جست‌وجوی استاد و پژوهشگر

• Artificial Intelligence
• Human-Computer Interaction
• Brain-Computer Interfaces
• +۵ مورد دیگر

Dr. Thomas Do is a Senior Lecturer at the School of Computer Science, University of Technology Sydney (UTS), where he also serves as Co-Director of the Human-centric AI (HAI) Centre since March 2023. His academic appointments at UTS include Senior Lecturer (November 2023-present), Research Fellow (November 2021-October 2023), and Research Associate (October 2020-October 2021). He is a member of the Faculty of Engineering and Information Technology, the Australian Artificial Intelligence Institute (AAII), and the School of Computer Science at UTS. Dr. Do's educational background includes: PhD in Computer Science from the University of Technology Sydney (2020) Master's degree in Human-Computer Interaction and Robotics from the Korea Institute of Science and Technology (2016) Dr. Do's research spans the intersection of artificial intelligence, neuroscience, and human-computer interaction. His primary focus is on Brain-Computer Interfaces (BCIs), where he investigates how to integrate BCI technology into everyday applications. He explores the convergence of AI, data science, neural engineering, and human-computer interaction to unlock the full potential of BCIs. His current projects include Human-centric AI technologies (funded by GrapheneX), Brain-Robot Interfaces (funded by Australian Defence), and Human-AI teaming (funded by ARC DP). His work often involves EEG analysis, spatial navigation studies, and object recognition systems. Dr. Do's recent publications demonstrate a strong focus on advancing Brain-Computer Interface technology through innovative approaches to signal processing, multimodal integration, and practical applications. His work spans from fundamental neuroscience research on brain connectivity patterns to applied AI systems for real-world problems in healthcare, transportation, and security. A notable trend in his research is the integration of explainable AI methods with neuroscience to create more transparent and trustworthy BCI systems. Dr. Do is actively involved in teaching and supervision at UTS, where he has taught courses including Data System, AI/Analytics Capstone Project, Technology Research Methods, and Interactive Media. His current research is supported by an ARC Discovery Project grant titled "Mind-reading AI to translate silent speech into words" (2025-2027). Dr. Do maintains active collaborations with institutions worldwide, having previously worked with the Technical University of Berlin, Germany, the University of California San Diego, USA, and the US Army Research Lab. His research has practical applications in medical, defense, and consumer technology sectors.

Dani Byrdمشاهده پروفایل

استاد

• Linguistics
• Speech Science
• Phonetics
• +۶ مورد دیگر

Dani Byrd is a Professor of Linguistics at the University of Southern California's Dornsife College of Letters, Arts and Sciences. She has held significant administrative leadership roles including Interim Dean, Executive Vice Dean, and multiple Vice Dean positions focusing on research advancement, faculty affairs, and institutional matters. Her interdisciplinary research bridges linguistics, engineering, and neuroscience to investigate human speech production and articulatory coordination. Byrd earned her PhD in Linguistics from UCLA in 1994 with a dissertation on 'Articulatory Timing in English Consonant Sequences.' She received simultaneous MA and BA degrees from Yale University in 1990, graduating magna cum laude with Distinction in Linguistics. Following her PhD, she completed post-doctoral training at Haskins Laboratories in New Haven, Connecticut. Her research specializes in speech production and articulatory coordination, employing cutting-edge magnetometer and real-time MRI technologies to track vocal tract movements during speech. Byrd's work investigates language production from a dynamical systems perspective, examining how linguistic structures relate to temporal speech realization. She combines theoretical linguistics with experimental speech science to understand the cognitive representation of language through physical production. Byrd's recent publications demonstrate a strong interdisciplinary trajectory, integrating linguistics, neuroscience, and artificial intelligence. Her work increasingly focuses on mental health applications of speech analysis, using AI to detect depression and suicidal ideation from speech and eye movements. She continues advancing vocal tract imaging techniques while expanding into speech foundation models that characterize speaker traits and dialect variations across languages. USC Dornsife Dean's Award for Distinguished Service (2012) Fellow of the Acoustical Society of America (2008) R. Bruce Lindsay Award for scholars under 35 NSF Graduate Fellow (1990-1992) UCLA Graduate Woman of the Year Award (1994) Professor Byrd has chaired or served on numerous PhD thesis committees across Linguistics, Electrical Engineering, and Psychology departments at USC. Her research has been continuously funded for three decades by the National Science Foundation and NIH's National Institute on Deafness and Other Communication Disorders. Current major grants include NSF funding for structured variability in vocal tract articulation dynamics and an IARPA contract for spoken human signal anonymization, totaling over $5 million in active funding. Byrd's research takes place in the Dynamic Imaging Science Center at the USC Michelson Center for Convergent Bioscience. She leads the USC SPAN (Speech Production and Articulation kNowledge) Research Group, which combines real-time MR imaging, linguistic experimentation, and machine learning to advance understanding of spoken language. Her team includes engineers, linguists, and neuroscientists working collaboratively on speech production research.

Cong Zhangمشاهده پروفایل

مدرس

• Speech Prosody
• Intonation
• Lexical Tone
• +۸ مورد دیگر

Dr. Cong Zhang is a Lecturer in Phonetics and Phonology at the School of Education, Communication and Language Sciences, Newcastle University, where he also serves as the Academic Lead for Student Employability and Enterprise. Previously, he held positions as a Postdoctoral Research Associate on the ERC project SPRINT at University of Kent (2019-2020) and Radboud University (2020-2022), and worked as a TTS linguist at Rokid Inc. in Beijing. Dr. Zhang's educational background includes: DPhil in General Linguistics and Comparative Philology from University of Oxford (2018), supervised by Professor Aditi Lahiri M.A. with Distinction in Linguistics & Language Acquisition from Newcastle University (2012) B.A. in Translation and Interpreting from Beijing Foreign Studies University (2011) His research primarily focuses on speech prosody, examining intonation, lexical tone, and rhythm across languages. He employs diverse methodologies spanning Phonetics and Phonology (particularly Laboratory Phonology), Psycholinguistics, Computational Linguistics, and Language Acquisition. His work often investigates tonal languages, particularly Mandarin varieties, exploring how sentence-level prosody interacts with word-level prosody. He also maintains research interests in translation and interpreting studies. His recent publications demonstrate a strong emphasis on methodological rigor in phonetic research, with multiple papers comparing recording methods and analytical approaches. He has made significant contributions to understanding citation tone production across languages, prosody in aphasia, and the application of gamification in linguistic data collection. His work bridges theoretical linguistics with practical applications in speech technology and clinical settings, reflecting an interdisciplinary approach that spans computational methods, experimental phonetics, and clinical linguistics. Dr. Zhang's scientific achievements include: Second Prize of Newcastle University's Open Research Awards (2024) Funding from ESRC for Festival of Social Sciences event 'Wey aye, man - Think you know a North-East accent when you hear one?' (2024) Dr. Zhang has been actively involved in knowledge exchange, with his Festival of Social Science event reported by BBC, Mirror, and Chronicle. He has collaborated extensively with researchers across multiple institutions on projects related to speech prosody, including the ERC-funded SPRINT project. His work on remote data collection methods has been particularly timely given the challenges of conducting phonetic research during the pandemic, demonstrating that lossless format phone recordings can be a viable option for certain phonetic studies. His invited talk at HKPU on 'Tonal Tug-of-War: The Interplay of Lexical and Sentence Prosody' further highlights his expertise in this specialized area. Dr. Zhang is affiliated with the LingLab facilities at Newcastle University and contributes to the Children's Speech and Language Clinic. His previous work with the Language and Brain Lab at Oxford and the ERC SPRINT project demonstrate his engagement with interdisciplinary research teams focused on the cognitive and communicative aspects of speech prosody, establishing him as a significant contributor to contemporary phonetic and phonological research.

• 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.

Myungin Leeمشاهده پروفایل

مدرس

• Multimodal Instrument Design
• Human-Computer Interaction (HCI)
• Machine Learning
• +۷ مورد دیگر

Myungin Lee is a Lecturer at the Department of Immersive Media Design, University of Maryland, College Park. His research focuses on designing multimodal instruments and interactive systems that integrate principles from HCI, machine learning, signal processing, and neuroscience. Key projects include NeuResonance (inter-brain synchronization feedback) and FractalBrain (EEG-based VR mindfulness tools). He has contributed to venues like ACM CHI, IEEE VIS, and NIME, and holds patents on reverberation time estimation using neural networks. Research interests span crossmodal correspondence in XR, neuro-interactive systems, and real-time audio-visual simulations. Notable collaborations include the NASA Ocean Project and AlloSphere Research Group . His work has been showcased at Ars Electronica and Getty PST 2024. Education: PhD in Media Arts & Technology (implied by dissertation, 2023) Patents: Multichannel microphone-based reverberation time estimation methods (WO2018111038A1, US10854218B2, etc.).

Sebastián Vallejo Veraمشاهده پروفایل

استادیار

• Political Science
• Gender Studies
• Race and Ethnicity
• +۳ مورد دیگر

Sebastián Vallejo Vera is an Assistant Professor in the Department of Political Science at the University of Western Ontario. He holds a PhD from the University of Maryland, College Park. His research focuses on gendered political institutions, racial identity, and racism in Latin America, with a methodological emphasis on Natural Language Processing (NLP) applied to legislative and social media texts. He is affiliated with the interdisciplinary Laboratory of Computational Social Science (iLCSS) and the Hewlett Packard Enterprise Data Science Institute (University of Houston). Previously, he served as a Post-Doctoral Fellow at the University of Houston and as an Assistant Professor at Tecnológico de Monterrey, México. His research explores barriers faced by marginalized groups in political institutions and the strategic behavior of political actors. Methodologically, he employs advanced NLP techniques, including transformer models, to analyze legislative speeches, tweets, and other text data. His work bridges computational methods with substantive political questions, particularly in gender and race studies. Vallejo Vera’s recent articles analyze topics such as racist discourse activation on social media, legislative speech patterns, and the impact of electoral systems on representation. His work has been published in journals like The Journal of Politics , Political Research Quarterly , and PloS one . He also contributes to open-source computational tools for text analysis and regularly collaborates on interdisciplinary projects.

• Artificial Intelligence
• Natural Language Processing (NLP)
• Machine Learning
• +۶ مورد دیگر

Dr. Rejwanul Haque is a Lecturer in the Department of Computing at South East Technological University (SETU), Carlow, Ireland. He holds a PhD in Computer Science and Engineering from Dublin City University (DCU), where he was supported by an SFI PhD Fellowship (2008–2011). His career spans industry and academia: he contributed to MT systems at Lingo24 and Applied Language Solutions, developed cloud-based MT solutions like SmartMATE, and led industry-oriented research at ADAPT Centre for Huawei Noah’s Ark. He was a Research Fellow at ADAPT (2019–2021) with Marie Sklodowska-Curie Fellowship funding, and Programme Director for MSc AI at National College of Ireland (2020–2022). His research focuses on AI, NLP, and machine translation challenges, including low-resource translation, ethical MT use, and adaptive systems. He has published 70+ peer-reviewed papers and collaborates with institutions like DCU, Trinity College Dublin, and French universities. He currently supervises two PhD students at SETU and secured funding for SETU’s PhD programme. Education: PhD in Computer Science and Engineering (Dublin City University, 2011) Research Interests: Dr. Haque’s work addresses cutting-edge NLP topics such as interactive machine translation, fairness in AI, domain adaptation, and sustainable MT models. He explores applications in biomedical translation, social media analytics, and question-answering systems. His recent projects include developing adaptive MT systems using large language models and improving low-resource language translation through novel techniques. Grants & Collaborations: He secured €189,924 via a Marie Sklodowska-Curie Fellowship and attracted SETU PhD scholarships (2023–2024). Collaborators include Microsoft Ireland, ADAPT Centre, and researchers from University Saint-Etienne, La Rochhelle University, and TCD. His work on the Citizen’s Assembly for COVID-19 earned the ADAPT Recognition Award (2020). Labs/Teams: Active contributor to the ADAPT Centre’s NLP initiatives and collaborates with DCU’s MT group. Engages in cross-institutional projects with French academic partners to advance multilingual systems and ethical AI practices.

• Technology Enhanced Learning
• User/Student Modeling
• Intelligent User Interfaces
• +۴ مورد دیگر

Dr. Beate Grawemeyer is an Assistant Professor in the CEES School of Science at Coventry University, specializing in computer science and artificial intelligence applied to education. Her work focuses on adaptive learning environments, user modeling, and affective computing to enhance learning experiences, particularly for neurodiverse learners. She holds a Doctorate in Computer Science and Artificial Intelligence from the University of Sussex (2007) and an MSc in Knowledge-Based Systems (1999). Education: Doctorate (2007) and MSc (1999) from University of Sussex Her research interests include technology-enhanced learning, intelligent user interfaces, and the design of systems that adapt to individual learner characteristics. Recent work explores affect-aware feedback in programming education, synthetic data generation for student risk prediction, and the impact of non-technical explanations in AI systems. Her publications span adaptive feedback mechanisms, emotion-aware learning environments, and the cognitive impacts of external representation use. Collaborations focus on interdisciplinary applications of AI in education and neurodiversity-inclusive design.

• Trustworthy Artificial Intelligence
• Cybersecurity
• Natural Language Processing
• +۱ مورد دیگر

K.P. Subbalakshmi is a Professor in the Department of Electrical and Computer Engineering at Stevens Institute of Technology, where she directs research on trustworthy AI, cybersecurity, and NLP applications in mental health. A Fellow of the National Academy of Inventors and Jefferson Science Fellow, she develops interpretable AI systems for healthcare and security domains. Her research bridges fundamental AI principles and practical applications, with recent work on causal synthetic data generation, Alzheimer's detection from speech, suicide prediction from social media, and explainable rumor detection. These projects focus on model transparency and real-world reliability. Awards and Honors: Fellow, National Academy of Inventors (2018) Jefferson Science Fellowship (2016) AFOSR Summer Faculty Fellow (2024, 2025) New Jersey Inventors Hall of Fame Innovator Award (2012) Dr. Subbalakshmi founded the Stevens Institute for Artificial Intelligence and holds leadership roles in IEEE COMSOC's Cognitive Networks committee. She has commercialized technologies through startups Dynamic Spectrum LLC and Jaasuz.

Minh Duc Buiمشاهده پروفایل

پژوهشگر

• Natural Language Processing
• Model Efficiency
• Fairness in NLP
• +۲ مورد دیگر

Minh Duc Bui is a PhD candidate in Natural Language Processing (NLP) at the Johannes Gutenberg University Mainz (Germany), advised by Prof. Dr. Katharina von der Wense. His research focuses on cross-cultural NLP, model efficiency, fairness, and transfer learning. He holds an M.Sc. in Data Science (University of Mannheim) and a B.Sc. in Mathematics in Economics. Current projects include curATime (data-independent acquisition in medicine), Emergent AI , and TOPML (trade-offs in machine learning properties). Past roles include a Data Scientist at Bosch (Stuttgart) and research at the University of Hamburg under Prof. Dr. Anne Lauscher. Key achievements include the Outstanding Paper Award at NAACL 2025 for Multi³Hate , a multimodal hate speech detection system. His work emphasizes cultural sensitivity and global inclusivity in AI applications.

Yang Zhangمشاهده پروفایل

استاد

• auditory neuroscience
• speech perception and production
• developmental psychology
• +۷ مورد دیگر

Yang Zhang is a Full Professor and Director of Undergraduate Studies in the Department of Speech-Language-Hearing Sciences at the University of Minnesota, Twin Cities. He also holds affiliation with the Masonic Institute for the Developing Brain. With over 233 publications and 59,364 reads on ResearchGate, Dr. Zhang has established himself as a leading researcher in auditory neuroscience and speech perception. Dr. Zhang's educational background includes a Ph.D. in Speech and Hearing Sciences from the University of Washington (2002) and an MA in Linguistics (psycholinguistics) from the University of Iowa (1997). His research focuses on brain plasticity across the lifespan, particularly examining neural signature markers for normal and pathological development of speech and language in socio-affective and cultural contexts. He employs an integrative approach combining top-down brain imaging techniques (high-density EEG, MEG, MRI, fMRI) with bottom-up construction through neural coding and computational modeling. Dr. Zhang's research has particularly emphasized speech perception in various populations including children with autism spectrum disorders, cochlear implant users, and second language learners. His lab has conducted extensive work on lexical tone perception, emotional prosody processing, and the neural mechanisms underlying language acquisition. Recent work has explored the application of artificial intelligence in communication sciences and disorders. Dr. Zhang serves as Section Chief Editor for Brain Sciences (MDPI) and Associate Editor for Developmental Science (Wiley), and is on the Editorial Board of the Journal of Speech, Language, and Hearing Research. His research has been recognized with awards including the Developmental Science Early Career Researcher Prize (2010) and the 2023 Brain Imaging Grant Award from the College of Liberal Arts. Developmental Science Early Career Researcher Prize (2010) 2023 Brain Imaging Grant Award from the College of Liberal Arts Dr. Zhang leads the Zhang Lab, which maintains an active research program with numerous ongoing projects examining brain plasticity in speech and language processing across different populations. The lab employs advanced neuroimaging techniques including EEG, MEG, and fMRI to investigate the neural mechanisms underlying speech perception, language acquisition, and emotional processing in both typical and atypical development.

Dominique Vaufreydazمشاهده پروفایل

استاد

• Multimodal Perception
• Affective Computing
• Robotics Interaction
• +۵ مورد دیگر

Professor Dominique Vaufreydaz holds a position in Computer Science at Grenoble Alpes University and leads the Multimodal Perception and Sociable Interaction (M-PSI) team at the LIG laboratory. His academic career includes roles as Associate Professor (2005–2023) and Head of the M-PSI team. He specializes in multimodal perception, affective computing, and sociable human-robot interaction, with projects like ARAS dataset and TokenCut object discovery. Education details are not explicitly provided, but his research spans robotics, autonomous systems, and healthcare technologies. He has published extensively in top-tier conferences (CVPR, ICMI) and journals (ACM Transactions, IEEE TPAMI). Over 30 PhD students have been supervised, with current advisees exploring activity recognition, head motion generation, and emotion analysis. Teaching roles include 300+ hours annually across computer science courses (C++, databases, mobile programming) and numerical literacy for non-specialists. He co-leads the MOSIG Master's GVR specialty and manages transversal courses at the Grenoble Faculty of Economics. His labs, notably M-PSI, focus on smart spaces, ambient assisted living, and ethical teaching analytics. Notable collaborations include EU projects (FAME, CHIL) and industry partnerships like Orange Labs. His work bridges cognitive science and machine learning, with applications in healthcare and urban autonomous systems.

Darlene Barkerمشاهده پروفایل

استادیار

• Emotion Recognition
• Machine Learning
• Deep Learning
• +۵ مورد دیگر

Darlene Barker serves as Assistant Professor and Coordinator of Computer Science Programs in the Department of Computer Science at Rivier University. Her research bridges virtual reality, computer science, and emotion recognition to develop systems enhancing human communication across physical distances, with significant applications in video game development and human-computer interaction. Her academic credentials include: Ph.D. in Computer Science from University of Massachusetts Lowell (Dissertation: "Creation of Thelxinoë: Emotions and Touch in Virtual Reality") M.S. in Computer Science from University of Massachusetts Lowell (Thesis: "An Eulerian Path Approach to Next-Generation DNA Sequencing with Pre-Sorted Reads") B.S. in Computer Science from Rivier University Dr. Barker's research spans Emotion Recognition, Machine Learning, Deep Learning, Speech and Natural Language Processing, Virtual Reality, Entrepreneurship, Computer Graphics, and Video Game Design. She pioneers frameworks like Thelxinoë for multimodal emotion detection using pupillometry, facial analysis, and touch processing within immersive environments. Her work uniquely integrates physiological sensing with machine learning to address real-world communication challenges. Analysis of her 2021-2025 publications reveals a clear trajectory: evolving from foundational VR emotion studies (2021) toward sophisticated multimodal frameworks combining gradient boosting, CNN-LSTM networks, and ethical considerations (2025). Her research consistently bridges academic theory with industry applications, particularly in gaming, while addressing emerging challenges in biometric privacy and model interpretability. Her scientific recognition includes: Second Best Paper Certificate at IEEE International Conference on Advanced Systems and Emergent Technologies (ICASET), 2023 Dr. Barker teaches core computer science courses including Algorithms, Database Management Systems, Deep Learning, Data Mining, and Computer Networks. She actively disseminates research through tutorials at premier conferences (IEEE VR, ISMAR) and leads developing frameworks such as Thelxinoë and Harmonia, which form the foundation of her lab's work on affective computing in virtual environments.

C. Kwang Sungمشاهده پروفایل

دانشیار

• Otolaryngology
• Laryngology
• Voice Disorders
• +۴ مورد دیگر

Dr. C. Kwang Sung is an Associate Professor of Otolaryngology — Head & Neck Surgery at Stanford University and holds a courtesy appointment in the Department of Music. He serves as the Residency Program Director in the Department of Otolaryngology and has administrative roles including Director of the Medical Student Clerkship. His clinical expertise includes voice disorders, laryngology, and airway management, with a focus on professional voice users and surgical techniques like phonomicrosurgery and laryngeal framework surgery. Education & Training: Bachelor's in Chemistry (Harvey Mudd College, 1989) MS in Organic Chemistry (University of Pennsylvania, 1992) MD (SUNY Downstate Medical Center, 2004) General Surgery Internship (Mount Sinai School of Medicine, 2005) Otolaryngology Residency (Mount Sinai School of Medicine, 2009) Laryngology Fellowship (Harvard Medical School/Massachusetts Eye and Ear Infirmary, 2010) Research & Scholarly Interests: Development of office-based laryngeal surgical methods Clinical outcomes in vocal fold pathology and glottic insufficiency Medical education curriculum development AI applications in vocal pathology detection (e.g., deep learning models) Awards & Recognition: Bay Area Top Doctors (2017-2024) Honor Award from American Academy of Otolaryngology (2023) Patient-Centeredness Honoree (Stanford Health Care, 2018-2019) Teaching & Mentorship: Course Director for Otolaryngology Grand Rounds Lecturer on vocal pedagogy in the Department of Music Advisor for medical students and residents Clinical Affiliations: Stanford Voice & Swallowing Center Veteran’s Administration Palo Alto Health Care System

Barbara Solenthalerمشاهده پروفایل

مدرس

• Computer Graphics
• Physics-Based Simulations
• Facial Animation
• +۳ مورد دیگر

Barbara Solenthaler is a Lecturer at the Department of Computer Science, ETH Zurich. Her research focuses on physics-based simulations, facial animation, and machine learning applications in computer graphics.