, and coreference His publication record shows a consistent focus on universal frameworks for linguistic annotation. The Universal Dependencies project, which he co-leads, represents a paradigm shift in how linguistic resources are created and shared across languages. His work bridges theoretical linguistics with practical language technology applications, with particular emphasis on making NLP accessible for resource-poor languages through cross-lingual transfer techniques. Scientific recognition includes: Fulbright-Masaryk Fellowship (2006-2007) at University of Maryland Dean's award for best monograph at the Faculty of Mathematics and Physics (2018) Senior area chair for LREC-COLING 2024 (CORE B conference) Area chair for ACL 2020 (CORE A* conference) Dr. Zeman has supervised 19 graduate students to completion (1 PhD, 13 Master's, 5 Bachelor's) as of March 2024. He leads several major research initiatives including Universal Dependencies (since 2014), CorefUD (since 2021), and is Vice-Chair of COST Action UniDive (2022-2026). His current projects span historical linguistics (HiČKoK, 2023-2026) to language understanding from syntax to discourse (LUSyD, 2020-2024). He has developed key linguistic resources including Interset (tagset conversion framework), HamleDT (harmonized treebanks), and Universal Dependencies. With over 5,468 citations and an h-index of 28, his work has significantly shaped modern computational linguistics methodology.

• Theatre Studies
• Cultural Transfers
• Central European Theatre
• +۴ مورد دیگر

Iva Mikulová is an Assistant Professor at the Department of Theatre Studies within Masaryk University's Faculty of Arts. Her office is located at Gorkého 57/7 in Brno, Czech Republic. She specializes in theatre studies with interdisciplinary research spanning cultural transfers, Central European theatre practices, and contemporary performance analysis. Her research explores: Cultural exchange mechanisms in Central European theatre Methodologies for analysing intercultural performance practices Contemporary Czech and Slovak dramatic literature Historical theatre networks during political transitions Interdisciplinary approaches to performance criticism Recent publications (2024) focus predominantly on Central European theatre, including critical analyses of German and Austrian productions, interviews with Czech/Slovak artists, historical examinations of protectorate-era drama, and cultural commentary on contemporary theatre scenes. Her works frequently employ comparative analysis across geographical and historical contexts. She leads the research project Cultural Transfers in Contemporary Central European Theatre Direction (2024) and participates in multiple collaborative projects including: Current Challenges of Theatre Studies II (2025) Research on theatre culture in interdisciplinary overlaps (2019-2023) Interculturality and multilingualism of the Czech lands (2022-2023)

• Computational Linguistics
• Natural Language Processing
• Language Technology Infrastructure
• +۵ مورد دیگر

Jan Hajič is a Full Professor of Computational Linguistics and Deputy Director of the Institute of Formal and Applied Linguistics at Charles University in Prague, Czech Republic. He also directs the LINDAT/CLARIAH-CZ infrastructure, part of the EU CLARIN network. His academic roles include Adjunct Full Professor at the University of Colorado Boulder (since 2016). He holds leadership positions in major initiatives like the European Language Grid (ELG) and chairs META-NET, the European language technology network. Education: PhD in Computational Linguistics (1995) from Charles University, with earlier studies in Mathematics and Physics (1984). Industrial experience includes IBM Research (1991) and Johns Hopkins University (1999–2000 as Visiting Assistant Professor). Research interests focus on semantic analysis, multilingual NLP, treebanking (e.g., Prague Dependency Treebank), and large-scale language technology infrastructure. He leads projects like OpenEuroLLM (2025), HPLT (2022–2025), and UMR (2023–2027). Over 180 publications and a book on computational morphology highlight his scholarly contributions. Awarded Donatio Prize (2022), Silver Medal (2020), and recognition for best student paper (2005). PI/co-PI of 40+ projects, including EU Horizon grants and NSF-funded initiatives. Key roles in international conferences: ACL 2010 General Chair, CoNLL Shared Tasks, and TLT workshop series. Labs/Teams: Oversees LINDAT/CLARIAH-CZ, collaborates with Brandeis University, University of Colorado Boulder, and European research consortia. Active in policy through Czech Science Foundation and EU advisory boards.

• Natural Language Processing
• Artificial Intelligence
• Information Extraction
• +۴ مورد دیگر

Assoc. Prof. Pavel Pecina, Ph.D., is a faculty member at the Institute of Formal and Applied Linguistics, Faculty of Mathematics and Physics, Charles University, Prague, Czech Republic. His primary academic role as an Associate Professor focuses on Natural Language Processing , Artificial Intelligence , and related areas. Research Interests: Information extraction, information retrieval, machine translation, multimodal data interpretation, optical music recognition Teaching: Courses since 2012-2022 including Natural Language Processing , Information Retrieval , and Statistical Methods in NLP Key Research Projects include GI-Insight (AI for healthcare), RES-Q+ (global stroke care registry), and MEMORISE (heritage digitization). His recent publications (2023-2025) demonstrate expertise across clinical NLP , historical document analysis , and music technology domains. Advising: Supervised 10+ graduate students in areas ranging from semantic search to optical music recognition. Collaborates with international institutions on multilingual translation and medical informatics challenges through initiatives like IWSLT and CLEF eHealth.

• interpretation of deep neural networks
• machine learning
• dependency syntax
• +۳ مورد دیگر

David Mareček is a researcher at the Institute of Formal and Applied Linguistics (ÚFAL) within the Faculty of Mathematics and Physics at Charles University. His work focuses on neural network interpretation, machine learning, dependency syntax analysis, and machine translation, with a particular emphasis on unsupervised and semi-supervised parsing techniques. Current projects: GenderBias (2023–present), EduPo (2024–present) Long-term contributions in dependency treebanks (HamleDT, 2012–2016) and neural machine translation frameworks (Treex, TectoMT) His research explores linguistic structure in neural architectures, including BERT and Transformer models, through methods like structural probing and attention analysis. Recent publications examine gender bias mitigation, automated poetry analysis, and theatre script generation. Key collaborations include Rudolf Rosa, Tomáš Musil, and Tomasz Limisiewicz. He supervises students in projects spanning multilingual representations, language model probing, and bias detection in AI systems. Technical leadership in developing tools like THEaiTRobot and DEPFIX demonstrates his commitment to applied computational linguistics and robust NLP systems.

Milan Strakaمشاهده پروفایل

استاد

• Machine Learning
• Artificial Neural Networks
• Deep Learning
• +۱۲ مورد دیگر

Milan Straka is a professor at the Institute of Formal and Applied Linguistics (ÚFAL) within the Faculty of Mathematics and Physics at Charles University, Prague. His research focuses on machine learning, artificial neural networks, deep learning, and structured prediction with applications to natural language processing (NLP) tasks including POS tagging, dependency parsing, named entity recognition, and optical music recognition. University: Charles University School: Faculty of Mathematics and Physics Department: Institute of Formal and Applied Linguistics Straka has developed several NLP tools like UDPipe and NameTag, contributing to multilingual coreference resolution, Czech grammar error correction, and historical language processing pipelines. His recent work involves contextualized embeddings, semantic parsing, and large-scale dataset creation for Czech NLP tasks. He collaborates on European Language Grid initiatives and has participated in multiple shared tasks (CRAC, MRP, W-NUT). His publications span topics from algorithm design (functional data structures) to modern transformer-based language models (RoBERTa) with emphasis on Czech language resources.

• Neural Machine Translation
• Multilingual Neural Machine Translation
• Simultaneous Speech Translation
• +۴ مورد دیگر

Dominik Macháček is a researcher at the Institute of Formal and Applied Linguistics (ÚFAL) at Charles University's Faculty of Mathematics and Physics in Prague. He successfully defended his PhD thesis titled 'Multi-Source Simultaneous Speech Translation' in June 2024 and is currently active in research while preparing for a post-doctoral fellowship at the University of Edinburgh starting in January 2026. His research focuses on Neural Machine Translation , particularly Simultaneous Speech Translation where translation happens in real-time with minimal latency (typically 2-4 seconds). His work spans Multilingual Neural Machine Translation, Quality Estimation for speech translation systems, and Human-to-Human Cross-Lingual Communication. His current 'Live Credible Translation' project aims to enhance simultaneous speech translation by adding quality estimation modules to improve credibility of real-time translations. Macháček has secured a US patent (12,056,457 B2) in August 2024 for a 'Computer-implemented method of real time speech translation and a computer system for carrying out the method'. His research has been presented at major conferences including ACL and IWSLT, particularly through his work on the SimulStreaming system which enables large foundation models like Whisper to operate in simultaneous mode. His publication record shows a consistent focus on real-time translation challenges, with recent work examining robustness to transcription errors, correlation between automatic metrics and human ratings, and continuous rating methodologies for human evaluation. His research trajectory demonstrates progression from theoretical foundations to practical applications with significant industry relevance. Macháček actively supervises Bachelor's and Master's theses and teaches the NPFL140 Large Language Models course. He is involved in multiple research projects including CEDMO 2.0, InCroMin, Sign LLM, NEUREM3, and ELITR. His future work will focus on advancing the state of the art in simultaneous speech translation through his 'Live Credible Translation' project at the University of Edinburgh.

• Discourse Analysis
• Sentence Information Structure
• Word Order
• +۷ مورد دیگر

Kateřina Rysová is a researcher at the Institute of Formal and Applied Linguistics (ÚFAL), Faculty of Mathematics and Physics, Charles University in Prague. Her work focuses on discourse analysis, sentence information structure, Czech word order, dependency syntax, corpus linguistics, and historical Czech studies. Key Affiliations: Charles University in Prague (ÚFAL), Institute of Czech Language (Czech Academy of Sciences), Czech-German collaborations. Research Interests: She investigates how contextual and valency factors shape Czech word order, with a focus on obligatory and free verbal modifications. Her work bridges functional generative description with empirical corpus analysis, including studies on discourse connectives (primary vs. secondary), text coherence, and older Czech syntax. Publication Trends: Her recent articles (2018–2015) emphasize discourse connectives, coherence evaluation, and Czech-German comparative syntax. Earlier works (2014–2011) explore valency-driven word order, annotation principles in the Prague Dependency Treebank, and historical Czech lexicon. Her contributions to older Czech studies include lexicographical projects like the Lexikální databáze humanistické a barokní češtiny (2010) and Elektronický slovník staré češtiny (2011). Labs & Teams: She contributes to the Prague Dependency Treebank and LINDAT/CLARIN projects, focusing on multilingual corpus annotation and computational analysis of text structure.

• Discourse Analysis
• Corpus Linguistics
• Dependency Syntax
• +۴ مورد دیگر

Magdaléna Rysová is a researcher at the Institute of Formal and Applied Linguistics, Faculty of Mathematics and Physics, Charles University in Prague. Her work focuses on discourse relations, discourse connectives, dependency syntax, and corpus linguistics, with additional contributions to second language acquisition and sentence information structure. Institute of Formal and Applied Linguistics, Charles University in Prague Research Interests: Her research explores how discourse connectives function in Czech, alternative lexicalizations for expressing discourse relations, and the annotation of textual phenomena in treebanks. She has developed computational tools for evaluating text coherence and contributed to multilingual discourse analysis frameworks. Projects: Notable projects include Automatic Evaluation of Text Coherence in Czech (NAKI II), TextLink: Structuring Discourse in Multilingual Europe (COST Action IS1312), and CorefDisk: Coreference and Discourse Relations (GA ČR). These span 2010–2019 and involve collaborations with institutions across Europe. Discourse Annotation: She has played a key role in annotating discourse relations in the Prague Dependency Treebank, including the Prague Discourse Treebank 2.0 (2016), which provides standardized corpora for language technology applications. Labs & Teams: She collaborates extensively with the Prague Czech-English Dependency Treebank team and contributes to international COST Action initiatives. Her work integrates functional generative description with computational linguistics and corpus annotation.

• Computational Linguistics
• Natural Language Processing
• Czech Language Processing
• +۴ مورد دیگر

Zuzana Nevěřílová serves as an Assistant Professor at Masaryk University's Department of Czech Language within the Faculty of Arts. She also maintains external cooperation with the Department of Machine Learning and Data Processing at the Faculty of Informatics, demonstrating interdisciplinary engagement between linguistic theory and computational approaches. Her research interests span computational linguistics with particular emphasis on Czech language processing, natural language processing methodologies, and development of language resources. Her work bridges theoretical linguistics with practical computational applications, focusing on areas such as named entity recognition, text analysis, word embeddings, and language resource development. Dr. Nevěřílová's recent publication trends (2021-2025) reveal strong focus on Czech language technologies, including named entity processing in parallel corpora, efficient language models, and educational applications of NLP. Her work demonstrates consistent contributions to Slavonic language processing communities through workshops like RASLAN and conferences like TSD. Her scientific contributions include extensive publications in proceedings of international conferences and workshops, software development for language resources, and educational materials for digital humanities. She has supervised various projects related to language technology and has contributed to significant resources like the New Encyclopedic Dictionary of Czech and VerbaLex lexical database. Her research has practical applications in language services, educational technology, and digital humanities. Dr. Nevěřílová works within the Institute of the Czech Language at Masaryk University, contributing to research teams focused on Czech language processing, corpus development, and computational lexicography.

• Vietnamese Studies
• Vietnamese Language
• Vietnamese Literature
• +۳ مورد دیگر

Julie Lien Vrbková serves as an Assistant Professor at Masaryk University, holding dual appointments with the Mongolian, Korean and Vietnamese Studies Seminar in the Faculty of Arts and the Department of Sociology in the Faculty of Social Studies. Based at Arna Nováka 1/1, 602 00 Brno, she maintains active correspondence via vrbkova.julielien@phil.muni.cz and teaches Vietnamese language, literature, and culture courses across multiple faculties through Spring 2026. Her research centers on Vietnamese literary traditions with particular emphasis on gender representation, cultural norm evolution, and intercultural dynamics within Czech-Vietnamese communities. Key thematic threads include the portrayal of modern women in romantic literature, self-sacrifice motifs, and cognitive approaches to language-culture relationships, reflecting deep engagement with both historical Vietnamese texts and contemporary diaspora experiences. Analysis of her 2017-2023 publications reveals consistent scholarly focus on Vietnamese women's literary archetypes, comparative cultural studies between Vietnam and China/Czechia, and practical intercultural applications. Her work bridges academic literary analysis with community-oriented projects like library accessibility initiatives and museum collaborations, demonstrating applied research impact. Teaching responsibilities span foundational to advanced Vietnamese language instruction, specialized literature courses, and interdisciplinary topics such as 'Vietnamese women and their place in society' and 'Vietnamese language, thought and culture in a cognitive approach' across the Faculty of Arts and Faculty of Education.