جستجوی استاد راهنمای دانشگاهی

• Natural Language Processing
• Artificial Intelligence
• Computational Argumentation
• +۳ مورد دیگر

Christina Niklaus is an Assistant Professor in the Department of Computer Science at the University of St. Gallen (HSG). Her research focuses on Natural Language Processing (NLP), Artificial Intelligence (AI), and Computational Argumentation, with an emphasis on text simplification, knowledge representation, and responsible AI. She leads the project 'Conversational AI: Dialogue-based Adaptive Argumentative Writing Support' funded by SNSF Basic Research (2022–2026). Education : Ph.D. in Computer Science, University of Passau, Germany (2022) M.Sc. in Computer Science, University of Passau, Germany (2016) B.Sc. in Applied Computer Science, University of Bamberg, Germany (2011) Research Interests : Christina Niklaus develops AI systems to bridge complex information with human understanding, emphasizing accessibility and ethical integrity. Her work includes: Context-aware NLP systems for simplifying technical texts Computational tools for enhancing argumentation skills in academic writing Open Information Extraction (OIE) for structured knowledge representation Responsible AI frameworks ensuring fairness and transparency Recent Article Trends : Her recent work explores large language models (LLMs) in education, discourse-aware text simplification, and argument quality assessment. Key contributions include applying FinBERT for financial text analysis and developing adaptive writing support systems. Awards : Best Paper Award (ECEI 2024) Best Paper Nomination (CSEDU 2023) Nominated for GI-Dissertationspreis (2022) delina Innovation Award (2021) Teaching & Grants : Teaches Database Systems and Advanced Databases at HSG Principal investigator of multiple grants including SNSF Basic Research Labs/Teams : Her research group focuses on interdisciplinary AI applications in education and argumentation, collaborating with institutions like LEARNTEC and CHI.

Sarah Eblingمشاهده پروفایل

استاد

• Computational Linguistics
• Assistive Technologies
• Sign Language Technologies
• +۷ مورد دیگر

Sarah Ebling is a Full Professor of Language, Technology and Accessibility at the University of Zurich's Faculty of Arts and Social Sciences. She leads the Language, Technology and Accessibility research group within the Institute for Computational Linguistics. Her work focuses on computational linguistics applications for assistive technologies targeting disabilities such as hearing impairments, visual impairments, and cognitive disorders. Key areas include sign language technologies, automatic text simplification, and audio description systems. She directs the large-scale Swiss innovation project 'Inclusive Information and Communication Technologies' (2022-2026, CHF12 million budget) and collaborates on EU H2020 and SNSF Sinergia projects. Education: Holds a doctoral degree (summa cum laude, 2016) from the University of Zurich with research on automatic translation to Swiss German Sign Language. Completed studies in German Linguistics, Computational Linguistics, and English Linguistics at Universities of Zurich and Heidelberg, with research stays in Dublin, Chicago, and Rochester. Research emphasizes multimodal accessibility solutions, including sign language fluency assessment, gesture-based interaction, and AI-driven text adaptation. Current projects explore audio description translation systems (SwissADT), sign language corpus development (SwissSLi), and digital tools for comprehensibility assessment in simplified texts. Her work bridges computational linguistics with ethical considerations in assistive technology deployment. Grants and Leadership: Principal Investigator on major accessibility-focused grants, including the CHF12M Swiss innovation project. Supervises PhD candidates in areas like sign language assessment tools and text simplification algorithms. Active in international collaborations, publishing extensively in computational linguistics and accessibility journals/conferences. Technology Development: Created the 'DigiSpon' benchmark for language sample analysis and developed open-source tools for sign language translation baselines. Her team's innovations include the SignCLIP model connecting text and sign language via contrastive learning, and pose estimation frameworks for sign language recognition.

Lisa Beinbornمشاهده پروفایل

استاد

• Natural Language Processing (NLP)
• Multilingual Language Models
• Cognitive Plausibility in NLP
• +۵ مورد دیگر

Lisa Beinborn is a Professor for Human-Centered Data Science at the University of Göttingen, leading the Human-Centered Data Science group. Her research bridges natural language processing with cognitive science, focusing on multilingual models and interpretability. PhD in Computer Science (2016), Technische Universität Darmstadt MSc in Computational Linguistics (2010), Saarland University & Bolzano, Italy BSc in Computational Linguistics (2008), Saarland University & Barcelona, Spain Her research explores cognitive plausibility in NLP, analyzing how language models process language differently from humans. Key areas include multilingual model interpretability, semantic drift, eye-tracking, and readability prediction. Recent work examines input representation stability in neural models, cross-lingual transfer of complexity, and aligning language models with human cognitive patterns. Her team has presented findings at EMNLP, CoNLL, ACL, and CoLING. VENI Grant for "Interpretability of Transfer in Multilingual Models" Early Career Partnership by Royal Dutch Academy of Science "Most Interesting Paper" Award at BabyLM Challenge "Best Project Award" by Network Institute She has taught courses like Language as Data and Advanced NLP at University of Göttingen, VU Amsterdam, and TU Darmstadt. Her group collaborates with institutions like Gemeente Amsterdam and NT2 on multilingual text simplification and learner correction.

Annette Riosمشاهده پروفایل

پژوهشگر

• Machine Translation
• Text Simplification
• Multimodal Processing
• +۵ مورد دیگر

Annette Rios is a Researcher at the University of Zurich within the Language, Technology and Accessibility group. Her work focuses on machine translation , text simplification , and sign language translation , particularly for multilingual and indigenous language contexts. Research highlights include contributions to the European EASIER project on sign language translation, the ZurichNLP consortium, and the development of tools for emotion detection and gender bias reduction in NLP systems. She has published extensively in top-tier venues like ACL and WMT, with a focus on multimodal translation and German language processing . Developed emotion_detection GitHub repository for German emotion analysis Contributed to ContraPro and ContraWSD projects on translation evaluation Created datasets for German text simplification and emotion detection Her publications reveal a strong emphasis on machine translation (7/15 recent works), sign language technology (3/15), and text simplification (2/15). While no formal advising is documented in the provided text, she has mentored GitHub contributors to her repositories. Current research directions include improving multimodal translation systems and expanding emotion detection capabilities beyond English.

Lukas Fischerمشاهده پروفایل

پژوهشگر

• Natural Language Processing
• Machine Translation
• Computational Linguistics
• +۴ مورد دیگر

Lukas Fischer is a researcher specializing in Natural Language Processing and Machine Translation, currently affiliated with the Language, Technology and Accessibility project. He holds an M.Sc. in Artificial Intelligence from the University of Edinburgh (2017-2018) and a B.A. in Computational Linguistics from the University of Zurich (2012-2016). His recent roles include lead developer for the Digilinguo online platform since 2025 and contributions to multimodal machine translation projects like IICT and Bullinger Digital. Research Focus: Machine translation for historical languages (Latin, Early New High German) Text simplification and accessibility technologies Multimodal translation systems Data curation for multilingual historical corpora Code-switching detection in early modern texts Publications highlight his work on SwissADT (audio description translation for Swiss languages), LLM-based Latin translation, and medieval text processing. His projects span both computational linguistics and practical accessibility applications.

• Computational Linguistics
• Natural Language Processing
• Natural Language Generation
• +۵ مورد دیگر

Leo Wanner is a prominent Professor at Universitat Pompeu Fabra's Department of Information and Communication Technologies, specializing in Natural Language Processing. With a research career spanning over three decades, he has made significant contributions to computational linguistics, particularly in natural language generation, collocations, and hate speech detection. He has served as editor for multiple editions of the International Conference on Computational Linguistics (COLING) including the 2025 edition. Wanner's research interests encompass a wide range of topics in computational linguistics, with recent work focusing on hate speech detection, multilingual processing, and the capabilities of large language models. His work bridges theoretical linguistics with practical applications, addressing challenges in lexical semantics, syntax, and discourse analysis. Notably, he has pioneered research in collocation processing and has contributed to the development of frameworks for analyzing thematic progression in texts. His publication record demonstrates consistent productivity with significant contributions across multiple subfields. Recent work shows a strong focus on contemporary challenges in NLP, particularly hate speech detection and the capabilities of large language models. His research often takes a multilingual perspective, addressing challenges across different language families including Romance and Slavic languages. Wanner has led significant research projects including the development of FORGe, a multilingual deep sentence generator based on the Meaning-Text Theory, which achieved top performance in the WebNLG challenge. His work on multilingual surface realization has established important benchmarks in the field through shared tasks that have engaged researchers worldwide. As an academic leader, Wanner has mentored numerous researchers and contributed to building research infrastructure through corpus development and annotation schema design. His work on collocation resources, thematic progression analysis, and hate speech detection frameworks has provided valuable resources for the broader NLP community.

• Machine Translation
• Natural Language Processing
• Computational Linguistics
• +۷ مورد دیگر

Pierrette Bouillon is affiliated with the University of Geneva as a researcher, focusing on machine translation, accessible communication, and language technology applications in healthcare. Her work bridges computational linguistics, speech processing, and inclusive design. Institution: University of Geneva Research Focus: Medical translation, sign language processing, text/pictograph translation Research Interests : Bouillon specializes in machine translation and computational linguistics , with particular emphasis on: Accessible communication for patients with language barriers Sign language and pictograph translation systems (e.g., BabelDr) Speech-to-speech translation in emergency settings Text simplification for intellectual disabilities Historical French normalization for NLP Multilingual speech recognition and post-editing Article Trends : Her recent publications highlight the integration of large language models with accessibility tools in healthcare, focusing on Swiss French sign language corpora , pictograph sequences , and spontaneous speech simplification . Work spans both NLP and human-computer interaction in medical contexts. Education and Teaching : While specific educational details are omitted, Bouillon contributes to translation pedagogy through tools like COPECO and MT3 , integrating speech technologies into post-editing workflows.

Michael Amslerمشاهده پروفایل

پژوهشگر

• Automated Media Content Analysis
• Political Communication
• Social Media Analysis
• +۳ مورد دیگر

Michael Amsler is a Researcher at the University of Zurich’s Institute of Mass Communication and Media Research, part of the Faculty of Arts. He holds dual roles as a Postdoctoral Scholar in Media Research and a Research Assistant in the Department of Computational Linguistics (Innosuisse Project ReAdvisor). His research focuses on automated media content analysis, political communication, and computational linguistics applications in social media environments. Amsler earned his MA in Mass Communication and Media Research (2012) and completed his PhD in the NCCR Democracy project (2020). Education: MA 2012 (UZH), PhD 2020 (UZH) Affiliations: Institute of Mass Communication, Department of Computational Linguistics, ARGUS der Presse AG (2013-2020) His work bridges computational methods with political communication studies, analyzing media framing of governance, populist strategies, and emotionalized discourse. Key projects include SIFT (media coverage toolkit) and ReAdvisor (innosuisse NLP project). His publications span sentiment analysis frameworks, verb-based polarity classification, and social media’s role in amplifying political anger. Notable contributions include developing Sentiframes (verb-centric German sentiment resources) and exploring how alternative media drive polarized reactions. His research emphasizes automated tools for analyzing governance legitimacy and public accountability through language technologies.

Alessia Battistiمشاهده پروفایل

پژوهشگر

• Sign Language Technology
• Accessibility
• Natural Language Processing
• +۳ مورد دیگر

Alessia Battisti is a Researcher and Ph.D. candidate at the University of Zurich , Faculty of Arts, affiliated with the Language, Technology and Accessibility Group . Her research focuses on sign language technology, accessibility, and natural language processing, particularly in the context of Swiss German Sign Language. She has contributed to projects like SMILE-II (funded by an SNF Sinergia grant) and the Flagship IICT . Battisti is actively involved in academic communities as the student representative on the board of the Special Interest Group on Speech and Language Processing for Assistive Technologies (SIG-SLPAT). Research Interests include: Swiss German Sign Language assessment and learning Automated readability and text simplification Sign language annotation and feedback systems Human motion modeling for sign language analysis Multilingual dataset curation and quality evaluation Recent Publications highlight her work in sign language fluency scales, automated annotation, and German text simplification frameworks. She collaborates on international initiatives like the First WMT Shared Task on Sign Language Translation . Grants include the SNF Sinergia grant supporting the SMILE-II project. Her work intersects computational linguistics , accessibility research , and machine learning to advance sign language and simplified text technologies. Labs/Teams : Language, Technology and Accessibility Group at the University of Zurich; SIG-SLPAT Special Interest Group.

• Marketing Technology
• Artificial Intelligence
• Natural Language Processing
• +۳ مورد دیگر

Dr. Guang Lu is a Lecturer at the Lucerne School of Business, affiliated with the Institute of Communication and Marketing (IKM) and its CC Communication & Marketing Technologies division. He holds a Ph.D. in Energy Science and Engineering from ETH Zurich (2016), an M.Sc. in Mechatronics from Southeast University (2010), and a B.Sc. in Mechanical Design from Southeast University (2007). His work bridges computational mechanics, marketing technologies, and AI-driven solutions for societal challenges. Dr. Lu’s research focuses on AI applications in elder care (e.g., emotion-aware chatbots), NLP for corporate culture analysis, and sustainability in e-commerce. He has pioneered studies on sharing economy dynamics, algorithmic nudging for eco-friendly consumer behavior, and greenwashing detection via ESG report analysis. His technical expertise spans computational fluid dynamics, granular mechanics (e.g., rockfall simulations), and multimodal emotion recognition systems. His career includes roles as a Computational Mechanics Engineer at WSL SLF (2017–2019), Researcher/Teaching Assistant at ETH Zurich (2010–2016), and Engineer at Southeast University’s Robotics Center (2007–2010). He has published over 39 peer-reviewed articles, with recent work emphasizing AI ethics in elder care technology and data-driven marketing strategies. Dr. Lu collaborates with industry partners like GPTW Switzerland AG and has conducted projects on corporate culture assessment, chatbot localization for German-speaking elderly populations, and algorithmic solutions for sustainable consumer choices. His research often integrates interdisciplinary methods, merging natural language processing with engineering systems to address modern business and societal challenges.

• Natural Language Processing
• Computational Linguistics
• Text Generation
• +۳ مورد دیگر

Elizabeth Clark is a researcher at the University of Washington, specializing in Natural Language Processing (NLP) and Computational Linguistics. Her work focuses on improving text generation systems through rigorous evaluation frameworks and datasets. Co-developer of the SEAHORSE dataset for multilingual summarization evaluation Principal investigator in context-aware rewriting and dialect-robust metrics Contributor to GEM benchmark standardization for NLG evaluation Her research explores challenges in: Human evaluation reliability for machine-generated text Counterfactual reasoning in narratives Contextual rewriting to enhance stylistic coherence Clark has published extensively in top conferences like ACL, EMNLP, and NAACL, often collaborating with Noah A. Smith and other NLP experts. Her work highlights critical gaps in automated evaluation metrics and proposes innovative solutions like CtxSimFit and NANO for robust assessment.

• Natural Language Generation
• Computational Linguistics
• Referring Expression Generation
• +۴ مورد دیگر

Kees van Deemter is a Professor in the Department of Computing Science at the University of Aberdeen's School of Natural and Computing Sciences. With a research career spanning over three decades, he has established himself as a leading figure in Natural Language Generation and Computational Linguistics. His work bridges theoretical linguistics with practical NLP applications, with particular focus on referring expression generation, multilingual processing, and evaluation methodologies. Van Deemter's research interests center on Natural Language Generation, with special emphasis on Referring Expression Generation (REG), computational modeling of linguistic phenomena across languages, and the development of robust evaluation frameworks for NLP systems. His work spans theoretical foundations to practical applications, including logic-to-text generation, cross-linguistic studies comparing East Asian and European languages, and addressing challenges in hallucination and reproducibility in NLP. His recent publications demonstrate a consistent focus on improving evaluation methodologies in NLP, with particular attention to task-based assessments rather than purely ratings-based approaches. He has made significant contributions to understanding how linguistic features influence reference production across languages, with extensive work on Chinese and Mandarin processing. His research group has developed several important corpora including QTUNA for quantifier studies and Mtuna for Mandarin referring expressions. Co-authored the influential survey 'Computational Generation of Referring Expressions: A Survey' (2012) Developed the Mtuna corpus for Mandarin referring expressions Contributed foundational work on the incremental algorithm for referring expression generation Pioneered research on vague language generation from a game-theoretic perspective Investigated cross-linguistic differences in reference production between English and East Asian languages Van Deemter has supervised numerous PhD students who have become active researchers in NLP, including Guanyi Chen, Fahime Same, and Albert Gatt. His collaborative work extends across multiple institutions and has significantly shaped current approaches to referring expression generation and evaluation in NLP. His recent work critically examines the limitations of current evaluation practices in NLP and proposes more scientifically grounded assessment frameworks.

• Terminology
• Corpus Linguistics
• Translation Studies
• +۳ مورد دیگر

Aurélie Picton is a researcher at the Department of Multilingual Computer Processing within the Faculty of Translation and Interpreting at the University of Geneva. Her work focuses on terminology, corpus linguistics, and specialized language analysis across diverse domains including medical communication, climate justice, and scientific discourse. Research Interests: Terminological variation, lay-expert communication, diachronic analysis of specialized languages, and tool-based approaches to translation. Key Trends: Recent publications explore the intersection of terminology with patient expertise, climate policy, exobiology, and accessibility for migrants through plain language strategies. Scientific contributions include methodological frameworks for analyzing knowledge-rich contexts in translation, mixed-methods studies on terminological evolution, and pedagogical innovations in terminology education using project-based learning and flipped classrooms.

• Theoretical Computer Science
• Artificial Intelligence
• Open Science
• +۳ مورد دیگر

Dr. Tomas Hruz is a Researcher at the Institute of Theoretical Computer Science at ETH Zurich, Switzerland. His work focuses on advancing open science practices, knowledge graph technologies, and the ethical application of large language models (LLMs). He contributes to initiatives like the Open Research Knowledge Graph (ORKG) and Project Alexandria, aiming to enhance scientific accessibility and reproducibility. His research spans theoretical computer science, AI ethics, and collaborative knowledge systems. Key areas of interest include scholarly communication reform, FAIR data principles, and leveraging AI for systematic literature reviews. He has published extensively on topics such as knowledge graph applications, metadata interoperability, and synthetic data in healthcare research. His contributions address challenges in reproducibility, ethical AI development, and interdisciplinary collaboration. Dr. Hruz is actively involved in the German National Research Data Infrastructure (NFDI), particularly in ontology development and semantic publishing. His recent work explores the potential of LLMs in scientific workflows, including abstract summarization and leaderboard tracking. Collaborations with international teams highlight his commitment to advancing open science through technological innovation.

• Inclusive Communication Technologies
• Translation Technology
• Machine Translation
• +۶ مورد دیگر

Dr. Martin Kappus serves as Head of the Professorship for Accessibility (ad interim) at the ZHAW School of Applied Linguistics in Zurich. His research focuses on inclusive communication technologies, translation ergonomics, and the integration of language technology in academic contexts. He leads projects like 'Inclusive Information and Communication Technologies' and explores machine translation applications for academic texts. Key research interests include optimizing translation tool interfaces, accessibility standards for multilingual communication, and the human factors in translation workflows. His work bridges applied linguistics with technology development, emphasizing user-centered approaches in language industry practices. Recent projects include investigating automatic text simplification evaluation frameworks and comparing subtitling guidelines across Swiss regions. He has presented at international conferences such as EST Congress and HumEval, contributing to both theoretical and practical advancements in accessible communication. Publications span peer-reviewed journals like Revista Tradumàtica and Handbook of the Language Industry , reflecting his contributions to translation studies, technology, and accessibility. His edited volumes address barriers in communication design for educational and digital content.