Slobodanka Dimova is a Professor of Multilingualism and Language Assessment at the Centre for Internationalisation and Parallel Language Use (CIP) , University of Copenhagen. Her work bridges language policy, assessment literacy, and English-medium instruction (EMI) in higher education. Faculty: Faculty of Humanities Department: Department of English, Germanic and Romance Studies Research Focus: Dimova investigates EMI's impact on teaching practices, test development (e.g., TOEPAS validation), and language assessment literacy for multilingual educators. She emphasizes holistic rating scales and multilingual pedagogy. Grants & Collaborations: Leads projects funded by the Independent Research Fund Denmark (2023-2027, 2014) and ERASMUS+ Strategic Partnerships (2017-2020, TAEC project). Serves as President of EALTA (2023-present) and Editor for Language Testing and Journal of English as a Medium of Instruction . Scientific Awards: Nominated for University of Copenhagen's Innovation Prize 2017 (TOEPAS test)
Martin Klotz is a Researcher at the Institute for German Language and Linguistics, Humboldt University of Berlin, affiliated with the Collaborative Research Center (SFB1412) and the Research Unit for Emerging Grammars (RUEG). His work focuses on corpus linguistics, computational linguistics, and digital humanities infrastructure. He holds an MSc in Cognitive Systems (2019, University of Potsdam) and a BA in German Linguistics & Computer Science (2015, Humboldt University). Key research interests include corpus architectures, historical and parallel corpora, language modeling for non-standard varieties, and research software engineering. He contributes to projects like the RUEG corpus and FALKO learner corpus, emphasizing multilingual and multimodal corpus development. His publications span corpus design, software tools (e.g., Annatto), and analyses of heritage languages. He actively organizes academic events, such as the 2021 DGfS short working group on contrastive corpus methodology. He participates in lab collaborations like Deutsch Diachron Digital and contributes to open-source corpus tools. His work bridges computational methods with linguistic theory, focusing on dynamic language systems.
Marcos Garcia Gonzalez is a Ramón y Cajal Research Fellow at the University of Santiago de Compostela (USC), affiliated with the Department of Spanish Language and Literature and the Center for Research in Intelligent Technologies (CITIUS). His research focuses on computational linguistics, particularly in semantic analysis, multilingual systems, and language technologies for Galician and Portuguese. He leads projects like the Nós Project, advancing Galician's integration into AI and NLP tools. His work includes developing resources like the Parallel Universal Dependencies Treebank and tools such as Bertinho (Galician BERT models). Key areas include idiomaticity detection in word representations, vector models for semantic analysis, and syntactic parsing. Education: PhD in Computational Linguistics from USC (2014), Master in Linguistics (University of Lisbon), and Degree in Portuguese Philology (USC). Postdoctoral research under the Juan de la Cierva fellowship (2016-2020). Awards include Ramón y Cajal and Juan de la Cierva fellowships. Research interests span vector models, multilingual NLP, and semantic compositionality. Projects include LINNA (linguistic-based neural models) and DeepR3 (green language tech). His publications explore topics like homonymy/synonymy representation and Galician language preservation through open-source tools. Key contributions include annotated corpora, coreference resolution systems, and cross-lingual parsing methods. He collaborates on hybrid intelligence systems for education (iRead4Skills) and Responsible AI (DeepR3.gal). Current efforts emphasize leveraging linguistic knowledge to enhance NLP models' interpretability and multilingual support.
Alfonsina Buoniconto is a Researcher in the Department of Humanities at the University of Salerno, Italy. Her academic work primarily focuses on linguistic typology, motion events encoding, and educational linguistics. She maintains regular reception hours on Wednesdays from 12:00-14:00 at the Fisciano Campus, Building D3, Third Floor, Room 015. Dr. Buoniconto's research interests center around linguistic typology, particularly the encoding of motion events in Romance languages. Her work investigates the continuum between verb-framed and satellite-framed languages, with special attention to boundary-crossing events and covert encoding strategies. Her research employs corpus-based methods, diachronic analysis, and cognitive linguistics frameworks to examine how languages express motion phenomena. She has developed the Modeg (Motion Decoding Grid) annotation tool for motion event analysis and has conducted comparative studies between English and Italian, as well as Ancient Greek and Latin. Her recent publications reveal a strong focus on motion events encoding across Romance languages, with particular attention to Italian. The research shows consistent patterns in how Romance languages handle boundary-crossing events, often displaying hybrid characteristics between verb-framed and satellite-framed typologies. Her work also extends to educational applications, particularly in teaching linguistic cohesion to improve reading comprehension among secondary school students. Dr. Buoniconto has collaborated with researchers across Italy on educational projects like LeCo (Leggere e Comprendere), which focuses on enhancing reading and text comprehension skills for high school students in Salerno and Avellino provinces. Her research bridges theoretical linguistics with practical educational applications.
Grzegorz Krynicki is a Senior Researcher at the Faculty of English , Adam Mickiewicz University, Poznań, Poland. He leads the Speech and Language Processing Laboratory , focusing on experimental phonetics, machine translation, and computer-assisted language learning. With a Ph.D. in English (2006) and MA in English (2000) from Adam Mickiewicz University, he has contributed extensively to articulatory phonetics and Polish-English corpus linguistics. Education MA in English, Poznań (2000) Ph.D. in English, Poznań (2006) His research interests bridge Articulatory Phonetics and Machine Learning , with applications in Computer Assisted Pronunciation Teaching , Automatic Speech Recognition , and Corpus Linguistics . He has developed tools like Wordbuilder for corpus-based exercises and IPA2Polglish for phonetic transcription conversion. The articles reflect his expertise in electropalatography (EPG) for L2 pronunciation teaching, phonetic error detection in Polish learners of English, and machine translation systems like POLENG. His work spans Multilingualism , Speech Technology , and Polish-English Contrastive Analysis . Scientific Awards University of Bielefeld scholarship (1999) Professional Activities include participation in the International Society of Phonetic Sciences and development of the Speech and Language Processing Laboratory . He has presented at conferences such as the International Congress of Phonetic Sciences (2019) and Societas Linguistica Europaea meetings, often collaborating with institutions like the University of Colorado and Linköping University.
Dr. Johannes Graën is a Researcher at the University of Zurich , affiliated with the Department of Computational Linguistics under the Faculty of Arts and Social Sciences . He leads the Language Technology group within the Linguistic Research Infrastructure, focusing on corpus linguistics, computer-assisted language learning (CALL), and games with a purpose (GWAP). Primary Affiliation: University of Zurich Role: Researcher and Educator His research emphasizes corpus linguistics , NLP tools for education , and language learning games . He develops web-based infrastructures like the LiRI Corpus Platform and SwissBERT, a multilingual language model tailored for Swiss languages. His work often intersects with machine translation , word alignment , and multilingual resource exploitation . The trends in his publications highlight multimodal corpus analysis , CALL applications , and parallel corpora modeling . He has contributed to tools like Multilingwis and SPARCLING, which enhance the accessibility and annotation of multilingual datasets.
Cristina España i Bonet is a Professor in the Department of Computer Science at the Polytechnic University of Catalonia (UPC), working within the Natural Language Processing group (GPLN) of the Center for Technologies and Applications of Language and Speech (TALP). She holds a Physics degree and a PhD in Cosmology from the University of Barcelona, later transitioning to Natural Language Processing and Machine Translation. Her academic journey includes teaching at both the Faculty of Physics of the University of Barcelona and currently at the Barcelona School of Informatics of UPC. Her research spans multiple areas of computational linguistics with a strong focus on Machine Translation. She has extensive experience in statistical and hybrid translation systems, document-level translation, multilingual systems, and machine learning applications in NLP. Her work often addresses real-world challenges with diverse text genres including news, patents, Wikipedia articles, and social media content. She has made significant contributions to developing translation systems that leverage context beyond the sentence level to improve coherence and quality. Cristina has been actively involved in numerous European and national research projects including OPENMT, OPENMT2, MOLTO, and TACARDI, where she has contributed both research and project coordination. Her recent work shows a growing interest in sign language translation, low-resource language processing, and the intersection of large language models with traditional machine translation paradigms. She has supervised multiple PhD and Master's students in topics related to machine translation and multilingual systems. Member of the Natural Language Processing group (GPLN) at TALP Research Center Supervisor of doctoral and master's theses in NLP and Machine Translation Lead researcher in multiple EU-funded projects on multilingual translation Developer of resources and tools for Wikipedia-based multilingual corpora Her research has evolved from statistical machine translation to incorporate neural approaches while maintaining focus on document-level context and multilingual applications. She has made significant contributions to understanding translation artifacts, developing methods for low-resource language translation, and creating resources for sign language processing. Her work bridges theoretical advances with practical applications across diverse language pairs and domains.
Iryna Smushchynska serves as Professor and Head of the M. Zerov Department of Theory and Practice of Translation from Romance Languages at Taras Shevchenko National University of Kyiv since 2011, following academic progression from Lecturer (1994) to Associate Professor (1995-2004) and Professor of French Philology (2004-2011). Her academic credentials include: 1984: Graduate, Faculty of Romance-Germanic Philology, Taras Shevchenko National University of Kyiv 1993: PhD in Philology (Romance Languages) 2003: Doctor of Philological Sciences 2011: Full Professor Professor Smushchynska's research centers on Translation Studies and Stylistics of Romance Languages, with emphasis on stylistic translation phenomena, pragmatics, literary translation, and computational lexicography. Current investigations examine micro/macro discourse elements in translation, artistic image transfer, stylistic tropes, denotative/connotative meaning preservation, and author-translator idiolect dynamics, utilizing interdisciplinary frameworks from linguistics, psycholinguistics, and computer science. Her 15 most recent publications (2009-2018) reveal strong thematic continuity in semantic analysis of translation challenges, particularly regarding archaisms, enantiosemy, and metaphorical language. Methodologically, she integrates corpus-based approaches with cognitive and computational perspectives, focusing predominantly on French-Ukrainian translation while expanding to Spanish, Italian, and Portuguese language pairs. As research group leader, she has supervised 17 PhD theses over the past decade, producing monographs, textbooks, dictionaries, and software tools. Her team edits the scientific collection 'Style and Translation' and provides expertise in conference interpreting training and comparative stylistics. The research group operates through interdisciplinary collaboration, employing parallel/comparable corpora to analyze translation phenomena across stylistics, literary studies, sociolinguistics, and computational linguistics, with emphasis on empirical validation of theoretical frameworks.
Rico Sennrich is an Assistant Professor at the University of Zurich's Department of Computational Linguistics, specializing in natural language processing with a focus on machine translation and multilinguality. He is also an Honorary Fellow at the University of Edinburgh and an ELLIS Fellow. His research spans low-resource and efficient methods, interpretability and model analysis, and multimodal language processing, particularly known for work on tokenization, neural architectures, and data augmentation. His research interests include developing practical solutions for multilingual machine translation, addressing challenges in low-resource scenarios, improving model efficiency, and analyzing how neural networks process language. He has made significant contributions to subword tokenization techniques and neural architecture design that have been widely adopted in both research and industry applications. His work often bridges theoretical insights with practical implementations to advance the state of the art in NLP. His recent publications reflect trends toward addressing bias in machine translation, improving document-level translation, enhancing multilingual capabilities, and developing more efficient inference methods for large language models. His research increasingly focuses on the intersection of machine translation with multimodal processing and low-resource language scenarios. ELLIS Fellow Honorary Fellow at the University of Edinburgh Action editor for Computational Linguistics and ACL Rolling Review Standing reviewer for TACL Senior area chair for ACL 2025 Professor Sennrich has advised numerous PhD students whose work has received recognition, including ACL outstanding paper awards and best thesis awards. He leads research projects such as Evolving Language (2024-), InvestigaDiff (2024-2027), and MT for Romansh idioms (2025-2026), having previously led the MUTAMUR project (2019-2025). His laboratory focuses on practical NLP solutions with real-world impact, particularly in multilingual and low-resource scenarios. The team actively collaborates with industry partners and participates in major research initiatives like ELITR.
Dmitry Idiatov is a Director of Research at the French National Center for Scientific Research (CNRS) within the LLACAN laboratory (Language, Languages and Cultures of Africa), focusing on African Linguistics , particularly Mande and Adamawa languages. He holds a PhD in Linguistics and Literature from the University of Antwerp (2007), a Master's degree in Oriental and African Studies from Saint Petersburg State University (2003), and a Bachelor's degree in Oriental and African Studies from the same institution (2001). His research spans comparative/diachronic linguistics , typology , phonetics , and language documentation . His scholarly work emphasizes interrogative pronominals , non-selective markers , and clause-final negation patterns . He explores diachronic typology, linguistic prehistory, and areal diffusion in Sub-Saharan Africa, particularly through studies on labial-velar stops , nasal vowel systems , and logophoricity . He is actively involved in projects like the BULB initiative for under-resourced language documentation and serves on editorial boards for journals such as Folia Linguistica Historica and Mandenkan . His conference organization includes workshops on areal phenomena and negation patterns in African languages. Contact: dmitry.idiatov@cnrs.fr . Official website: Dmitry Idiatov's Academic Profile .
Dr. Toral Ruiz is an Assistant Professor at the University of Groningen 's Faculty of Arts . Her research focuses on Machine Translation , Computational Linguistics , and Natural Language Processing , with particular emphasis on translation quality assessment, literary adaptation, and ethical automation frameworks. Expertise: Machine Translation, Computational Linguistics, NLP, Translation Quality, Literary Adaptation, Ethical Automation Contact: a.toral.ruiz@rug.nl Her recent work explores speech-text discrimination , tokenization strategies , and lexical diversity in literature . She contributes to the European Association for Machine Translation and collaborates on projects like LT-LiDER for digital literacy in translation. Press engagement includes discussions on machine translation limitations in creativity and cross-lingual literary reception . Notable collaborations include studies on Catalan/Dutch translation reception and sustainability frameworks for translation automation.
Eneko Agirre is a Professor in the Department of Computer Science and Artificial Intelligence at the Faculty of Informatics, University of the Basque Country. He is a leading researcher in Natural Language Processing with a strong focus on multilingual systems, particularly for the Basque language, and has published extensively in top NLP conferences including ACL, EMNLP, and NAACL. His research spans multiple areas of computational linguistics including word sense disambiguation, machine translation, cross-lingual learning, and information extraction. Agirre has pioneered work on zero-shot learning approaches, data contamination issues in LLM evaluation, and low-resource language processing. His recent work includes developing the Latxa family of Basque language models and creating novel methods like WiCkeD for more challenging benchmarks and GUIDEX for zero-shot information extraction. Analysis of his recent publications reveals a strong trend toward addressing fundamental challenges in large language model adaptation, evaluation reliability, and cross-lingual transfer learning. His work often combines theoretical insights with practical applications, particularly for under-resourced languages like Basque. His research demonstrates how linguistic typology impacts cross-lingual performance and how to overcome data limitations through innovative methodology. Agirre has mentored numerous researchers who have become active contributors to the NLP field, including Oscar Sainz, Jon Ander Campos, and Iker García-Ferrero. His collaborative work spans institutions across Spain and internationally, reflecting his standing in the global NLP community.
CHEN Lian is a linguistics researcher currently serving as an ATER (Temporary Teaching and Research Attaché) at the University of Artois. She holds associate researcher positions at the LLL-CNRS laboratory (University of Orléans) and CRLAO-CNRS-INALCO. Dr. Chen obtained her PhD in Language Sciences from Cergy Paris University, specializing in contrastive analysis of French-Chinese idiomatic expressions. Her academic affiliations include ongoing participation in the DiCoP project (Digital Dictionary and Corpus of Phraseology) and membership in the Société de Linguistique de Paris. Her research spans: Contrastive lexicology and phraseology Digital lexicography and NLP applications Phraseodidactics and language-culture pedagogy Corpus linguistics and metalexicography She has pioneered digital pedagogical frameworks through projects like HYPA (Hyper Pinyin Alphabet) and HELD (Hybrid Language Teaching), implementing Moodle-based flipped classrooms. Publication analysis reveals three dominant themes across her 15 most recent works (2020-2025): Computational phraseology and ontology modeling Cross-cultural analysis of idiomatic expressions Innovations in digital language pedagogy Her research consistently bridges theoretical linguistics with practical applications in NLP and education technology. Awards and recognitions: First Excellence Award for Young Researchers (15th International Conference on Bilingual Dictionaries, 2023) Finalist in "My Thesis in 3 Minutes" competition (Beijing, 2023) She leads several funded projects: Chinese and European Digital Lexicography (2023-2025, G2023157010L) HYPA digital dictionary (Nouvelle-Aquitaine Region, 2020-2022) HELD-IDEX digital pedagogy (Université Grenoble Alpes, 2019-2020) Dr. Chen directs the DiCoP laboratory (phraseologia.com) focusing on electronic phraseological resources and collaborates with international teams on computational lexicography projects. She maintains active involvement in the HYPAquky association as Vice-President for Academic Science.
Cristina España-Bonet is a researcher at the Department of Computer Science (CS) in the Polytechnic University of Catalonia (UPC), where she works in the Natural Language Processing (GPLN) group. Previously, she was affiliated with the University of Barcelona (UB) in the Department of Astronomy and Meteorology (DAM), where she completed her PhD in Cosmology. Her research spans both Natural Language Processing and Cosmology , with a strong focus on Machine Translation and Multilingual Systems . Her work in NLP includes: Statistical and Hybrid Machine Translation Document-level Translation Multilingual Information Retrieval Sign Language Translation Low-resource Language Processing She has contributed to major projects such as: OPENMT MOLTO TACARDI Wikiparable Her research has produced significant resources including: Wikipedia-based comparable corpora Hybrid translation systems for patents Stopword lists for Occitan Sign language translation systems
Pablo Gamallo Otero is a Professor at the University of Santiago de Compostela (USC), affiliated with the Faculty of Philology and the Department of Spanish Language and Literature. He leads research in the LComp Research Group in Computational Linguistics and is part of the Center for Research in Intelligent Technologies (CITIUS). His work focuses on computational linguistics, natural language processing (NLP), and language technologies for minority languages like Galician and Portuguese. He has extensively contributed to projects like the Nós initiative, developing large-scale corpora (e.g., CorpusNÓS) and models for low-resource languages. Key research interests include sentiment analysis, hyperpartisan news detection, neural machine translation (NMT), and cross-lingual paraphrasing. His work bridges theoretical linguistics and practical NLP applications, with a focus on preserving and revitalizing Galician through advanced AI tools. He has collaborated on international initiatives such as the Iberobench benchmark and the SemEval competition, advancing multilingual AI evaluation frameworks. His articles often address challenges in machine translation for Galician, leveraging Portuguese resources via transliteration strategies. He has also explored diachronic language distance measurement, lexical resources for mental health analysis, and dependency-based compositional semantics. His contributions span conferences like PROPOR and TREC, reflecting his role in both academic research and applied technology development.
