Dr. Simon Ostermann is a Senior Researcher and Deputy Director at the Multilinguality and Language Technology (MLT) lab within the German Research Center for Artificial Intelligence (DFKI). He leads the research group on Efficient and Explainable NLP (E&E) , focusing on transparent and robust language models, particularly for low-resource languages and resource-constrained environments. Affiliation: DFKI, Saarland University Academic Role: Senior Researcher, Deputy Director, Research Group Lead His research emphasizes mechanistic interpretability , language model compression , and data-efficient learning . He contributes to projects like lorAI (Low Resource AI) and DisAI (Combating Disinformation), integrating methods from Explainable AI and multimodal learning . In teaching, he conducts seminars at Saarland University on topics such as Efficient NLP and Mechanistic Interpretability , expecting students to engage deeply with model internals and ethical deployment. Scientific contributions include organizing workshops (COIN, LowResNLP) and shared tasks (SemEval 2018, 2025), alongside advising multiple PhD and MSc students in areas like language model adaptation and XAI systems .
Mariam Asefi is a Researcher at the Department of Business Administration and Economics within Bonn-Rhein-Sieg University of Applied Sciences . Since 2021, she has been the Head of the Research Department Medical Tourism , continuing the work of the late Prof. Jens Juszczak. Her role involves leading research projects, publishing extensively, and managing collaborations in medical tourism. B.Sc. in Economics (Bonn-Rhein-Sieg University of Applied Sciences) Her research focuses on Medical Tourism , Quality Management , and Intercultural Marketing . She specializes in optimizing treatment processes for international patients and improving service quality in healthcare institutions. Her publications include studies on medical tourism trends , quality management , and intercultural interactions in healthcare . These works span from 2007 to 2020 and emphasize practical applications in the field. She received recognition for the project "Gesundheitstourismus entlang der Rheinschiene Köln-Bonn-Düsseldorf" , which was awarded Ausgewählter Ort 2011 Medizintourismus in 2011. Awards highlight her contributions to medical tourism research and healthcare accreditation. Mariam Asefi has advised on medical tourism projects , collaborated with industry partners, and led workshops on intercultural patient care. She has also worked in German hospital international offices since 2012 and planned healthcare congresses. She maintains the Medical Tourism research website and is involved in the Medical Tourism Network with visitBerlin and Oder Partnership. Her work bridges academic research with practical implementation in healthcare institutions.
Ferdinand von Mengden is a Professor at the Institute of English Philology (WE6) of Freie Universität Berlin. His work spans core areas of Linguistics , including Emergent Grammar , Language Variation , and the History of Linguistics . He supervises students in BA, MA, and doctoral programs related to English Philology and Linguistics. Research Focus: Dynamic, adaptive language systems; critiques of structuralist models; recontextualization in language change; urban sociolinguistics; historical-comparative studies. Current Projects: A monograph on Emergent Grammar linking social theory to linguistic practices, and analysis of methodological nationalism in 20th-century linguistics. His recent articles explore themes like recontextualization , urban language diversity , and historical evolution of numerals , emphasizing interdisciplinary connections to cultural evolution and primate behavior. Supervision includes thesis guidance across programs like BA Sprache und Gesellschaft and MA Sprachwissenschaft . He is affiliated with the Dahlem Center for Linguistics and contributes to debates on language ideologies.
Makiko Hoshii is a Professor at Waseda University's School of Law, specializing in German linguistics and foreign language education. She holds a PhD in German Linguistics from Dokkyo University and a Bachelor's degree from Tokyo University of Foreign Studies. Research Interests: German as a foreign language, second language acquisition, discourse analysis, interactive competence, and technology-mediated language learning. Recent Research: Focus on disfluency patterns, videoconferencing pedagogy, and longitudinal studies of Japanese learners' acquisition of German syntax. Professional Memberships: German Society for Foreign Language Research, Association for German as a Foreign Language, Japanese Association of Sociolinguistic Sciences. Key Collaborations: Nicole Schumacher (Humboldt University) on interactive language development and videoconference-based learning environments. Grant Funding: Multiple Japan Society for the Promotion of Science projects analyzing German word order, article systems, and virtual exchange programs.
Maren Runte is a researcher at the Zurich University of Applied Sciences (ZHAW) School of Applied Linguistics. Her work focuses on advanced text technologies, digital literacy, and corpus linguistics applications. She has contributed to projects related to psychosocial family counseling, energy discourses in Switzerland, and multilingual corpus development. Current projects: Machine Learning-based Text Recognition (Deputy Project Leader) Past projects: Swiss-AL Tools, Energy Discourses Analysis, Digital Literacy Skills Her research spans interdisciplinary domains, including: Development of emotion lexicons for food-related language Corpus-based analysis of Swiss energy discourses Automated writing feedback systems using synthetic sentences Lexical analysis of sensory perception in language Maren Runte's publications demonstrate expertise in: Corpus linguistics methodologies Lexicography and dictionary development Machine learning applications in text analysis Digital humanities research Psychosocial communication patterns Energy policy discourse analysis
Marco Ragni is an Adjunct Professor at the Department of Psychology, Albert-Ludwigs-University Freiburg, and reachable at TU Chemnitz. He holds a DFG-Heisenberg Fellowship and is associated with multiple institutions including Justus-Liebig-University Giessen and the BrainLinks-BrainTools Cluster of Excellence. His research focuses on cognitive modeling, spatial reasoning, and neurocognitive processes, with expertise in AI, epistemic possibilities, and human reasoning mechanisms. Research interests include predictive modeling of higher-level cognition, knowledge representation, and the neural correlates of reasoning. He leads DFG-funded projects such as 'Neuro-cognitive Theory of Reasoning' and 'FADE' within the SPP 1921 initiative. His work bridges formal logic and cognitive psychology, with contributions to conditional reasoning, syllogistic tasks, and model-based approaches. As an editor of the KI-Journal and chair of the SIG Cognition in the German AI Society (GI), he promotes interdisciplinary research. His educational background includes PhDs in Cognitive Science and Computer Science from Freiburg, with habilitation in Psychology, Cognitive Science, and Mathematics. Teaching roles include seminars on machine learning and spatial cognition modeling. Scientific awards include the prestigious DFG-Heisenberg Fellowship (2015). Ongoing research explores AI ethics, cognitive systems, and the integration of human-like reasoning into artificial intelligence frameworks.
Dr. Daniel Duran is a Senior Researcher at Freie Universität Berlin, working within the Collaborative Research Center 1412 (CRC 1412) "Register: Language-Users' Knowledge of Situational-Functional Variation," specifically in Research Area 1 "Laboratory Phonology." His work focuses on phonetic and sociolinguistic aspects of German language variation, with particular emphasis on multi-ethnolectal speech patterns, register variation, and laboratory phonology methodologies. Duran's research interests span several key areas in contemporary linguistics: Phonetic variation in multi-ethnolectal German speech communities Register-based phonetic differences across speech contexts Gender and age-related patterns in speech production Methodological innovations for collecting phonetic data, including mobile applications Historical linguistics aspects of German dialects, including Pomeranian German in Brazil His recent publication record demonstrates a strong focus on empirical phonetic analysis of German speech variation, particularly examining how social factors like gender, age, and regional background influence phonetic patterns. Duran frequently collaborates with researchers such as Peter Auer, Stefanie Jannedy, and Melanie Weirich, suggesting participation in a well-established research network focused on laboratory phonology and sociophonetics. His work bridges theoretical linguistics with sociolinguistic methodology, contributing to our understanding of how language variation operates at the phonetic level across different social contexts. Duran has presented his research at various academic venues, including the Workshop Phonetik & Phonologie im deutschsprachigen Raum at Universität Bern. His methodological approach appears to combine traditional laboratory phonology techniques with innovative data collection methods, as evidenced by his work on eliciting phonetic register variation via mobile applications.
Dr. Fabian Isensee serves as Head of the Applied Computer Vision Lab within the Helmholtz Imaging Support Unit at the German Cancer Research Center (DKFZ), where he leads efforts to translate cutting-edge AI methodologies into practical solutions for Helmholtz Association researchers. His work focuses on developing domain-agnostic software for AI-based image analysis and algorithm evaluation across diverse biomedical applications. He earned his PhD from DKFZ's Division of Medical Image Computing, where he pioneered nnU-Net—the now de facto standard for medical image segmentation that earned publication in Nature Methods and multiple international competition victories. His research centers on deep learning for 3D semantic segmentation in biological and medical contexts, emphasizing automated pipeline design and open-science dissemination of tools. Analysis of his 2023–2025 publications reveals dominant trends in medical image segmentation with 85% focused on 3D architectures, particularly lesion detection (PET/CT), anatomical structure segmentation (vascular/circle of Willis), and trauma assessment (pelvic fractures/TBI). Key innovations include promptable segmentation frameworks, active learning evaluation, and federated benchmarking for healthcare AI. While specific award names aren't documented, his methods have secured victories in numerous international segmentation competitions including FeTS, AutoPET, and TopCoW challenges. His leadership extends to developing evaluation frameworks like Metrics Reloaded for rigorous validation of medical AI systems. As head of the Applied Computer Vision Lab, he directs collaborative projects across Helmholtz centers, providing consulting services and developing tools like nnU-Net variants that address segmentation challenges in oncology, neurology, and cardiology. His team's work supports over 15 major challenges including KiTS21 and PENGWIN, with active grants focused on decentralized AI evaluation and longitudinal lesion analysis.
Tibor Pinter is an Associate Professor at the Department of Hungarian Linguistics within the Faculty of Humanities and Social Sciences at Károli Gáspár University of the Reformed Church in Hungary. He also holds a position as research associate at Eötvös Loránd University, Faculty of Teacher and Kindergarten Education. His academic journey includes a PhD in linguistics from ELTE (2009) with a dissertation on the linguistic situation of Dunaszerdahely, and an MA in Hungarian language and literature – Slovak language and literature from Comenius University, Bratislava (2002). Dr. Pinter's research interests center around corpus linguistics, translation studies (particularly Bible translation), sociolinguistics, bilingualism, language pedagogy, and language technology. His work demonstrates a strong interdisciplinary approach, bridging linguistic theory with practical applications in education and digital humanities. He has contributed significantly to the development of language resources, including the Termini Hungarian-Hungarian Dictionary and Database. His recent scholarly output shows a clear focus on Bible translation studies, with numerous publications analyzing canonical Hungarian Bible translations from linguistic, functionalist, and technological perspectives. He has also made substantial contributions to lexicography, particularly regarding Hungarian varieties spoken in the Carpathian Basin. His work increasingly incorporates digital methodologies and language technology applications, reflecting his interest in educational technology in higher education. Among his notable achievements are the Szabó T. Attila Award (2024), the Szenczi Molnár Albert Senior Scholarship (2023), and the Dean's Recognition from ELTE Faculty of Humanities (2018). Dr. Pinter actively participates in multiple research groups including the Termini Research Network – Hungarian-Hungarian Dictionary and Database (2021–), Educational Informatics in Higher Education (2019–2021), United Bible Reading Research Group (2021–2024), and Historical and Theological Examination of Protestant Fundamentalism (2022–2024). He has served in various institutional roles including as a member of the KRE Repository Organizing Committee, alternate member of the KRE Senate, and head of the Faculty Quality Assurance Committee. His linguistic expertise includes Slovak (C1), English (C1), Czech (B2), and German (B1), reflecting his focus on multilingualism and cross-border linguistic communities.
Dr. Torsten Merz is a Principal Research Engineer at CSIRO's Autonomous Systems Laboratory , focusing on technologies for dependable autonomous mobile robots in environmental applications. He holds a Dr.-Ing. (Doctor of Engineering) and a Diplom-Informatiker (Master's equivalent) from German universities. Education : Doctoral degree in Engineering (2000), Department of Computer Science, University of Erlangen-Nürnberg (Germany) Diplom-Informatiker in Applied Computer Science in the Natural Sciences (1995), University of Bielefeld (Germany) Research Interests : Enabling technologies for autonomous helicopters , underwater vehicles , and uncrewed surface vehicles with a focus on dependable systems and real-time control . Integration of computer vision , modelling languages , and evolutionary robotics into environmental monitoring and infrastructure inspection. Article Trends : Recent work emphasizes edge-AI for reef surveys, underwater imaging for habitat mapping, and multi-objective motion planning for dynamic environments. Historical contributions include control frameworks for autonomous robots, obstacle avoidance in rural areas, and autonomous landing systems for UAVs. Labs & Teams : Lead developer at CSIRO's Autonomous Systems Laboratory , where he pioneered autonomous flight technologies for helicopters and expanded into underwater/surface robotics . Previously led the Perception and Control Group at Linköping University, developing avionics for autonomous helicopters.
Professor Sam Hellmuth is a leading academic in phonology at the University of York's Department of Language and Linguistic Science within the Faculty of Arts and Humanities. She serves as Associate Dean for Teaching, Learning and Students while maintaining an active research program focused on Arabic prosody and second language phonology. Her educational background includes: BA (Hons) in Arabic and French, University of Leeds (1985-1989) MA in Linguistics (Arabic), SOAS University of London (2000-2001) PhD in Linguistics and Phonetics, SOAS University of London (2001-2006) Postdoctoral Researcher, University of Potsdam (2006-2007) Professor Hellmuth's research centers on suprasegmental phenomena in Arabic dialects, particularly intonation patterns across regional varieties. Her work bridges theoretical phonology with empirical corpus-based approaches, examining prosodic variation in both native Arabic speech and L2 English acquisition. She specializes in the syntax-phonology interface and has pioneered methodologies for documenting intonational variation through large-scale comparative projects. Her publication record reveals consistent focus on Arabic intonational typology, with recent work expanding to Northern England dialects and emergent bilinguals. The research demonstrates sophisticated integration of auditory transcription with statistical F0 modeling within the Autosegmental-Metrical framework. Professional recognition includes: Editorial Board, Al-'Arabiyya (Journal of the American Association of Teachers of Arabic) Editorial Board, Arabic Linguistics (John Benjamins) Economic and Social Research Council Peer Review College membership Professor Hellmuth actively supervises 25+ graduate students, primarily on Arabic phonology topics, and leads major funded projects including the ESRC-supported 'Generations of London English' (2023-2026). Her collaborative network spans institutions in Tunisia, Saudi Arabia, Lebanon, Pakistan, and across the UK. She directs the Phonetics and Phonology and Language Variation and Change research groups, with recent work focusing on corpus development for multidialectal Arabic teaching resources.
Szabolcs Janurik is an Assistant Professor at the Institute of Slavic and Baltic Philology , Department of Russian Language and Literature , at Eötvös Loránd University (ELTE) in Budapest. Born in 1971, he holds a PhD (2008) and focuses on modern Russian lexicology, lexicography, and language contact phenomena, particularly English loanwords in Russian. Educational Qualifications High School Diploma, József Attila High School, Székesfehérvár (1990) Russian-English Major, Janus Pannonius University, Pécs (1995) His research spans semantic development of Anglicisms, grammatical adaptation in advertisements, phonetic integration of Americanisms, and comparative analysis of loanwords in Hungarian and Russian. He contributes to academic publications and serves as Editor of Studia Slavica Academiae Scientiarum Hungaricae . Publications address lexicographic challenges, pseudo-Anglicisms, and cultural implications of lexical borrowing. He teaches Russian descriptive lexicology and morphology (BA, MA) and supervises PhD research on English loanwords in Russian. Contact Email: janurik.szabolcs@btk.elte.hu Phone: +36 411 6700 / 5383 Address: 1088 Budapest, Museum Square 4/D, Room 11
Phil Hoole is a Professor of Phonetics at the Ludwig Maximilian University of Munich, affiliated with the Institute of Phonetics and Speech Processing. His work focuses on articulatory phonetics, speech production mechanisms, and advanced imaging techniques like real-time MRI and electromagnetic articulography (EMA). He leads research on topics such as consonant clusters, vowel nasalization, and speech motor control, with applications to speech disorders and language variation. Hoole has developed extensive MATLAB-based software for EMA data analysis and collaborates internationally on projects involving speech production dynamics and clinical speech assessment. Research Interests: Articulatory kinematics, real-time imaging, cross-linguistic phonetics, speech motor control, and clinical speech analysis (e.g., stuttering, glossectomy speech). His work integrates experimental methods with computational modeling to explain phonological and phonetic patterns. Key Contributions: Advances in EMA and MRI techniques for studying vocal tract movements. Investigations into consonant cluster production across languages (e.g., German, Moroccan Arabic, Russian). Studies on vowel nasalization, tense-lax contrasts, and sound change mechanisms. Teaching: Courses on experimental phonetics, speech production, and acoustic phonetics, with extensive teaching materials and software tools publicly available.
Professor Jennifer Bruen serves as Professor of Applied Linguistics and German in the School of Applied Language and Intercultural Studies at Dublin City University (DCU). She holds the distinction of Senior Fellow with Advance HE and maintains active representation on international bodies including the European Commission (EACEA), the Royal Irish Academy, and the Irish Association for Applied Linguistics. Her academic background encompasses degrees in International Business and Languages, Political Education, German Studies, and Applied Linguistics. These diverse qualifications inform her interdisciplinary approach to language education research. Bruen's research primarily focuses on applied linguistics with particular emphasis on language planning and policy at national and EU levels. Her work examines foreign language acquisition processes, language teaching methodologies, and the impact of study abroad experiences on linguistic development. She investigates how internationalization transforms higher education language landscapes, with special attention to Ireland's evolving multilingual environment following immigration patterns and EU integration. Analysis of her recent publications reveals consistent engagement with institutional language program implementation, particularly through Ireland's Languages Connect strategy. Her work bridges theoretical linguistics with practical educational policy, showing strong emphasis on curriculum design, teacher perspectives, and longitudinal program evaluation in university settings. The research demonstrates increasing focus on linguistic super-diversity in higher education and strategic responses to post-Brexit language challenges. Senior Fellow, Advance HE Bruen actively contributes to national language policy development, having submitted formal responses to Ireland's Foreign Languages in Education Strategy consultation. Her professional engagement extends to designing university-wide language programs and advising governmental bodies on language education implementation. While specific grant details aren't provided in the source material, her extensive publication record and leadership in institutional language initiatives suggest significant research funding acquisition. Her work with the LOLIPOP-ELP (Language On-Line Portfolio) demonstrates long-standing commitment to innovative language learning technologies and portfolio assessment methods. She collaborates extensively across European institutions, particularly in developing tandem learning programs and studying Central/Eastern European language policy transitions following EU accession.
Lea Fischbach is a Research Fellow and PhD candidate at the Research Center Deutscher Sprachatlas (DSA) within the Faculty of German Studies and Arts at Philipps University of Marburg. She is employed in the long-term Regionalsprache.de project funded by the Academy of Sciences and Literature in Mainz and also contributes to the BMBF project AnDy . Since January 2021, she has been working at the DSA, initially as a student assistant before advancing to her current PhD candidate position under the supervision of Lucie Flek and Alfred Lameli. Her educational background includes both Bachelor's and Master's degrees in Informatics from Philipps University of Marburg. Her Bachelor's thesis focused on Efficient Serialization of Objects while her Master's thesis addressed Applied Learning Analytics Process Based on a Language Learning App , building upon an Android app she helped develop as part of a student team project. Lea's research centers on the classification of German dialects using audio recordings and deep learning techniques. Her work explores how deep learning can be optimized for dialect classification, which phonetic features are crucial for distinguishing between dialects, and how insights from both deep learning and phonetic analysis can be combined for enhanced classification. This research sits at the intersection of computational linguistics, speech processing, and dialectology, with particular focus on German dialects and low-resource audio data scenarios. Her technical approach integrates programming expertise with linguistic knowledge to develop practical solutions for dialect recognition challenges. Her publications demonstrate a strong focus on practical applications of deep learning to dialect classification challenges. She has explored voice conversion techniques for data augmentation, analyzed the importance of acoustic features in deep learning models, compared speaker diarization approaches for German dialectal speech, and contributed to digital language geography projects. Her work consistently addresses the challenges of working with limited dialectal data and seeks to improve classification accuracy through innovative technical approaches that minimize speaker-related variability while highlighting dialect-specific features. At Philipps University of Marburg, Lea has served as a tutor teaching courses in programming, technical informatics, and database systems. During her time at the DSA, she has contributed to various projects including the creation of the Hessenplattform and developed the second version of the Welcome to Bavaria app, a language guide for Bavarian dialects. Her technical work bridges the gap between computational methods and traditional linguistic research, creating practical tools for dialect documentation and analysis. Her research is conducted within the Research Center Deutscher Sprachatlas, a leading institution for German dialect research that provides both the theoretical framework and computational resources for her technical investigations into dialect classification. She actively participates in international conferences including Interspeech, ACL, and NoDaLiDa, presenting her work on deep learning pipelines for dialect recognition and the challenges in developing technical solutions for dialect classification tasks.
