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Sara Stymne is a Senior Lecturer in Computational Linguistics at the Department of Linguistics and Philology, Uppsala University, where she has been working since 2012. She initially joined as a post-doc (2012-2015), then worked as a researcher (2015-2017), and served as an assistant professor (2017-2023) before her current position as Senior Lecturer. Prior to Uppsala, she was a researcher at Linköping University's Department of Computer and Information Science. Dr. Stymne earned her PhD in Computational Linguistics from Linköping University in 2012 with the thesis 'Text Harmonization Strategies for Phrase-Based Statistical Machine Translation,' following a Licentiate degree in Computational Linguistics (2009) and a Master's degree in Cognitive Science (2006), both also from Linköping University. During her doctoral studies, she spent the autumn of 2010 and spring of 2009 at Xerox Research Centre Europe in Grenoble, France. Her primary research interests focus on cross-lingual natural language processing and digital humanities, with particular emphasis on multilingual dependency parsing. Dr. Stymne is passionate about applying computational linguistics to solve research questions in other fields, including language history, literary analysis, and political science. Her earlier work concentrated on machine translation, with specific interests in discourse-aware translation, compound processing, and error analysis. She has made significant contributions to the development of language technology tools for analyzing dialogue, narrative, and stylistic features in literature. Analysis of Dr. Stymne's recent publications reveals a strong focus on cross-lingual and cross-domain natural language processing. Her work spans multiple subfields including dependency parsing across genres and topics, discourse relation analysis in low-resource languages like Egyptian Arabic, direct speech identification in Swedish literature, and causality detection in governmental documents. A notable trend is her application of NLP techniques to digital humanities problems, particularly in analyzing literary texts and historical language change. Her research often involves creating and utilizing specialized datasets for specific linguistic phenomena across multiple languages. Dr. Stymne actively supervises graduate students, having guided numerous master's and bachelor's theses on topics ranging from speech recognition to multilingual parsing and causality detection. She leads or participates in several research projects including 'Fictional prose and language change' (funded by VR, 2021-2023) and 'Enabling climate-resilient development' (funded by Marianne and Marcus Wallenberg Foundation, 2023-2027), demonstrating her commitment to interdisciplinary research with practical applications. Her work has resulted in several notable software resources including uuPronPred for cross-lingual pronoun prediction, uuparser for dependency parsing, and Docent for document-level machine translation. Within the Computational Linguistics and Language Technology group at Uppsala University, Dr. Stymne contributes to multiple research initiatives focused on developing language technology tools for digital humanities applications. Her team works closely with literary scholars and historians to create computational methods for analyzing large corpora of literary texts, particularly focusing on Swedish literature across different historical periods. Her research bridges the gap between theoretical computational linguistics and practical applications in the humanities, creating new methodologies for quantitative analysis of literary and historical texts.

• Computational Linguistics
• Natural Language Processing
• Cross-lingual NLP
• +7 more

Nina Tahmasebi is a Professor at the University of Gothenburg, affiliated with the Department of Linguistics and Theory of Science. Her research focuses on computational methods for studying lexical semantic change, particularly through projects like the 6-year RJ-funded 'Change is Key!' initiative. She leads interdisciplinary teams collaborating with institutions such as the University of Lund and Queen Mary University of London. Her work bridges computational linguistics and the humanities, emphasizing data science applications in historical text analysis, sentiment lexicon creation, and argument mining at Språkbanken . Her research interests include developing robust evaluation frameworks for semantic change detection, leveraging AI and NLP for humanities research, and improving accessibility of historical parliamentary data. She teaches statistics for humanities researchers and leads study circles on data science applications in the field. Key contributions include the DWUGs dataset for multilingual semantic change analysis, the DURel annotation tool, and frameworks like TRoTR for evaluating text reuse. Her publications span semantic shift detection, word sense induction, and benchmarking Swedish language models (e.g., Superlim). Advising and grants involve leading teams of researchers and engineers on EU and national grants. She collaborates with the Center for Digital Humanities (CDH) and contributes to Swedish NLP infrastructure through initiatives like SentSALDO and parliamentary data enhancement projects.

• Computational Lexical Semantic Change Detection
• Data Science for the Humanities
• Natural Language Processing (NLP)
• +3 more

Linnéa Bäckström is a Senior Lecturer at the School of Education, Humanities and Social Sciences, Halmstad University. She holds a PhD in Nordic Languages and specializes in Swedish linguistics, focusing on language change and grammatical evolution. University: Halmstad University School: School of Education, Humanities and Social Sciences Academic Rank: Senior Lecturer Research Interests: Language Change Grammatical Change Swedish Syntax Constructicon Resource Development Cross-Lingual Construction Analysis Publications demonstrate expertise in historical linguistics, computational methods for construction identification, and comparative studies between English, Swedish, and Brazilian Portuguese. Her work on HA-omission in Swedish traces syntactic innovations from contact phenomena to standardized usage.

• Linguistics
• Historical Linguistics
• Grammatical Change
• +3 more

Henrik Kaatari is a Senior Lecturer in the Department of English at the University of Gävle . His research focuses on corpus linguistics , language learning , and formality in academic writing , with particular interests in grammatical variation , syntactic complexity , and the impact of extramural English (EE) activities on L2 writing development. Current Project : Principal Investigator of the ComplEExity Project (RJ P23-0437), funded by the Bank of Sweden Tercentenary Foundation, investigating EE's impact on Swedish secondary students' L2 writing. Research Areas : Lexical complexity, register variation, phraseology, and self-initiated language learning. His recent publications analyze the relationship between extramural exposure (e.g., gaming, YouTube) and improvements in lexical diversity and grammatical complexity. Using the Swedish Learner English Corpus , Kaatari employs cross-sectional designs and complexity measures to assess writing development across lexis, phraseology, and grammar. His work has practical implications for English pedagogy in Swedish schools.

• Corpus Linguistics
• Language Learning
• Grammatical Variation
• +3 more

Joakim Nivre is a Professor of Computational Linguistics at Uppsala University in the Department of Linguistics and Philology. His research primarily focuses on grammatical analysis, studying how to analyze typologically different languages in a uniform way within the Universal Dependencies project, and developing better computational models for automatic analysis within this framework. His teaching is associated with the international Master's Program in Language Technology. His research interests include: Computational Linguistics and Natural Language Processing Dependency Parsing and Universal Dependencies Cross-linguistic Analysis and Multilingual NLP Syntax Analysis and Grammatical Frameworks Language Resource Development Nivre's publication record demonstrates significant contributions to dependency parsing, treebank development, and cross-linguistic analysis. His recent work (2023-2024) shows expansion into evaluating generative language models, resource-efficient NLP techniques, climate change impact analysis, causality detection in governmental documents, and historical text processing. His research bridges theoretical linguistics with practical computational applications, with particular emphasis on creating frameworks that work across diverse languages. His work on the Universal Dependencies framework has been particularly influential, establishing a standard resource that enables consistent syntactic annotation across numerous languages, significantly impacting the field of multilingual natural language processing.

• Computational Linguistics
• Dependency Parsing
• Universal Dependencies
• +5 more