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Simon PicklView profile

Associate Professor

• Historical Sociolinguistics
• Dialectology
• Corpus Linguistics
• +3 more

Simon Pickl is an Associate Professor in German Studies at the University of Salzburg, with a focus on historical sociolinguistics, dialectology, and corpus linguistics. He has held visiting positions at the University of Cambridge (2017–2019) and serves as a co-editor for the Journal of Historical Sociolinguistics . His research integrates stochastic image analysis and geolinguistic data to model regional language variation. Research Interests: Historical language variation, dialectometry, spoken German analysis, sociolinguistic change, and corpus-based methodologies. His recent work explores the interplay between spatial patterns, occupational complexity, and life events in shaping colloquial German variation. He has developed the GeoLing software for geolinguistic data analysis and leads the MuSt project on regional language structures. Scientific Awards: Feodor-Lynen Fellowship (2017), Johann-Andreas-Schmeller Prize (2013), Hugo-Moser Prize (2019). Academic Roles: Affiliated Lecturer at Cambridge (2018–2020), Postdoctoral Research Associate (2017–2019). Pickl contributes to conferences like the International Conference on Language Variation in Europe (ICLaVE) and maintains the Historical Sociolinguistics Network (HiSoN) website. His 58 publications span dialectology, historical syntax, and sociolinguistic theory.

Jan NiehuesView profile

Professor

• Machine Translation
• Natural Language Processing
• Artificial Intelligence
• +3 more

Jan Niehues is a Professor at the Karlsruhe Institute of Technology (KIT), working at the Institute for Anthropomatics and Robotics (IAR). He leads the "Artificial Intelligence for Language Technologies" research group, focusing on developing practical AI systems for real-time language translation and speech processing applications. His research spans Machine Translation, Natural Language Processing, and Neural Networks, with emphasis on building AI assistants that solve real-world communication problems. Niehues views translation software as a human aid rather than replacement, particularly valuable where professional translators are cost-prohibitive. His work targets everyday usability in scenarios like international conferences through real-time spoken language translation. Niehues and his team develop neural network-based systems trained on large datasets including European Union minutes and TED talks. He stresses that AI model quality directly depends on training data quality, with neural networks learning probabilistic language patterns through weighted neuron connections. His research anticipates increased value in personal communication methods as automated systems become ubiquitous.

Mª Angeles Solano RodriguezView profile

Researcher

• Phraseology
• Paremiology
• Translation Studies
• +7 more

Mª Angeles Solano Rodriguez is a researcher at the University of Murcia's Department of Language and Literature Teaching. Her work focuses on phraseology, paremiology, and translation studies with a strong emphasis on foreign language pedagogy. PhD in French Phraseology Member of the 'Phraseology, Paremiology and Translation' research group Previously part of 'Fonología y Lectura' research team Her research combines phraseological analysis with didactic strategies to enhance language acquisition. Key areas include: Pragmatic phraseological units Metacognitive learning frameworks Task-based language teaching Translation of literary idiomatic expressions Contrastive phraseology between languages Recent publications analyze phraseological patterns in Daniel Pennac's works, pragmatic markers in foreign language classrooms, and integrated phraseology projects for Spanish teaching. Her methodology emphasizes cognitive-emotional intersections in language learning and digital resource utilization for phraseological instruction.

Brenda RappView profile

Research Professor

• Cognitive Neuropsychology
• Attention
• Reading and Writing
• +10 more

Brenda Rapp is a Research Professor at the Krieger School of Arts and Sciences , Johns Hopkins University, affiliated with the Department of Cognitive Science . Her work focuses on cognitive neuropsychology, attention, reading, and writing, particularly in the context of neurological injury and developmental disorders. Education: PhD in Cognitive Science from Johns Hopkins University. Research Interests: Brenda investigates the cognitive processes and neural substrates underlying written and spoken word production and comprehension. She examines how neural injury affects language mechanisms, using cognitive neuropsychology, fMRI, and computational modeling to study recovery and neuroplasticity in post-stroke dysgraphia and primary progressive aphasia. Publications: Brenda's recent work includes studies on transcranial stimulation, neural network reorganization, orthographic learning, and language rehabilitation. Her articles explore topics such as bilingual reading pathways, functional connectivity in aphasia, and the role of expertise in letter perception. Scientific Honors: Elected to the Society of Experimental Psychologists, recognizing her contributions to experimental psychology across cognitive, perceptual, and neuroscientific domains. Advising: She has advised PhD graduates like Kyriaki Neophytou and currently mentors students such as Angela Xu (PhD) and Ata Kolday (MA) in the Cognitive and Brain Sciences Lab.

• Language Register Processing
• Psycholinguistics
• Sentence Comprehension
• +5 more

Dr. Katja Maquate is a Researcher at the Institute for German Language and Linguistics within the Faculty of Arts and Humanities at Humboldt-Universität zu Berlin. She is actively involved in the Collaborative Research Centre (CRC 1412) with a specific focus on project C03: "Real-time register comprehension in adolescent heritage speakers' languages." Her research spans multiple aspects of language processing with particular emphasis on how social context influences linguistic comprehension. Maquate's research interests center around language register processing, examining how formality levels in language interact with syntactic and semantic processing during comprehension. Her work investigates the real-time processing of register congruence effects using eye-tracking methodologies in both written and spoken language comprehension. She explores how contextual formality information rapidly impacts sentence processing, interacts with morphosyntactic knowledge, and influences verb-argument relations. Her research spans multiple methodologies including eye-tracking reading studies, Visual World Paradigm experiments, and self-paced reading tasks to investigate the cognitive mechanisms underlying register processing. Analysis of Maquate's recent publications reveals a consistent focus on the intersection of social context and linguistic processing. Her work demonstrates sophisticated experimental designs that manipulate register congruence alongside traditional linguistic variables like morphosyntactic agreement and verb-argument relations. A notable pattern is her investigation of how context effects unfold over time during sentence processing, with particular interest in whether register effects emerge rapidly or require more processing time compared to traditional linguistic constraints. Her research often compares different presentation modalities (blocked vs. mixed) to understand how comprehenders adapt to shifting social contexts. Maquate actively collaborates with researchers across multiple institutions, frequently working with Pia Knoeferle and other members of the CRC 1412. Her grant-funded research through the Collaborative Research Centre demonstrates significant funding support for her investigations into language register phenomena. While specific grant amounts aren't detailed in the available information, her multiple publications from this research program indicate substantial research support. As part of the CRC 1412 team, Maquate contributes to a larger research infrastructure examining register phenomena across different time periods, languages, modalities, and cultures. Her work represents an important component of this comprehensive investigation into how social context shapes language use and comprehension.

Pushpak BhattacharyyaView profile

Professor

• Natural Language Processing
• Computational Linguistics
• Machine Learning
• +6 more

Pushpak Bhattacharyya is a distinguished Professor in the Department of Computer Science and Engineering at the Indian Institute of Technology (IIT) Bombay. He holds the prestigious title of Abdul Kalam National Fellow and is a Fellow of the National Academy of Engineering (FNAE). His academic leadership extends to roles such as Professor Incharge of the IIT Bombay-Monash Australia Academy and Chairman of the MEITY Committee for Indian Language Standards. Professor Bhattacharyya's research spans multiple domains within computational linguistics and artificial intelligence. His work focuses on Natural Language Processing, Computational Linguistics, Machine Learning, Sarcasm Detection, Sentiment Analysis, Multilingual Processing, and Cognitive NLP. He has made significant contributions to Indian language technology, leading NITI Aayog's initiative on creating an Indian Language NLP stack and Virtual Agents. His recent publications reveal a strong focus on multilingual NLP for Indian languages, bias detection in language models, sarcasm and humblebragging detection, mental health applications of NLP, and code generation. His work bridges theoretical advances with practical applications in education, healthcare, and government services. The research demonstrates increasing integration of cognitive aspects with traditional NLP approaches and a growing emphasis on ethical AI considerations like bias detection and cultural competence. FNAE (Fellow of National Academy of Engineering) Abdul Kalam National Fellow Listed among top 10 Machine Learning Researchers in India Listed among most prolific NLP-ML researchers 2012-17 Professor Bhattacharyya has mentored numerous PhD and Masters students who have gone on to make significant contributions in academia and industry. His research has been supported by various grants from government agencies and industry partners, enabling large-scale projects in Indian language technology and NLP. He has led the development of comprehensive NLP resources for Indian languages and has been instrumental in establishing research collaborations between IIT Bombay and international institutions. He leads a vibrant research group at IIT Bombay focused on Natural Language Processing, with active projects in sarcasm detection, multilingual processing, cognitive NLP, and applications of NLP in healthcare and education. His team has developed several notable systems including those for Indian language translation, sarcasm detection, and mental health analysis through text.

Tianmin ShuView profile

Assistant Professor

• Machine Social Intelligence
• Embodied AI
• Human-Robot Interaction
• +7 more

Tianmin Shu is an Assistant Professor in the Department of Computer Science at Johns Hopkins University's Whiting School of Engineering, with a secondary appointment in the Department of Cognitive Science. He directs the Social Cognitive AI (SCAI) Lab and is a member of the Data Science and AI Institute. Dr. Shu's educational background includes: PhD in Statistics, University of California, Los Angeles (2019) BS in Electronic Engineering, Fudan University (2014) Dr. Shu's research pioneers machine social intelligence to build human-centered AI systems. His work integrates: Embodied AI for physical-world human-robot collaboration Neurosymbolic methods for multimodal social reasoning Computational models of human social cognition Theory of Mind frameworks for mental state inference Continual learning for adaptive social agents Recent publications (2024-2025) reveal three dominant research thrusts: (1) Multimodal Theory of Mind systems like MMToM-QA for mental state reasoning, (2) Embodied assistance frameworks such as GOMA for goal-oriented human-robot alignment, and (3) Human feedback learning methods including pragmatic feature preferences. His work increasingly bridges language models with world models while exploring neural correlates of social cognition through fMRI studies. Dr. Shu's scientific contributions have been recognized with prestigious awards: Cognitive Science Society’s 2017 Computational Modeling Prize 2020 NeurIPS Best Paper Award (Cooperative AI Workshop) 2022 IROS Workshop Excellent Paper Award 2024 ACL Outstanding Paper Award (MMToM-QA) As director of the SCAI Lab, Dr. Shu leads research on socially intelligent systems through open-source platforms including VirtualHome 2 (multi-agent household simulator) and SimWorld (photorealistic interaction simulator). His lab develops computational frameworks that enable machines to perceive social dynamics, infer intentions, and provide context-aware assistance in complex environments.

Eleanor ChodroffView profile

Assistant Professor

• Phonetics–Phonology Interface
• Cross-Talker Phonetic Variation
• Speech Prosody
• +4 more

Eleanor Chodroff is an SNF Assistant Professor in the Department of Computational Linguistics at the University of Zürich . She leads the Phonetics and Cognitive Science Lab (PaCSci Lab) within the broader Phonetics & Speech Sciences Group . Her research spans the phonetics–phonology interface , cross-talker and cross-linguistic phonetic variation , speech prosody , and morphophonology . A central theme involves leveraging large spoken corpora to advance linguistic theory, with applications in speech recognition and phonetic analysis . Former roles include Lecturer in Phonetics and Phonology at the University of York and postdoctoral researcher in the Prosody & Speech Dynamics Lab at Northwestern University . She holds a PhD in Cognitive Science from Johns Hopkins University and a BA in German and Linguistics from New York University . Recent collaborative projects include the CorpusPhon workshop (co-organized with Morgan Sonderegger), computational studies on temporal anticipation in speech , and methodological investigations of speaker heterogeneity in datasets like Common Voice. Her work intersects acoustic phonetics with machine learning frameworks, particularly in low-resource language contexts.

Srikanth MadikeriView profile

Lecturer

• Automatic Speech Recognition
• Speaker Recognition
• Language Recognition
• +3 more

Dr. Srikanth Madikeri is a Lecturer and Senior Researcher at the University of Zurich's Department of Computational Linguistics. He holds a Ph.D. in Computer Science from IIT Madras (2013) and a Bachelor of Engineering from Anna University (2008). Before joining UZH, he spent 11 years at Idiap Research Institute as a Postdoctoral Researcher and Research Associate. His research focuses on low-resource speech technologies, including Automatic Speech Recognition (ASR), Speaker Diarization, Language Recognition, and Spoken Dialog Systems. He specializes in adapting models for challenging domains like air traffic control and criminal investigations. Recent publications demonstrate strong trends in multimodal systems, domain adaptation for ASR, and efficient data selection techniques. His work frequently integrates speech processing with NLP tasks and criminal network analysis. Awards: Best Paper Award in Signal Processing Track (NCC 2011) International Create Challenge 2017 Winner He teaches Speech Technology and Machine Learning for Computational Linguistics at UZH. Professional activities include serving as Area Chair for Interspeech (2021-2022) and developing open-source toolkits like pkwrap for LF-MMI training.

Merel ScholmanView profile

Assistant Professor

• Discourse Analysis
• Psycholinguistics
• Computational Linguistics
• +3 more

Dr. Merel Scholman is an Assistant Professor at Utrecht University within the Department of Languages, Literature and Communication and affiliated with the Institute for Language Sciences . Her research focuses on how people use language to create meaning through discourse relations , investigating cognitive processing of coherence markers in written, spoken, and visual communication. PhD in Language Science and Technology from Saarland University (summa cum laude, 2019) Research Master in Linguistics from Utrecht University (cum laude, 2015) Visiting researcher at Lancaster University and University of Edinburgh Her work combines theoretical psycholinguistics with computational modeling , using quantitative empirical methods like corpus analysis and crowdsourcing experiments. Recent research examines cross-modal discourse signals across Nigerian Pidgin , English , and European languages , while methodological contributions explore annotation reliability and experimental design. Publications demonstrate expertise in discourse markers , coherence relations , and low-resource NLP , with applications to gesture synthesis , spoken language analysis, and educational tools . She received the Veni grant for her project on natural discourse structure signals across modalities. As an educator, she contributes to the Communication and Information Sciences (BA) and Linguistics (RMA) programs, teaching courses like Writing Style as a Choice . Her methodological innovations in crowdsourcing and annotation frameworks have shaped discourse analysis practices in computational linguistics.

• Phonology
• Variationist Linguistics
• Sociolinguistics
• +5 more

Jean-Michel Tarrier is a Lecturer at the University of Toulouse 2 - Jean Jaurès , affiliated with the Cognition, Languages, Ergonomics (CLLE) laboratory's ERSS team. His career spans both teaching and research, with a focus on phonology, variationist linguistics, and sociolinguistics. Co-coordinator of the LVTI Program (Language, City, Work, Identity) since 2013 Active participant in the PFC Program (Phonology of Contemporary French) His research investigates language variation in urban contexts, particularly examining socio-phonological patterns in Toulouse French through fieldwork and corpus analysis. Key interests include phonological leveling, dialect modeling, and interdisciplinary approaches to spoken language study. Publication trends reveal consistent contributions to phonological variation in French, with particular emphasis on Urban-rural dialect contrasts Interview-based data collection Transcription system development Comparative sociophonology Language change mechanisms Identity construction through speech Current affiliations include CLLE Laboratory , where he works with the ERSS team on projects related to language structure and variation.

Celine VaguerView profile

Lecturer

• French Syntax
• Lexical & Grammatical Semantics
• Discourse Analysis
• +4 more

Céline Vaguer is a Lecturer at Université Toulouse - Jean Jaurès, affiliated with the Cognition, Languages, Ergonomics (CLLE) school. Her academic work focuses on French syntax, lexical & grammatical semantics, and discourse analysis. Syntactic Constructions Lexical Semantics Discourse Markers Phraseology Translation Studies Her research explores how linguistic forms interface with meaning, particularly through prepositions, adverbial phrases, and discourse markers. She has extensively analyzed expressions like en même temps and genre in spoken French, revealing their enunciative and argumentative roles. Recent publications (2022-2024) highlight her work on synonymy (vélo/bicyclette), discursive categorization (genre), and syntactic constructions. She serves as an editorial manager for journals like Langages and Langue française , contributing to academic discourse through Varia issues.

Harald BaayenView profile

Professor

• Computational Linguistics
• Psycholinguistics
• Morphological Productivity
• +7 more

Harald Baayen is a Professor at the University of Tübingen within its Faculty of Humanities, Department of Linguistics . His work spans computational linguistics, psycholinguistics, and phonetics, with a focus on discriminative learning models for lexical processing. After studying under Geert Booij in Amsterdam (PhD 1989), he held positions at the Max Planck Institute for Psycholinguistics (1990-1998), Radboud University (Associate Professor via Dutch Science Foundation award), and the University of Alberta (Full Professor 2007-2011). His 2011 Alexander von Humboldt Award and 2025 Honorary Doctorate from Tartu reflect his scholarly impact. Education: PhD in General Linguistics (Amsterdam, 1989) Awards: Alexander von Humboldt (2011), Dutch Science Foundation Career Advancement (1998) Teaching: Courses in Linguistics for Cognitive Science and Statistical Methods since 2011 at Tübingen Research Synthesis Baayen's research bridges computational modeling and empirical phonetics . Notable projects include: Linear Discriminative Learning (2019): A unified framework for morphological processing without morphemes Articulatory Phonetics : Using EMA and ultrasound to study dialect variation and articulation practice effects Statistical Methods : Pioneering generalized additive models and quantile regression in psycholinguistic analysis His 2025 publications explore Mandarin-English semantic differences , Ukrainian grammatical number , and deep learning alternatives to discriminative frameworks. His work consistently challenges traditional morphological theories by integrating discriminative learning with real-world phonetic data .

Mirjam ErnestusView profile

Professor

• Psycholinguistics
• Speech comprehension
• Laboratory phonology
• +5 more

Mirjam Ernestus is a Professor of Psycholinguistics at the Centre for Language Studies within Radboud University's Faculty of Arts. She serves as Chair of the Editorial Board of Radboud University Press and Scientific Director of the Centre for Language Studies since 2017. Her career spans 20+ years in psycholinguistics and phonetics research. Member of Royal Netherlands Academy of Arts and Sciences Recipient of ERC Starting Grant and NWO VICI grant Specializes in speech comprehension and conversational speech Research Focus: Her work integrates psycholinguistics and phonetics to explore auditory word recognition, morphological processing, and cross-linguistic speech phenomena. She develops computational models like DIANA for speech comprehension analysis. Publication Trends: Recent studies examine exemplar-based processing differences between native/non-native speakers, phonetic-morphological interactions, speech rate dynamics, and multimodal language learning approaches. Her work frequently applies machine learning and experimental paradigms. Awards: ERC Starting Grant (2011) NWO VICI grant (2011) KNAW membership (2015) EURYI Award (2006) Leadership: She has directed major research initiatives including the gravitation project Language in Interaction and the Research Unit Spoken Morphology. Her management roles include overseeing 160+ researchers at the Centre for Language Studies.

Gediminas NavickasView profile

Lecturer

• Speech Recognition
• Speech Synthesis
• Signal Processing
• +5 more

Gediminas Navickas is a Lecturer at Vilnius University's Institute of Data Science and Digital Technologies (DMSTI) within the Faculty of Mathematics and Informatics, specializing in the Image and Signal Analysis Group. His work bridges academic research with practical applications in Lithuanian language technologies. His primary research focuses on automatic Lithuanian speech recognition, speech signal processing, speech synthesis methods and algorithms, and speech synthesis quality assessment. Navickas has made significant contributions to developing speech technologies specifically for the Lithuanian language, addressing the challenges of resource scarcity compared to more widely spoken languages. His work demonstrates strong interdisciplinary connections between computer science, linguistics, and cognitive science. Navickas's publication record reveals a consistent trajectory of innovation in speech technology, with recent work emphasizing cognitive approaches to evaluating synthetic speech, particularly examining differences in perception between blind and sighted users. His research has evolved from foundational work on neural network architectures for speech synthesis to comprehensive studies on speech corpus development and accessibility applications. He has been instrumental in major EU-funded projects including the LIEPA series (2013-present), which have developed comprehensive speech recognition and synthesis systems for Lithuanian. These projects have produced practical applications ranging from educational robots to voice-controlled mobile services and assistive technologies for the visually impaired. Member of Lithuanian Computer Society (LIKS) Council Member of IEEE organization Active participant in COST actions including UniDive and Multi3Generation Navickas regularly engages with the public through media appearances on LRT radio and television, where he explains complex speech technology concepts to general audiences. His science communication efforts demonstrate a commitment to making technical research accessible and relevant to Lithuanian society.