جستجوی استاد راهنمای دانشگاهی

Naomi Feldmanمشاهده پروفایل

استاد

• Computational Linguistics
• Cognitive Science
• Machine Learning
• +۵ مورد دیگر

Naomi Feldman is a Professor at the University of Maryland with dual affiliations in the Department of Linguistics and the University of Maryland Institute for Advanced Computer Studies (UMIACS) . She is also affiliated with the Department of Computer Science , the Program in Neuroscience and Cognitive Science , and the Computational Linguistics and Information Processing (CLIP) Lab . Her research focuses on computational psycholinguistics , applying methods from statistics, machine learning, and automatic speech recognition to model cognitive processes underlying speech perception, phonetic learning, and language acquisition . Key areas include understanding how humans learn language structure in complex environments and developing computational strategies to assist language learners and clinicians. Research combines infant phonetic learning with neural network modeling Investigates cross-linguistic speech recognition and selective attention mechanisms Explores language discrimination , developmental language disorders , and computational models of aphasia Her recent publications (2022-2025) cover topics such as reward-based language learning, rhythm analysis in speech, self-supervised speech representations, and argument role sensitivity in language models. These works have received recognition like the Computational Modeling Prize in Perception & Action and Best Paper Award Honorable Mention . Naomi actively advises students across three graduate programs: Linguistics , Neuroscience and Cognitive Science (NACS) , and Computer Science . Her research team includes postdocs, PhD candidates, and undergraduate collaborators. She has received grants including an NIH Pilot Grant to assist children with specific language impairment. She is a core member of the university's interdisciplinary Language Science community and participates in projects crossing multiple departments. Her lab maintains open-source code repositories for research reproducibility.

• First Language Acquisition
• Morphosyntax
• Dynamics of Youth

Jacqueline van Kampen is an Affiliated Researcher at the Institute for Language Sciences , Utrecht University. A leading expert in First Language Acquisition and Morphosyntax , her work focuses on the Dynamics of Youth research theme. She has extensively studied Dutch syntax acquisition, verb clusters, pronoun systems, and discourse-related phenomena.

• Linguistics
• Language and Education
• Grammar Education
• +۶ مورد دیگر

Dr. Jimmy van Rijt is an Associate Professor at Utrecht University’s Department of Languages, Literature and Communication, specializing in Language and Education. He bridges linguistic theory with practical pedagogy, focusing on grammar instruction, teacher education, and enhancing student understanding through metaconcepts. His work spans secondary and higher education, with administrative roles in programs like Alfa4All and Masterlanguage. Research Interests: Van Rijt explores how grammatical understanding impacts reading comprehension, pragmatic interventions in writing, and reflective thinking in language classrooms. His studies integrate cognitive development and curriculum design, particularly in Dutch education. Publications: His 15 most recent articles (2024–2025) address grammar pedagogy, linguistic reasoning, blended learning, and pragmatic education, reflecting a blend of theoretical and applied research in linguistics and education. Editorial Roles: He serves as editor for L1-Educational Studies in Language and Literature (unpaid) and contributes to the Professional Didactic Manual (unpaid) and Skilled with Professional Content (paid). He co-coordinates the ARLE Special Interest Group in Educational Linguistics. Professional Networks: Van Rijt collaborates with institutions like Tilburg University and Fontys Hogescholen, and contributes to national projects such as DoY (Dynamics of Youth). His work influences teacher training curricula and policy in Dutch language education.

Anqi Liuمشاهده پروفایل

استادیار

• Machine Learning
• Artificial Intelligence
• Distributionally Robust Learning
• +۵ مورد دیگر

Anqi Liu (Angie) is an Assistant Professor in the Department of Computer Science at the Whiting School of Engineering, Johns Hopkins University. She is affiliated with the Data Science and AI Institute, Mathematical Institute for Data Science (MINDS), and Institute for Assured Autonomy (IAA). Her research focuses on developing principled machine learning algorithms for reliable, trustworthy, and human-compatible AI systems in high-stakes applications. PhD in Computer Science from University of Illinois Chicago Postdoctoral Research at Caltech's Department of Computing and Mathematical Sciences Her work emphasizes robustness to changing data environments, uncertainty quantification, and human-AI interaction. Key methodologies include distributionally robust learning, active learning, safe exploration, fair machine learning, and conformal prediction. Applications span healthcare (NIA/NIH-funded), robotics, and computational social science. Amazon Research Award Johns Hopkins + Amazon Initiative for AI Faculty Research Johns Hopkins Discovery Award Institute for Assured Autonomy Challenge Grant She advises PhD candidates in AI safety and fairness, with students co-advised by faculty in Human-Robot Interaction and Computational Linguistics. Collaborations include Center for Language and Speech Processing (CLSP) and Laboratory for Computational Sensing and Robotics (LCSR).

• Aphasia
• Semantic and Cognitive Assessment
• Apraxia of Speech
• +۳ مورد دیگر

Dr. Lucy Dyson is a Senior University Teacher and Disability Liaison Officer in the Department of Human Communication Sciences at the School of Allied Health Professions, Nursing and Midwifery, University of Sheffield. A registered Speech and Language Therapist with the Royal College of Speech and Language Therapists and Health and Care Professions Council, she maintains active clinical practice while advancing academic training. Her educational foundation includes a BMedSci degree followed by a PhD completed in 2017, funded by The Stroke Association's Junior Research Training Fellowship. Her doctoral work investigated semantic processing assessment in aphasia and cognitive-performance relationships in semantic testing. Research centers on acquired communication disorders with emphasis on post-stroke aphasia, apraxia of speech, and stammering. She pioneers computer-based therapeutic interventions while examining cognitive-semantic interfaces and psychosocial dimensions of communication impairments. Her clinical-academic integration ensures practical relevance in rehabilitation methodologies. Publication trends reveal consistent innovation in therapeutic technology for speech disorders, particularly self-administered computer systems for apraxia and aphasia. Her work bridges neurolinguistics, cognitive neuroscience, and clinical rehabilitation across high-impact journals including Stroke and Aphasiology, establishing evidence-based frameworks for speech therapy. Scientific recognition includes: Junior Research Training Fellowship from The Stroke Association As Disability Liaison Officer and clinical placement coordinator, she mentors future speech and language therapists while securing research funding through collaborations with NHS trusts and academic partners. Her Stroke Association-funded projects with Dr. Ruth Herbert and Professor Rosemary Varley demonstrate sustained grant acquisition in neurorehabilitation. She leads the Rotherham Stroke Rehabilitation Team within Rotherham NHS Foundation Trust, delivering continuous post-stroke care through six months of recovery. Her dual academic-clinical role integrates university research with frontline therapy for neurological conditions and stammering, maintaining direct patient contact that informs teaching and innovation.

• Linguistics
• Translation Studies
• Japanology
• +۴ مورد دیگر

Veronica Samu serves as an Assistant Professor at the Department of Japanology within the Institute of East Asia at the Faculty of Humanities and Social Sciences, Károli Gáspár Reformed University in Budapest, Hungary. Specializing in linguistics and translation studies with particular expertise in Japanese onomatopoeia, she maintains regular reception hours on Tuesdays from 12:00-13:00 (currently conducted online by prior arrangement). MA in Japanology (2011) from Károli Gáspár Reformed University PhD in Linguistics (defense scheduled for 2024) from University of Pécs Dissertation: "A sound-schema-based analysis of Japanese and Hungarian onomatopoeias in a contrastive approach – with special regard to the semantic domains mapped by sound schemes" Dr. Samu's research centers on Japanese onomatopoeia, investigating its morphosemantic structures, cognitive foundations, and pedagogical applications. Her work explores how sound schemas map semantic domains across Japanese and Hungarian languages, revealing cross-linguistic parallels. She extends this research to translation studies, particularly regarding culture-specific words between Japanese and Hungarian, and develops innovative approaches to teaching Japanese onomatopoeia through artistic methods and visual aids. Her scholarship bridges theoretical linguistics with practical language instruction, focusing on how onomatopoeic elements enhance language acquisition. Analysis of Dr. Samu's publications from 2012-2022 reveals a clear scholarly trajectory from theoretical linguistic analysis toward practical pedagogical applications. Her early work focused on translation strategies for Japanese phraseologisms and onomatopoeia, while her more recent publications (2021-2022) explore the artistic dimensions of onomatopoeic expressions across media—from children's literature to audiovisual arts. This evolution demonstrates her commitment to applying linguistic theory to enhance Japanese language teaching methodologies in Hungarian educational contexts, particularly through multimodal approaches that leverage artistic expression. Dr. Samu has participated in significant professional development opportunities, including Japanese language programs at the Japan Foundation in 2015 and 2017, which have informed her cross-cultural research and teaching practices. Her linguistic expertise spans Japanese (advanced), English (intermediate), and Serbian (advanced), supporting her comparative research between Japanese and Hungarian languages. She has organized academic events such as the "Translation, not distortion" translators' workshop in 2016 and has contributed to the scholarly community through book reviews and conference organization. Her research demonstrates consistent engagement with both theoretical linguistic frameworks and practical language teaching applications, particularly in the specialized domain of onomatopoeia across Japanese and Hungarian languages. This dual focus positions her work at the intersection of cognitive linguistics, translation studies, and language pedagogy, contributing to both academic discourse and practical educational methodologies in Japanology.

Vladimir Mladenovićمشاهده پروفایل

استاد

• Symbolic computation and processing
• Artificial intelligence and machine learning
• Deep learning and neural networks
• +۷ مورد دیگر

Prof. Dr. Vladimir Mladenović is a Full Professor at the Department of Information Technologies , Faculty of Technical Sciences in Čačak , University of Kragujevac , Serbia. A 1975 native of Paraćin, he earned his Dipl. Ing. from the Faculty of Electronic Engineering, University of Niš (2000), followed by an M.Sc. (2005) and Ph.D. in Technical Sciences (2009) from the University of Kragujevac. His career spans industry (IT Manager, Serbian Glass Factory, 2001–2004), secondary education (teacher, 2004–2009), and academia (Professor of Vocational Studies, 2009–2013) before joining the University of Kragujevac. Research Focus: Symbolic software & tools, higher integration in IT systems Signal & multimedia processing, computer vision & AI/ML 5G/IoT architectures, edge computing, data protection Modern communication systems, web & network technologies He directs the Digital Innovation Lab at his faculty and has authored over 100 peer-reviewed publications in leading journals and conferences, with a strong emphasis on cross-layer modeling, deep learning, and IoT applications. He also co-holds 18 Serbian utility patents covering smart IoT systems ranging from greenhouse monitoring to smartwatch data collection, fire detection, and pedestrian safety. Honors & Professional Standing: Licensed Technology-Transfer Engineer – WIPO & Intellectual Property Office of Serbia (2012) Member, Union of Engineers and Technicians of Serbia Teaching Portfolio: Undergraduate: Modern Software Architectures, Multimedia Systems, Data Protection Master: Modern Communication Systems, Web Programming Doctoral: Modern Network Technologies, Applied Computer Vision

• Second language acquisition
• Phonology
• Pronunciation teaching
• +۸ مورد دیگر

Cecilie Slinning Knudsen is a PhD student and research fellow at the Department of Teacher Education at NTNU (Norwegian University of Science and Technology) from 2023 to 2027. She is currently on leave from her position as a senior lecturer in Norwegian didactics. Her academic work focuses on language education, particularly in the areas of reading and writing instruction, second language acquisition, and phonology. Dr. Knudsen holds a master's degree in linguistics from NTNU and a bachelor's degree in languages with English and Nordic languages from Volda University College. She has also studied Norwegian as a second language at NTNU. Her educational background has provided a strong foundation for her research in language education and second language acquisition. Her primary research interests include language education, the first reading and writing lesson, reading and writing difficulties, second language acquisition, phonology, pronunciation lessons, and linguistic awareness. She is particularly interested in how teachers' knowledge of phonology and the relationship between language phonology and orthography impacts reading and writing instruction quality. As a member of the research groups "Linguistic Diversity in School and Society" and "GrammaKIKK," she contributes to ongoing discussions about language education in multilingual contexts. Dr. Knudsen's publication record shows a consistent focus on pronunciation teaching, phonology in language education, and second language acquisition. Her work bridges theoretical linguistic concepts with practical classroom applications, particularly in Norwegian language teaching. She has authored textbooks, scholarly articles, and professional development materials that help teachers implement effective language instruction strategies. Dr. Knudsen has extensive experience supervising bachelor's and master's theses. Her professional activities include numerous presentations at conferences and professional development workshops for teachers across Norway. She has collaborated on various projects related to Norwegian pronunciation teaching and has served as a consultant for textbook development. She is actively involved in the "Phonology in teacher education" project and has previously worked on "Ten tips on how to support language learning" and the resource bank "uttale.no" for teachers and students working with Norwegian pronunciation.

• Neural Machine Translation
• Multilingual Neural Machine Translation
• Simultaneous Speech Translation
• +۴ مورد دیگر

Dominik Macháček is a researcher at the Institute of Formal and Applied Linguistics (ÚFAL) at Charles University's Faculty of Mathematics and Physics in Prague. He successfully defended his PhD thesis titled 'Multi-Source Simultaneous Speech Translation' in June 2024 and is currently active in research while preparing for a post-doctoral fellowship at the University of Edinburgh starting in January 2026. His research focuses on Neural Machine Translation , particularly Simultaneous Speech Translation where translation happens in real-time with minimal latency (typically 2-4 seconds). His work spans Multilingual Neural Machine Translation, Quality Estimation for speech translation systems, and Human-to-Human Cross-Lingual Communication. His current 'Live Credible Translation' project aims to enhance simultaneous speech translation by adding quality estimation modules to improve credibility of real-time translations. Macháček has secured a US patent (12,056,457 B2) in August 2024 for a 'Computer-implemented method of real time speech translation and a computer system for carrying out the method'. His research has been presented at major conferences including ACL and IWSLT, particularly through his work on the SimulStreaming system which enables large foundation models like Whisper to operate in simultaneous mode. His publication record shows a consistent focus on real-time translation challenges, with recent work examining robustness to transcription errors, correlation between automatic metrics and human ratings, and continuous rating methodologies for human evaluation. His research trajectory demonstrates progression from theoretical foundations to practical applications with significant industry relevance. Macháček actively supervises Bachelor's and Master's theses and teaches the NPFL140 Large Language Models course. He is involved in multiple research projects including CEDMO 2.0, InCroMin, Sign LLM, NEUREM3, and ELITR. His future work will focus on advancing the state of the art in simultaneous speech translation through his 'Live Credible Translation' project at the University of Edinburgh.

• Computer Science
• Artificial Intelligence
• Machine Learning
• +۹ مورد دیگر

Prof. Dr. Hayri Sever is a full-time faculty member at Çankaya University, Department of Computer Engineering, since 2018. He previously held professorship roles at Hacettepe University (1997-2018), University of Massachusetts Amherst (2000-2002), and Başkent University (2003-2007). His academic journey includes a PhD in Computer Science from the University of Louisiana at Lafayette (1995), a Master's from the University of Maine (1991), and a BSc in Computer Engineering from Hacettepe University (1987). Education: PhD (1995), Computer Science, University of Louisiana at Lafayette MS (1991), Computer Science, University of Maine BSc (1987), Computer Engineering, Hacettepe University Prof. Sever's research spans Artificial Intelligence, Data Mining, Natural Language Processing, Cybersecurity, and Machine Learning . His recent work focuses on applications in violence detection in videos, sentiment analysis, blockchain security, medical decision support systems, and Turkish language processing. He has supervised over 40 graduate students in topics ranging from deep learning to blockchain and IoT security. His 15 most recent publications (2019-2024) highlight expertise in deep learning for video analysis , blockchain reputation systems , 3D CNN applications , and sentiment analysis in Turkish/Arabic . Collaborations include institutions like Hacettepe University, University of Massachusetts, and international projects funded by TÜBİTAK, UNESCO, and the UN. He has led projects such as "KGYS: Smart Support Software Development" and "DiCoMa: Disaster Control Management" , with roles as researcher, coordinator, and advisor. Professional memberships include IEEE (2005-), ACM (2002-), and Tübitak (2005-).

Molly Babelمشاهده پروفایل

استاد

• Speech Perception
• Speech Processing
• Speech Production
• +۴ مورد دیگر

Dr. Molly Babel is a Professor of Linguistics at the University of British Columbia, where she directs the Speech In Context Lab (SpeeCon). Her research examines speech perception, processing, and production within the broader context of spoken language use, including social and performative elements such as gender identity and accent variation. Her work spans sociolinguistics, phonetics, and psycholinguistics with core interests in bilingual speech (particularly Cantonese-English), phonetic variation, voice evaluation, and perceptual learning. She investigates how social context, syntactic factors, language environment, and talker variability influence speech processing, often focusing on gender identity and crosslinguistic phenomena in early bilinguals. Analysis of her recent publications (2023-2025) reveals dominant trends in bilingual voice learning, Cantonese-English phonetic mergers, perceptual adaptation to pronunciation variation, and critical examinations of essentialist language ideologies. Her research integrates acoustic analysis, perception experiments, and computational modeling to explore speech intelligibility, voice recall, and cognitive representation of spoken language. The Speech in Context Lab, which she leads, studies spoken communication through a broad lens of context—including social, linguistic, and environmental factors—to unravel how language is cognitively represented. The lab's work emphasizes practical applications in speech technology, language education, and understanding social biases in voice perception, using the acorn metaphor to represent speech as a dense information package requiring careful analysis.

Cai Zhenguangمشاهده پروفایل

استاد

• Psycholinguistics
• Cognitive Psychology of Language
• Computational Linguistics
• +۳ مورد دیگر

Prof. Cai Zhenguang is a Professor in the Department of Linguistics and Modern Languages at The Chinese University of Hong Kong (CUHK), where he leads the Language Processing Lab affiliated with the Brain and Mind Institute. His research integrates behavioral, neuroscientific, and computational approaches to investigate language processing mechanisms. His educational background includes a PhD in Psychology from the University of Edinburgh. Prior to joining CUHK, he served as a lecturer at the University of East Anglia and held an ESRC Future Research Leader fellowship at University College London. Prof. Cai's research centers on psycholinguistics and cognitive neuroscience of language, with specific focus on language comprehension, production, and learning mechanisms. His lab investigates how interlocutors influence language processing, Chinese handwriting literacy including character amnesia, and whether large language models exhibit human-like language behaviors. Additional interests include psychophysics of magnitude perception where physical dimensions interact statistically. Recent publications (2024-2025) reveal strong trends in neural correlates of speaker-contextualized comprehension, computational modeling of language adaptation, and AI-human language comparisons - particularly in Chinese language phenomena. Key methodological approaches combine ERP/fNIRS neuroimaging with Bayesian modeling and deep learning techniques. Scientific recognition includes: ESRC Future Research Leader fellowship He has successfully advised multiple PhD students including Zebo Xu, Hanlin Wu, and Xufeng Duan, along with MA students like Tianyi and Yufeng Wu. His research is supported by significant grants: two General Research Fund projects as Principal Investigator (on character amnesia and interlocutor modeling), an Academic Equipment Grant for TMS-EEG systems, and a teaching grant for virtual behavioral research methodologies. The Language Processing Lab maintains active collaborations across disciplines, having organized major conferences including AMLaP Asia and CogSci Hong Kong Meetup, while recruiting researchers with expertise in fMRI, Bayesian modeling, and machine learning for ongoing projects.

Anne-Michelle Tessierمشاهده پروفایل

دانشیار

• Phonology
• Linguistics
• Constraint-based Grammars
• +۶ مورد دیگر

Anne-Michelle Tessier is an Associate Professor at the University of British Columbia (UBC) within the Faculty of Arts, Department of Linguistics. As Director of the UBC Child Phonology Lab, she investigates theoretical phonology and language acquisition through constraint-based grammars like Optimality Theory (OT), Harmonic Grammar, and Harmonic Serialism. Her interdisciplinary research bridges phonology with cognitive science, speech technology, and biomedical applications. PhD in Linguistics, UMass Amherst (2006) Former Assistant/Associate Professor, University of Alberta (2006-2016) Lecturer in Linguistics/Psychology, University of Michigan (2016-2018) Adjunct Professor, Simon Fraser University (2016-2019) Her research focuses on phonological acquisition , constraint-based learning algorithms , and cross-linguistic studies . She explores topics such as: U-shaped development in child phonology Second language production/perception in childhood Prosodic processing in cochlear implant users Morpho-phonological domain interactions French liaison acquisition mechanisms Swearword phonological satisfaction Key publications include her textbook Phonological Acquisition and work on error-driven learning models. She previously served as Associate Editor for Glossa and Lingua journals. Current projects examine English onset clusters, French liaison simulations, and L1/L2 phonological modeling.

Fernanda Ferreiraمشاهده پروفایل

استاد

• Psycholinguistics
• Cognitive Psychology
• Sentence Processing
• +۴ مورد دیگر

Fernanda Ferreira is a Professor in the Department of Psychology at the University of California, Davis, and Principal Investigator of the Ferreira Lab. She also serves as Editor-in-Chief of the journal Glossa Psycholinguistics . Ph.D., Psychology, University of Massachusetts, Amherst (1988) M.A., Linguistics, University of Massachusetts, Amherst (1986) M.S., Psychology, University of Massachusetts, Amherst (1985) B.A., Psychology, University of Manitoba, Canada (1982) Professor Ferreira's research spans psycholinguistics , focusing on how formal linguistic theories inform language processing mechanisms. Her work integrates behavioral and neural measures , including eye-tracking (fixations, saccades, pupil diameter) and ERPs, to explore real-time language comprehension and production, prosody, disfluency, and individual differences. Her recent publications analyze prosody in human-AI interaction , working memory in bilingualism , ERP studies on disfluency , visual attention in language production , and cross-linguistic syntactic processing . Key themes include cognitive load, syntactic ambiguity, and the interplay between language and other cognitive systems. Scientific Honors and Awards: 1996 American Psychological Association Distinguished Scientific Award for Early Career Contribution to Psychology Fellow, American Association for the Advancement of Science Fellow, Cognitive Science Society Fellow, Royal Society of Edinburgh (FRSE) Fellow, Association for Psychological Science (APS) She teaches cognitive psychology , psycholinguistics , language production/comprehension , and prosody and disfluency at UC Davis. The Ferreira Lab investigates how language processing interacts with memory, vision, and action, with a focus on syntactic theory and experimental methods.

• Human Factors Psychology
• Human-Machine Interaction
• Trust in Automation
• +۷ مورد دیگر

Dr. Qiyuan Zhang is a Lecturer in Human Factors at Cardiff University's School of Psychology , specializing in human-machine systems with emphasis on human-robot interaction , trust in automation , and human-AI collaboration in safety-critical contexts including transportation, emergency services, and cybersecurity. His research integrates Cognitive Psychology and Social Psychology theories to address real-world challenges. PhD in Cognitive Psychology from Durham University Focus on human-automation interdependence , auditory communication , and cognitive workload effects Key grants: £800k ESRC-JST (Rule of Law in AI Age), £5.6M Innovate UK (Flourish CAV Project), and £75k Airbus (XAI Research) Email: ZhangQ47@cardiff.ac.uk His work explores anthropomorphism in autonomous vehicles , noise impact on cognition , and human error in digital security , with methodological approaches spanning simulations, AR integration, and experimental paradigms.