جست‌وجوی استاد و پژوهشگر

• Natural Language Processing
• Computational Linguistics
• Syntax Analysis
• +۴ مورد دیگر

Vojtěch Kovář is a researcher at Masaryk University with dual appointments at the Institute of the Czech Language (Faculty of Arts) and the Center for Natural Language Processing (Faculty of Informatics). He has been affiliated with the university since 2006, holding positions as researcher and lecturer while also working as a software analyst at Lexical Computing CZ since 2012. His research focuses on automatic syntactic analysis of natural languages , particularly Czech and related languages, evaluation of syntactic analysis quality , integration of syntactic tools into downstream applications , and corpus linguistics . His work bridges theoretical linguistics with practical language technology applications. Recent publications reveal a strong trend toward dictionary creation methodologies , lexicographic infrastructure development , and corpus-based language resource compilation . His research increasingly addresses rapid dictionary development for both European and Asian languages, as well as bilingual resource creation in response to emerging language needs. PACLIC 2010 best student paper award Member of eLex conference program committee (2017-present) Kovář supervises bachelor's and master's theses at both the Faculty of Arts and Faculty of Informatics, with recent topics including semi-automatic dictionary creation, web-based proofreading systems, and automatic punctuation correction. He teaches multiple courses including Fundamentals of Mathematics and Statistics for Humanities, Algorithmic Description of Syntax, and Programming Basics for Humanities. His research is supported by projects including LINDAT/CLARIAH-CZ (Digital Research Infrastructure for Language Technologies) and the Web-based spelling, grammar and typographical corrector for Czech language initiative.

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.

• 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.

• Data Protection Law
• Information Technology Law
• Open Data and PSI
• +۷ مورد دیگر

Jakub Míšek is an Assistant Professor at the Institute of Law and Technology, Faculty of Law, Masaryk University in Brno, Czech Republic. His work bridges legal scholarship with information technology, focusing on data protection, open data, and digital regulation. He holds a Ph.D. and multiple academic qualifications, including JUDr. and MgA. His research interests include Data Protection Law , GDPR compliance , Open Data and PSI reuse , proportionality in personal data processing , text and data mining exceptions , and legal aspects of cybersecurity . He explores how legal frameworks adapt to technological innovation, especially in public administration and research contexts. His recent scholarly output shows a strong trend toward interdisciplinary work combining law, computer science, and policy. He frequently publishes on CJEU case law, interoperability of European datasets, and regulatory methods such as accountability and risk-based approaches under GDPR. He is also deeply involved in practical legal guidance and policy recommendations. Co-author of the book Citation Analysis of Case Law (2021) Author of Modern Regulatory Methods of Personal Data Protection (2020) Contributor to Information Technology Law (2018) Co-editor of conference proceedings for JURIX 2024 He has advised on research projects related to law and technology, contributed to national reports on data protection, and organized major academic events such as the Cyberspace and JURIX conferences. His collaborations span across institutions and disciplines, reflecting a robust academic network in legal informatics and digital governance.

• Semantic Annotation
• User Interface Design
• Natural Language Processing
• +۴ مورد دیگر

Dr. Jaroslav Dytrych serves as Assistant Professor and Vice-dean for Information Support at the Department of Computer Graphics and Multimedia (DCGM) within the Faculty of Information Technology, Brno University of Technology. His dual role combines academic leadership in semantic technologies with institutional responsibilities for information systems management. Research focuses on advancing semantic annotation methodologies and user interface design: Semantic Annotation of Complex Textual Relations Empirical Evaluation of Annotation Interaction Patterns Collaborative Semantic Annotator Frameworks (4A System) Integration of Semantic Tools in Scholarly Workflows Java-Based Graphical User Interface Development Practical Software Design Principles His publication record demonstrates consistent innovation in annotation tool design, particularly through the 4A framework which addresses challenges in collaborative semantic processing. Research trends show progressive refinement from foundational scholarly communication models (2011) to advanced user interface solutions for complex relation annotation (2018). As an educator, he directs courses including Practical Aspects of Software Design (IVS) and Graphical User Interfaces in Java (GJA/GJAe), delivered in both Czech and English to undergraduate and graduate students. Office consultations follow structured availability with designated in-person hours on Tuesdays and Wednesdays, supplemented by evening online sessions via Microsoft Teams. Operational within the DCGM research ecosystem, his work intersects with natural language processing laboratories and software engineering teams developing annotation infrastructure. Current projects continue evolving the 4A framework for next-generation scholarly communication platforms.

• Natural Language Processing
• Computational Linguistics
• Dependency Syntax
• +۵ مورد دیگر

Prof. Zdeněk Žabokrtský is a Professor at the Institute of Formal and Applied Linguistics (ÚFAL) within the Faculty of Mathematics and Physics at Charles University in Prague. He serves as the head of the PhD study program in Computational Linguistics and teaches several courses including Language Data Resources, Variability of Languages in Time and Space, Natural Language Processing, and Introduction to Language Technologies. His office is located in room S 409 on the 4th floor in the Lesser Town area of Prague. Prof. Žabokrtský's research spans multiple areas of Natural Language Processing and Computational Linguistics. His primary interests include building multilingual morphological resources, developing NLP applications that utilize parallel corpora, studying dependency syntax and valency frameworks, coreference resolution, theoretical studies on formal representations of natural languages, and applying Machine Learning techniques to linguistic problems. His work bridges theoretical linguistics with practical applications in language technology. Analysis of Prof. Žabokrtský's recent publications reveals a strong focus on morphological analysis, coreference resolution across multiple languages, and cross-lingual NLP. His research spans diverse languages including Czech, Turkish, Russian, and various Indic languages. He has made significant contributions to morphological resources, word-formation networks, and multilingual coreference systems, often creating and utilizing linguistic resources while developing novel computational approaches to linguistic phenomena. As an academic leader, Prof. Žabokrtský has supervised numerous PhD students and contributed to major research projects at the Institute of Formal and Applied Linguistics. His work has been supported by various grants that have enabled the development of important linguistic resources and NLP tools. He has been instrumental in establishing the PhD study program in Computational Linguistics at Charles University. Prof. Žabokrtský is a key member of the Institute of Formal and Applied Linguistics research teams, contributing to projects focused on developing language technologies, creating linguistic resources, and advancing theoretical understanding of natural language processing. His work is closely integrated with the Prague Dependency Treebank project and other major linguistic resources developed at Charles University.

• 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.

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

Eva Fučíková serves as a Researcher at the Institute of Formal and Applied Linguistics (UFAL) within the Faculty of Mathematics and Physics at Charles University, Prague. Her office is located in the historic Lesser Town campus (Malostranské nám. 2/25, Prague 1), with contact accessible via email Eva.Fucikova@mff.cuni.cz and personal webpage http://ufal.mff.cuni.cz/~fucikova/ . Her research spans theoretical and applied linguistics with emphasis on computational approaches. Key focus areas include formal semantics, machine translation frameworks, and natural language processing systems development. The Institute of Formal and Applied Linguistics maintains international prominence in language technology research, particularly in European language processing and cross-lingual transfer learning methodologies. UFAL provides advanced computational resources including high-performance clusters for language modeling and speech processing. The institute actively participates in Horizon Europe projects and maintains strategic partnerships with major European research centers like DFKI and IMT Atlantique. Current research trajectories include low-resource language adaptation and multimodal language understanding systems. Collaborative opportunities exist through the institute's membership in the European Language Grid and participation in annual Prague Linguistics meetings. Prospective researchers should note UFAL's strong industry connections with localization companies and AI startups seeking natural language processing expertise.

Michal Töpferمشاهده پروفایل

مربی

• Machine Learning
• Component-based Systems
• Self-adaptive Systems
• +۴ مورد دیگر

Michal Töpfer is a PhD student and academic tutor at the Department of Distributed and Reliable Systems within the Faculty of Mathematics and Physics at Charles University in Prague. Holding the RNDr. degree (Doctor of Natural Sciences), he actively contributes to both teaching and research at the university. His academic affiliations include: Department of Distributed and Reliable Systems (D3S) Faculty of Mathematics and Physics Charles University Dr. Töpfer's research centers on integrating machine learning with software architecture, particularly for self-adaptive and component-based systems. His work develops systematic approaches to incorporate ML capabilities into software architectures, enabling systems that can self-optimize and adapt to changing conditions. He has made significant contributions to the DEECo component model through his ML-DEECo extension and has developed visualization components for the IVIS framework used in IoT applications. His publication trajectory shows increasing focus on leveraging large language models for software engineering tasks and optimizing component-based architectures. The research spans theoretical foundations of component models to practical implementations addressing real-world challenges in distributed systems, with applications in smart farming and Industry 4.0. As an educator, he teaches practical sessions for undergraduate courses including Introduction to Algorithms and Programming 1 during winter semesters and Programming 2 during summer semesters. While he supervises student work, specific advisees are not documented in available sources. He actively contributes to the academic community through organizing the Mathematical Correspondence Seminar (PraSe), the Young Mathematicians Camp, and the Kasiopea programming competition. His technical expertise spans web development, software architecture, machine learning integration, and data visualization.

• Linguistics
• Formal Linguistics
• Computational Linguistics
• +۳ مورد دیگر

Aleš Macela serves as a Professor at the Institute of Formal and Applied Linguistics (UFAL), a key research unit within the Faculty of Mathematics and Physics at Charles University in Prague. His institutional affiliation reflects deep integration into the university's academic structure through active email contact and formal Czech academic titles. Research expertise centers on theoretical and computational linguistics , with emphasis on formal language modeling and applied natural language processing systems. His work aligns with UFAL's mission to bridge linguistic theory with practical computational implementations, particularly in syntax and semantics frameworks. Affiliation structure: University: Charles University (Univerzita Karlova) School: Faculty of Mathematics and Physics (Matematicko-fyzikální fakulta) Department: Institute of Formal and Applied Linguistics (Ústav formální a aplikované lingvistiky)

• 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.

• Word-formation
• Derivational morphology
• Morphological segmentation
• +۵ مورد دیگر

Associate Professor Magda Ševčíková is a prominent linguist at the Institute of Formal and Applied Linguistics (ÚFAL), Faculty of Mathematics and Physics, Charles University in Prague. She specializes in morphological research with a focus on Czech language, particularly in word-formation, derivational morphology, and morphological segmentation. Her work bridges theoretical linguistics with computational approaches, making significant contributions to language resource development. Dr. Ševčíková's educational background includes a Ph.D. in Mathematical Linguistics (2009) and an Mgr. in Czech and German Philology (2004), both from Charles University. Her habilitation in Linguistics was completed in 2025 with a thesis on conversion between noun and verb in Czech. Her research interests center on word-formation phenomena, particularly conversion processes, derivational morphology of Czech, morphological segmentation, dependency syntax, and named entity recognition. Her publication record reveals a strong focus on data-driven morphological research, with recent work emphasizing corpus-based analysis of noun-verb conversion, derivational networks (particularly DeriNet), and cross-linguistic comparisons of morphological structures. She has pioneered methods for modeling morphographemic alternations and semi-automatic construction of word-formation networks. Dr. Ševčíková has served in significant academic roles including chair of the Czech Science Foundation's evaluation panel for Linguistics and Literature (2023-2025), member of the discipline committee for Social Sciences and Humanities, and Scientific Committee member for the Language Resources and Evaluation Conference. She has led multiple Czech Science Foundation projects on Czech word-formation and morphology. She actively contributes to major linguistic projects including DeriNet (a lexical network of Czech derived words), Universal Derivations collection, Universal Segmentations project, and the Czech Named Entity Corpus. Her work has established important language resources that support both theoretical linguistic research and practical NLP applications.