جستجوی استاد راهنمای دانشگاهی

Mark Steedmanمشاهده پروفایل

استاد

• Artificial Intelligence
• Computational Cognitive Science
• Natural Language Processing
• +۹ مورد دیگر

Mark Steedman is a Professor in the School of Informatics at the University of Edinburgh, where he conducts research in Artificial Intelligence, Computational Cognitive and Social Science, and Natural Language and Speech Processing. He is affiliated with the Institute for Language, Cognition and Computation (ILCC), the Centre for Speech Technology Research (CSTR), and the Human Communications Research Center (HCRC). He also holds an adjunct professorship in Computer and Information Science at the University of Pennsylvania. His research focuses on Combinatory Categorial Grammar (CCG) , computational linguistics , prosody and intonation , temporal semantics , gesture in communication , and computational music analysis . He has authored foundational books including Surface Structure and Interpretation , The Syntactic Process , and Taking Scope . The recent publications reflect a strong trend toward integrating formal grammatical frameworks like CCG with modern neural and distributional models, particularly in semantic parsing, entailment reasoning, and cognitive modeling. His work bridges symbolic and statistical approaches in NLP, often focusing on robust, wide-coverage parsing and semantic interpretation. Best Paper Award at AACL/IJCNLP 2023 for 'Smoothing Entailment Graphs with Language Models' Best Paper Award at ACL 2023 for 'Extrinsic Evaluation of Machine Translation Metrics' Influential Paper Award 2017 from IFAAMAS for 'Animated Conversation' Mark Steedman has supervised numerous PhD students and collaborated widely across institutions. He leads research in formal grammar applications to cognitive modeling, dialogue, and multimodal communication. His lab contributes to CCG software and semantic parsing tools, and he continues to be actively involved in advancing the integration of symbolic and neural AI.

• Artificial Intelligence
• Natural Language Processing
• Human-AI Interaction
• +۴ مورد دیگر

Khiet P. Truong is an Associate Professor affiliated with the Digital Society Institute and the Human Media Interaction group. Their research focuses on the intersection of artificial intelligence, robotics, and human-computer interaction, with particular emphasis on speech emotion recognition, conversational agents for children, and multimodal interaction analysis. Recent work includes exploring how robots can restore trust through apologies, benchmarking Dutch automatic speech recognition systems, and developing child-friendly interfaces for cultural heritage archives. Truong has also investigated physiological signals like laughter and stress markers in speech across diverse contexts. Scientific Awards : Best Functional Design Award (2019) Research Trends : Analysis of speech patterns, emotion recognition, robot-human dialogue, and multimodal behavioral cues dominate their recent publications. Key subfields include Dutch language processing, laughter classification, trust indicators in child-robot interactions, and healthcare applications of speech technology. Academic Activities : Chair of the 26th ACM International Conference on Multimodal Interaction (2024) Examiner roles for PhD defenses and research evaluations (2024–2023) Contributions to workshops on emotion representation and social signal processing

John W. Du Boisمشاهده پروفایل

استاد

• Discourse and Grammar
• Sociocultural Linguistics
• Referential Pragmatics
• +۶ مورد دیگر

John W. Du Bois is a Professor in the Department of Linguistics at the University of California, Santa Barbara (UCSB), within the College of Letters and Science. His work focuses on the interplay between discourse, grammar, and sociocultural contexts. Specializing in dialogic syntax, he explores how linguistic structures emerge from interactional dynamics, particularly in conversational coherence and stance-taking mechanisms. His research integrates corpus linguistics, computational methods, and ethnographic approaches to study languages like Mayan and Kazakh. Key research areas include: Discourse and grammar integration Dialogic resonance and affective alignment Corpus design and analysis Ritual language and cognitive models Mayan linguistic systems Recent studies emphasize computational tools like Rezonator for dialogue coherence visualization and remote corpus development methodologies. His work bridges theoretical linguistics with applied research in language documentation and education. Du Bois has contributed to foundational texts on discourse transcription standards and maintains active involvement in the Santa Barbara Corpus of Spoken American English project. His publications span over four decades, reflecting sustained engagement with linguistic complexity across multiple levels—from micro-level syntactic interactions to macro-level sociocultural frameworks. Current projects investigate dialogic syntax in autism and the evolutionary niche of language within social interaction.

Susan E. Brennanمشاهده پروفایل

استاد

• Cognitive Science
• Psycholinguistics
• Human-Computer Interaction
• +۳ مورد دیگر

Susan E. Brennan is a Distinguished Professor in the Department of Psychology at Stony Brook University, with joint appointments in Computer Science and an affiliation in Linguistics. She holds a Ph.D. from Stanford University (1990) and has been a faculty member since 1990. Her research focuses on the cognitive science of language use, particularly interactive spoken dialogue, eye-tracking as a communication tool, and human-AI interaction. She is also involved in projects exploring how technology interfaces with communication, including speech and language systems. Her academic roles include serving as Director of Graduate Studies and Associate Chair in Psychology. Brennan’s work has been continuously supported by the NSF, totaling over $3.5M in grants. Notable awards include the Chancellor’s Award for Excellence in Scholarship (2003) and the Dean’s Award for Excellence in Service (2012). Research interests span the psychology of language, multimodal communication, and the neural basis of dialogue. She has published extensively on topics like common ground in conversation, coordination signals, and the role of gaze in collaborative tasks. Her lab integrates behavioral experiments, eye-tracking, and computational models to study real-world communication dynamics.

Megumi Kameyamaمشاهده پروفایل

پژوهشگر

• Logical Theory of Discourse Semantics
• Computational Discourse Model
• Grammar-Pragmatics Interface
• +۳ مورد دیگر

Megumi Kameyama was a Senior Research Scientist at the Artificial Intelligence Center (AIC) of SRI International. Her research focused on discourse semantics, computational models for information extraction, and mismatch resolution in machine translation. She contributed to projects like FASTUS, MIMI, and GEMINI, addressing challenges in spoken dialogue summarization and cross-lingual translation. Key projects included the NSF-funded Mismatch Resolution in Machine Translation (1996-1999), where she co-led efforts to develop logical and statistical approaches for resolving linguistic discrepancies between languages. Her work emphasized real-time systems and robust context modeling, particularly for Japanese-English translation and dialogue analysis. Dr. Kameyama maintained active involvement in software development, including MIMI for spoken dialogue extraction and FASTUS for text analysis. Her publications explored dialogue structure, context dependency, and system robustness in natural language processing. She passed away on January 23, 1999.

• Human–robot interaction
• Spoken language processing
• Image and audio processing
• +۳ مورد دیگر

Tetsunori Kobayashi is a Professor in the School of Fundamental Science and Engineering at Waseda University, Japan, where he has served since 1997. He is renowned for pioneering research in human–robot interaction, spoken language processing, and multimodal conversational systems, leading to over 230 refereed papers and an h-index of 35 (Google Scholar). Education: 1980 B.Eng. in Electrical Engineering, Waseda University 1982 M.Eng. and 1985 Dr.Eng. from Graduate School of Science and Engineering, Waseda University Research Interests: His work spans intelligent robotics , perceptual information processing , pattern recognition , image and audio processing , and conversational AI . He develops algorithms for real-time dialogue systems, multi-party conversation facilitation robots, and non-autoregressive speech recognition leveraging CTC and pre-trained language models. Recent Publication Trends: Since 2020 his group has advanced non-autoregressive end-to-end ASR (Mask-CTC, Intermpl, BECTRA), noise-robust attention , multi-look-ahead conversational ASR , and neural speaker diarization . They integrate BERT-style pre-training with CTC losses to accelerate inference while maintaining accuracy. Parallel work explores vision-and-language topics such as scene-graph generation, video semantic indexing, and personalized summarization for spoken news delivery. Scientific Awards: IEICE Fellow 2023 – for multi-modal multi-party conversation research IPSJ Fellow 2016 – for pioneering robot conversation studies JST Award for Academic Start-ups 2024 Best Paper Awards from IEICE, IEEE BTAS, ACM SIGGRAPH VRCAI, and several IPSJ workshop prizes Advising & Grants: He has mentored dozens of PhD and Master’s students who now lead in academia and industry. Major funded projects include JST CREST on conversational robotics, NEDO and JST-support for AI-based speech interfaces, and industry collaborations with NHK, OKI, and NEC. Labs & Teams: Kobayashi heads the Perceptual Computing Laboratory at Waseda, conducting interdisciplinary research with domestic and international partners such as MIT, ATR, and NHK Science & Technology Labs.

• Computational Linguistics
• Natural Language Processing
• Sentiment Analysis
• +۲ مورد دیگر

Alexandri Christina is a Lecturer at the Faculty of German Language and Literature at the National and Kapodistrian University of Athens. Her research focuses on computational linguistics and natural language processing, with applications in sentiment analysis, machine translation, and human-computer interaction systems. Her work examines how implicit meaning and unspoken context in spoken interactions can be computationally modeled, particularly in political, journalistic, and technical domains. Recent projects explore the integration of generative AI with traditional linguistic approaches to enhance human-machine communication across specialized fields including medical, engineering, and maintenance contexts. Research trends show consistent focus on multilingual processing challenges, with innovations in knowledge graph construction for bias detection and cross-domain adaptation techniques. Publications demonstrate strong interdisciplinary connections between linguistics, computer science, and social sciences.

Natalie Pardeمشاهده پروفایل

دانشیار

• Natural Language Processing
• Interactive Systems
• Multimodality
• +۲ مورد دیگر

Natalie Parde is an Associate Professor and Co-Director of Undergraduate Studies in the Department of Computer Science at the University of Illinois Chicago (UIC). She co-directs the UIC Natural Language Processing Laboratory and holds affiliations with the AI.Health4All Center for Health Equity using Machine Learning and Artificial Intelligence as well as the UIC Honors College. Her research focuses on natural language processing with applications in healthcare, multimodal communication, and creative language analysis. Ph.D., Computer Science and Engineering, University of North Texas M.S., Computer Science, University of North Texas B.S., Computer Science, University of North Texas Parde's research spans three primary strands: NLP interfaces for educational technology, health-oriented summarization, and multimodal communication systems. Recent publications highlight advancements in dementia detection through spoken language analysis, empathy prediction in conversational systems, and multimodal emotion classification. Her work frequently addresses healthcare applications of NLP, including mental health assessment and medical self-disclosure detection. Scientific awards include the Dr. Hermann Zemlicka Award for Most Visionary Paper at Gmunden Retreat on NeuroIS 2024. She has advised numerous doctoral students, including Gyeongeun Lee working on empathy detection via figurative language, Shahla Farzana researching dementia detection methods, and Mohammad Arvan investigating reproducibility in NLP evaluations. The UIC NLP Lab under her direction focuses on developing NLP systems that positively impact society through educational technology interfaces and healthcare applications.

Shawn Loewenمشاهده پروفایل

استاد

• Instructed Second Language Acquisition
• Second Language Interaction
• Quantitative Research Methodology
• +۲ مورد دیگر

Shawn Loewen serves as Professor and Associate Chair for Graduate Studies in Michigan State University's Department of Linguistics, Languages, and Cultures within the College of Arts & Letters. He directs the Second Language Studies (SLS) program and teaches second language acquisition and quantitative research methods courses. His educational background includes an MA from Temple University and PhD from the University of Auckland. Loewen's research centers on instructed second language acquisition (ISLA) , second language interaction , and quantitative methodology , with particular focus on bridging SLA research and classroom practice. He investigates how teachers engage with research and how mobile-assisted language learning impacts pedagogy. His recent publications reveal strong trends in mobile language learning effectiveness (Duolingo/Babbel studies), research-practice interface challenges, and methodological rigor in SLA. He examines nonverbal feedback mechanisms, synchronous communication platforms, and pronunciation acquisition through both empirical and theoretical lenses. His scientific recognition includes: Fulbright award for Polish University collaboration (2021) As SLS program director, Loewen fostered the graduate community that earned MSU's 2018 Outstanding Graduate Program Community Award. Since 2018, he has served as associate editor of The Modern Language Journal while securing research grants including the Fulbright. Though specific advisees aren't listed, his leadership roles indicate active graduate mentorship across second language studies. Loewen maintains active involvement in the SLS program and collaborates on language learning technology projects, frequently addressing media inquiries about language app efficacy as seen in Kiplinger's 2024 coverage.

• Language Acquisition
• Cognitive Science
• Computational Modeling
• +۷ مورد دیگر

Emmanuel Dupoux is a Professor at École des Hautes Études en Sciences Sociales (EHESS), affiliated with the School of Advanced Studies in Social Sciences and the Laboratory of Cognitive Science and Psycholinguistics (LSCP). His work bridges cognitive science, computational linguistics, and machine learning to study infant language acquisition and social cognition. Co-creator and director of EHESS Cognitive Science Master program Former LSCP laboratory director (1998-2009) Current research focuses on textless speech modeling and ecological audio analysis Research areas include: Modeling early language acquisition mechanisms using Bayesian models and HMM Investigating phonological 'deafness' and critical age plasticity Studying social cognition development through infant-toddler experiments His technical contributions span speech processing toolkits like Shennong, emergent communication frameworks (STOP dataset), and innovative approaches to self-supervised speech modeling. Recent publications demonstrate breakthroughs in: Topography-inspired CNN designs for better memory efficiency Prosody-aware generative spoken language models (pGSLM) Textless emotion conversion systems He actively explores how machine learning can reverse-engineer infant language learning processes from ecological audio data, with applications in neurodegenerative disease diagnostics. Key collaborations include: INRIA's Cognitive Machine Learning (CoML) team Facebook AI Research (FAIR) partnerships VoxPopuli multilingual speech corpus development

M. Theuneمشاهده پروفایل

استادیار

• Natural Language Processing
• Human-Computer Interaction
• Conversational Agents
• +۴ مورد دیگر

M. Theune is an Assistant Professor at the Human Media Interaction (EEMCS-CS-HMI) group within the Faculty of Electrical Engineering, Mathematics and Computer Science at the University of Twente. Specializing in Natural Language Processing and Human-Computer Interaction, their research focuses on embodied conversational agents, interactive digital storytelling, and educational technology applications. Expertise: Conversational Agents, Virtual Humans, Natural Language Generation, Serious Games, Human-Media Interaction Key Projects: Research on lexical alignment in AI interactions, bias mitigation strategies, self-disclosure mechanisms in voicebots, and immersive learning technologies Research Trends Theune's recent publications (2023-2025) demonstrate consistent focus on lexical alignment in human-agent conversations, with applications in large language models (GPT-3.5/GPT-4), confirmation bias mitigation , and trust dynamics . Their work bridges dialogue system design with psychological modeling , particularly in educational contexts and multi-user interaction scenarios. Scientific Contributions: Netherlands Organisation for Scientific Research (NWO) grant (2003) for language/gesture generation in embodied agents Co-developer of systems like BLISS (spoken dialogue dataset), Data2Game (integrated demonstrator), and ExpReal (narrative authoring tools)

Daniel Sonntagمشاهده پروفایل

استاد

• Intelligent User Interfaces
• Natural Language Processing
• Information Retrieval
• +۷ مورد دیگر

Prof. Dr.-Ing. Daniel Sonntag serves as Scientific Director of Interactive Machine Learning at the German Research Center for Artificial Intelligence (DFKI) and holds an Endowed Chair of Applied Artificial Intelligence at University of Oldenburg. He leads multiple significant research initiatives including No-IDLE (Interactive Deep Learning Enterprise), MASTER (Mixed reality ecosystem for teaching robotics), Ophthalmo-AI (intelligent eye care diagnostics), pAItient (AI applications in medicine), and XAINES (explainable AI with narratives). His research spans intelligent user interfaces, natural language processing, information retrieval, dialogue systems, common-sense modeling, and explainable machine learning methods for cognitive computing. His work particularly focuses on multimodal-multisensor interfaces for medical and health systems and Industry 4.0 applications. His research has had industrial impact, with SmartWeb's multimodal interaction design forming the technical infrastructure for Apple's Siri. His recent publications demonstrate strong trends in medical AI applications, particularly in eye tracking, radiology report generation with enhanced interpretability, and interactive federated learning frameworks. His work consistently bridges theoretical AI advances with practical medical and industrial applications. German High Tech Champion Award (2011) As a principal investigator, Sonntag leads national and European projects funded by the Federal Ministry of Education and Research, Federal Ministry for Economic Affairs and Energy, Federal Ministry of Health, and Horizon Europe. He has supervised numerous researchers including Michael Barz, Jan Zacharias, and Alexander Prange across multiple projects. His research group has successfully transitioned technologies to industry, with former researchers joining companies like Apple, Wacom, and Semvox. Sonntag's laboratory work centers on the Interactive Machine Learning department at DFKI, with strong connections to medical institutions and industry partners. His team develops cognitive assistance systems, mixed reality applications for smart factories, and AI-based diagnostic support tools, particularly in ophthalmology and radiology.

• Computational Linguistics
• Human-Computer Interaction
• Natural Language Processing
• +۵ مورد دیگر

Alexandra Christina is affiliated with the Department of German Language and Literature at the National and Kapodistrian University of Athens. Her work bridges computational linguistics, human-computer interaction (HCI), and political/journalistic text analysis. She specializes in natural language processing (NLP), sentiment analysis, terminology management, and multilingual applications. Her research focuses on extracting implicit information from spoken and written texts, with applications in medical chatbots, aircraft maintenance communication, and political discourse analysis. Notable projects include the 'Athena' medical chatbot, Gricean maxim modeling in NLP, and HCI design for international conferences. Key Areas: Generative AI, ethical AI frameworks, cross-lingual dialogue systems, and cognitive bias analysis in ancient/modern texts. Publications: Over 100 peer-reviewed articles since 2007, including works on terminology databases, HCI conference proceedings, and sentiment analysis platforms. Her recent work emphasizes socially responsible AI, integrating NLP with ethical guidelines, and leveraging crowd-sourced data for unspoken sentiment detection. She collaborates on multilingual terminology projects like TERMONLINE and CNCTST database initiatives.

Souvick Ghoshمشاهده پروفایل

استادیار

• Conversational Search Systems
• Database and Other Retrieval Systems
• Human Information Behavior
• +۱۰ مورد دیگر

Souvick Ghosh is a Tenure-Track Assistant Professor at the School of Information, San Jose State University. His research focuses on conversational search systems, human-computer interaction, and information retrieval, integrating machine learning and natural language processing to enhance interactive information-seeking environments. Ph.D. : Communication, Information, and Media Studies, Rutgers University (2020) M.S. : Computer Science and Engineering, Jadavpur University (2016) B.S. : Computer Science and Engineering, Jadavpur University (2011) His research interests include conversational search systems, database and retrieval systems, human information behavior, human-computer interaction, information retrieval theory and practice, information systems and technologies, information visualization, and research methods. He applies machine learning, natural language processing, and deep neural networks to develop intelligent functionalities in voice-based and interactive environments. His recent publications span topics such as conversational agents, question quality in social Q&A, citation sentiment, and learning-oriented search. These works appear in top venues like HICSS, ASIS&T, SIGIR, and CHIIR, reflecting a consistent focus on improving user-system dialogues, modeling search behavior, and designing human-centered conversational systems. Outstanding Graduating Student Award, Rutgers University (2020) Ghosh has taught graduate and undergraduate courses in data science, programming, and information technology at both SJSU and Rutgers. He leads the ICANN Lab, where he mentors students and conducts ongoing research in conversational AI and information systems. His work emphasizes technology for social good, with applications in education, accessibility, and equitable information access.

Michael Rushforthمشاهده پروفایل

استاد آموزشی

• Linguistics
• Language Teaching
• Computational Linguistics
• +۴ مورد دیگر

Michael Rushforth serves as Assistant Dean for Experiential Learning Initiatives and Professor of Instruction in the Department of Modern Languages and Literatures at the University of Texas at San Antonio's College of Liberal and Fine Arts, where he bridges academic leadership with innovative language education practices. His research spans computational linguistics, virtual reality applications in language pedagogy, dialogue systems for tactical questioning, and accessibility solutions for visually impaired learners. He integrates artificial intelligence with speech technologies to develop immersive language learning environments, with particular focus on Spanish fluency assessment and cross-cultural communication frameworks. His work addresses critical gaps in accessible linguistics education and equitable technology implementation. Recent publications reveal a trajectory from foundational dialogue system research toward AI-driven language assessment tools, demonstrating consistent innovation in merging theoretical linguistics with practical educational technology. His 2024 dataset for Spanish fluency prediction exemplifies this evolution, building upon earlier work in virtual human interactions and tactical questioning systems developed since 2001. Rushforth secured a $74,750 grant for an Intelligent Virtual Reality System for Language Learning (2020-2022) and maintains active conference engagement, presenting at Linguistics Society of America meetings on accessibility, pandemic-era online teaching adaptations, and virtual reality applications across national and international venues including Washington DC, San Francisco, and Salt Lake City.