جست‌وجوی استاد و پژوهشگر

Min-Joo Kimمشاهده پروفایل

استاد

• Theoretical Syntax
• Semantics
• Syntax-Semantics Interface
• +۶ مورد دیگر

Min-Joo Kim is a Professor in the Department of English at Texas Tech University's College of Arts & Sciences, with additional affiliations to the Linguistics Program and Philosophy department. She holds a Ph.D. from the University of Massachusetts Amherst (2004) and specializes in theoretical syntax, semantics, and their interface. Her secondary research interests include language acquisition, pragmatics, and grammaticalization. Kim's research investigates linguistic phenomena including Noun Modification, E-type Anaphora, Existential Sentences, Free Choice, Implicature, Aspect, and Evidentiality. Her work employs formal linguistic frameworks to analyze Korean and English data, frequently exploring cross-linguistic patterns and cognitive interfaces. Her publications demonstrate a consistent focus on syntax-semantics-pragmatics interfaces, with recent work examining anaphoric systems, copular constructions, and temporal-aspectual phenomena. The research consistently integrates formal linguistic theory with empirical analysis of Korean and cross-linguistic data. Awards and Honors: TTU's 2019 Integrated Scholar 2021 President's Faculty Book Award Outstanding Faculty Research Award (Inaugural Recipient) National Humanities Center Summer Residency Fellowship C. L. Baker Award nominee (Linguistic Society of America, 2022) As Director of Linguistics at TTU for over 10 years, Kim established the linguistics program's foundation. She has served as Associate Editor for Glossa: a journal of general linguistics and maintains extensive disciplinary service through editorial and conference activities.

Omair Shafiqمشاهده پروفایل

دانشیار

• Natural Language Processing
• Machine Learning
• Deep Learning
• +۴ مورد دیگر

Omair Shafiq is an Associate Professor at the School of Computer Science, Carleton University. His research focuses on advanced topics in natural language processing (NLP), machine learning, and their applications in knowledge graphs, blockchain, and network security. He leads projects that integrate large language models (LLMs) with structured data to enhance information retrieval and decision-making systems. His work spans areas like explainable AI, adversarial robustness, and real-time traffic prediction. Shafiq is affiliated with Herzberg Laboratories and contributes to interdisciplinary research, including smart contracts, encrypted traffic classification, and IoT security. Education details are not explicitly listed in the provided text. His research interests emphasize practical solutions for challenges in AI ethics, data privacy (e.g., GDPR compliance), and scalable analytics for big data applications. He has developed frameworks like ECSGen/iZen for NLP tasks and CARD-B for encrypted traffic classification. His recent publications (2022–2025) highlight innovations in ensemble learning, adversarial attacks defense, and blockchain-based solutions for secure transactions. Shafiq’s work often bridges theory and practice, addressing real-world problems such as cybersecurity in vehicular networks, stock market prediction using deep learning, and user behavior analysis on social platforms. His contributions include tools like RevDet for event detection in news feeds and HybLoc for indoor localization. Though no specific awards are mentioned, his prolific publication record reflects sustained academic impact.

Andrei Antonenkoمشاهده پروفایل

مدرس

• Syntax
• Semantics
• Binding Theory
• +۸ مورد دیگر

Andrei Antonenko is a Lecturer in the Department of Linguistics at Stony Brook University, where he earned his Ph.D. in 2012. His research focuses on syntax, semantics, and their interface, particularly in areas like Binding Theory, Phase Theory, and the syntax-morphology interface of Caucasian languages such as Archi and Russian. He has expertise in teaching large general education courses like LIN 200: Language in the USA and advanced syntax courses. His work bridges formal linguistic theory with empirical analysis of Slavic and Caucasian languages. Education: Ph.D. in Linguistics, Stony Brook University (2012) Research interests include long-distance phenomena, agreement systems, switch-reference, and word order movement. His studies on Russian imperative inflection, subjunctive clauses, and Archi pronouns highlight his commitment to morphosyntactic analysis. Recent work explores pedagogical innovations in linguistics education, emphasizing asynchronous and learner-centered approaches. Publications span formal syntax, Slavic linguistics, and language contact phenomena. Notable works include analyses of Russian predicate doubling and feature valuation in binding theory. His collaborative research on uncertainty expression in natural language demonstrates interdisciplinary applications of linguistic theory.

Mrigank Rochanمشاهده پروفایل

استادیار

• Computer Vision
• Machine Learning
• Deep Learning
• +۴ مورد دیگر

Dr. Mrigank Rochan is an Assistant Professor in the Department of Computer Science at the University of Saskatchewan. Previously, he served as a Senior Researcher in Huawei Noah's Ark Lab's Autonomous Driving Perception team. He holds a Ph.D. and M.Sc. from the University of Manitoba (2020 and 2016) and a B.Tech. from Amrita University, India (2011). His research focuses on Deep Learning applications in Computer Vision, including video highlight detection, domain adaptation, and autonomous systems perception. Notable awards include the 2020 CIPPRS John Barron Doctoral Dissertation Award and the 2024 Google PaliGemma Academic Program Award. Education Ph.D. in Computer Science, University of Manitoba, Canada (2020) M.Sc. in Computer Science, University of Manitoba, Canada (2016) B.Tech. in Computer Science and Engineering, Amrita Vishwa Vidyapeetham University, India (2011) Research Interests His work emphasizes unsupervised learning techniques, domain adaptation for autonomous systems, and multimodal learning (e.g., audio-visual fusion). Recent projects include improving LiDAR-based 3D object detection and developing adaptive crowd counting models. He explores video summarization methods and cross-modal networks for referring segmentation. Grants & Awards NSERC Discovery Grant (2024) Google PaliGemma Academic Program Award (2024) CIPPRS John Barron Doctoral Dissertation Award (2020) Advisees & Teaching He teaches CMPT 489/828: Deep Learning and CMPT 318: Data Analytics . While no named students are listed, his publications suggest active collaboration with graduate researchers like Zahidul Islam, Sujoy Paul, and Linwei Ye. Labs & Collaborations Prior work at Huawei's Autonomous Driving Perception team informs his current focus on real-world perception challenges. His lab at USask likely addresses interdisciplinary AI applications in vision systems.

Fausto Giunchigliaمشاهده پروفایل

استاد

• Artificial Intelligence
• Computational Models of the Mind
• Knowledge Representation
• +۴ مورد دیگر

Prof. Fausto Giunchiglia is a Professor of Computer Science at the University of Trento and holds prestigious fellowships from EURAI and the Academia Europaea. His research focuses on computational models of the mind, knowledge representation, and diversity-aware data-driven social innovation. He has supervised over 100 doctoral/post-doctoral students and contributed to interdisciplinary projects like the Knowdive Group and DataScientia Initiative. Education and Career: Studied/Worked at Universities of Genoa, Stanford, Edinburgh; served as Vice-Rector of the University of Trento, coordinated national/international research programs, and held leadership roles in organizations like IJCAI and KR, Inc. Research Interests: Explores how knowledge is grounded in unknowns, with applications in AI ethics, cultural heritage preservation, and low-resource language processing. His work bridges theory and technology transfer, including roles in the European Research Council and Italian National Research Programs. Awards: Ten Best Paper Awards, over fifty invited talks, and chair roles at major conferences (e.g., ICDCS 2020, IJCAI 2005). Editorial roles include the Journal of Data Semantics and Journal of Artificial Intelligence Research. Grants/Initiatives: Spearheaded platforms like QROWD for citizen-driven smart city analytics and WeNet for social interaction integration. His current focus includes mitigating language model biases and advancing pluriversal design in language technology.

Lina Spjutمشاهده پروفایل

دانشیار

• Education History
• Curriculum Studies
• Minority Education
• +۳ مورد دیگر

Lina Spjut is an Associate Professor in the Department of Education at Umeå University. Her research focuses on the intersection of educational history, curriculum analysis, and minority representation. She leads the 'Utbildningshistoria' research group and participates in the History and Education research center at Umeå's Social Studies Didactics unit. Her work examines historical educational policies, particularly regarding Sámi and Finnish minorities, through comparative textbook analyses and institutional studies. Educational Background: Her academic journey includes a Doctorate from Örebro University (2018) and Licentiate studies from Umeå University (2014). Her doctoral thesis analyzed national identity formation through Swedish and Finnish textbooks from 1866-2016. Current projects include investigating ironworks school systems' adaptation to state regulations post-1842 elementary school acts. Research Interests: Spjut explores how educational materials construct national identities, particularly for marginalized groups. She analyzes historical curricula's role in shaping ethnic consciousness and evaluates contemporary textbooks' portrayal of minority communities. Methodologically, she employs critical discourse analysis and comparative historical research. Key Research Themes: Textbook content analysis across time and borders Sámi cultural representation in education Nordic educational historiography Minority inclusion policies Industrial-era school systems Her work reveals evolving narratives of national belonging, showing how educational materials both reflect and shape societal attitudes toward minorities. Current projects focus on institutional adaptations in ironworks schools during Sweden's decentralization period.

Mahdi Belcaidمشاهده پروفایل

استاد پژوهشی

• Computational Biology
• Bioinformatics
• Natural Language Processing
• +۳ مورد دیگر

Mahdi Belcaid is an Assistant Research Professor at the University of Hawaii at Manoa, holding joint appointments in the Information and Computer Sciences Department and the Hawaii Institute of Marine Biology (HIMB). He serves as the Executive Director of the Hawaii Data Science Institute (HIDSI). His research focuses on computational biology, bioinformatics, natural language processing (NLP), and data science education. Belcaid earned his M.Sc. in Computer Science from the University of Quebec at Montreal and his Ph.D. in Computer Science from the University of Hawaii. His lab is multidisciplinary, integrating informatics with biology and document analytics. Notable projects include developing AI tools for medical record systems and expense-tracking apps with high school interns under the Hokulani Project. He emphasizes collaboration and innovation, aiming to advance computational methods in biology and healthcare. Recent work includes viral genomics analysis, LLM applications in genomics, and improving disease tracking through sero-molecular studies. Belcaid’s mission is to drive scientific impact through software engineering and data-driven solutions, prioritizing education and community engagement. His lab’s achievements include the Resheipt app and Parrot Forms, showcasing AI’s potential in healthcare and education. He actively participates in translational research and digital collaboration tools, such as Sage3 and 2D Jupyter Notebooks.

Tomoko Takedaمشاهده پروفایل

مدرس

• Second Language Acquisition
• Foreign Language Pedagogy
• Discourse and Grammar
• +۳ مورد دیگر

Tomoko Takeda is a Lecturer in the Department of Modern Languages & Literatures at Santa Clara University's College of Arts and Sciences. She specializes in Japanese linguistics and pedagogy, focusing on discourse analysis, second language acquisition, and foreign language teaching methodologies. Education: M.A. and Ph.D. in Japanese Linguistics and Pedagogy. Research Interests: Her work addresses functional aspects of Japanese grammar, narrative analysis across spoken/written modalities, and the application of linguistic theory to language education. She develops tools for analyzing syntactic structures in Japanese, such as conjunctive particles and postpositional marking systems. Teaching: Instructs Japanese language courses from introductory to advanced levels (JAPN 1-23, 100-101) and cultural studies courses (JAPN 137: Japanese Culture & Society/Language). Publications: Her research spans computational linguistics applications in Japanese syntax analysis (2014 CAJLE paper) and theoretical studies on postpositional systems (2006 Japanese Korean Linguistics).

Ahmed El-Robyمشاهده پروفایل

دانشیار

• Knowledge Graphs
• Question Answering Systems
• Domain Adaptation
• +۲ مورد دیگر

Ahmed El-Roby is an Associate Professor in Carleton University's School of Computer Science, affiliated with the Institute for Data Science. His research spans question answering over knowledge graphs, domain adaptation, and sports analytics. He leads projects on cross-domain recommendation systems and knowledge graph benchmarking, with applications ranging from healthcare to antiquities trafficking analysis. His teaching includes database systems and big data trends. Research groups focus on knowledge graph analytics and machine learning applications, with active collaborations in sports analytics and healthcare AI.

Anca Ralescuمشاهده پروفایل

استاد

• Machine Learning
• Imbalanced Data Learning
• Image Understanding
• +۴ مورد دیگر

Dr. Anca Ralescu is a Professor in the Department of Computer Science at the University of Cincinnati. She teaches a wide range of computer science courses including Introduction to Computer Science, Data Structures, Algorithms, and Machine Learning. Her PhD in Mathematics/Theory of Probability from Indiana University Bloomington forms the foundation for her interdisciplinary research approach. Her research centers on machine learning theory and applications, with specific focus on learning from imbalanced data, context-dependent computing, feature selection, and quantum computing. Applied research includes brain-computer interfaces for individuals with cerebral palsy, malware detection for avionics systems, and morphological analysis for cerebral aneurysm prediction. She maintains significant research funding from NSF, Air Force Research Laboratory, and NIH. Publications reveal strong emphasis on fuzzy systems applications in cybersecurity and medical domains, with recent work exploring machine learning techniques for malware detection in executable files and neuroimaging analysis. Collaborative projects investigate binary diversification for cyber defense and brain-computer interfaces for motor impairment rehabilitation. Significant grants include NSF funding for brain-computer interface exploration and Air Force Research Laboratory support for malware detection in avionics systems. Teaching portfolio spans undergraduate to advanced graduate courses in algorithms, programming languages, and artificial intelligence.

Martin Jagersandمشاهده پروفایل

استاد

• Robotics
• Computer Vision
• Medical Imaging
• +۲ مورد دیگر

Martin Jagersand is a Professor in Computing Science at the University of Alberta, specializing in robotics, computer vision, and medical imaging. His research develops real-time vision systems for robot control in unstructured environments, including assistive technologies and space telerobotics. Key projects include Back2Future-SIM for predictive haptic feedback in teleoperation, quantum models for visual neuroscience with Concetta Morrone, and wheelchair-mounted robotic manipulators for independent living. His work emphasizes applications in healthcare, space exploration, and autonomous systems. He teaches courses like CMPUT 428 (3D Computer Vision) and mentors graduate students in robotics and machine learning. His recent publications focus on data-driven teleoperation and activity analysis for assistive robotics.

Nanette Veilleuxمشاهده پروفایل

استاد

• Computational Linguistics
• Speech Recognition
• STEM Education
• +۳ مورد دیگر

Nanette Veilleux is a Professor and Director of the Data Science Program at Simmons University, within the Department of Computer, Data, and Mathematical Sciences. She holds a Ph.D. in Systems Engineering from Boston University and has over 30 years of academic experience. Her research focuses on computational models of speech prosody and pedagogical strategies to enhance STEM retention. She has led NSF-funded projects, including collaborations on prosody and meaning, and serves as a Research Affiliate at MIT's Research Lab of Electronics. Veilleux is also a former Fulbright Scholar in Vietnam and Rwanda. Education: Ph.D., Systems Engineering, Boston University (1994) M.S.E.E., Electrical Engineering, Boston University (1988) Sc.B., Biophysics, Brown University (1979) Research Interests: Her work bridges computational linguistics and education. Key areas include intonational phonology (e.g., F0 scaling, tonal alignment) and STEM education equity, emphasizing faculty-student mentorship and community-building strategies. She co-developed the PoLaR annotation system for prosodic variation analysis. Recent Articles: Recent work explores machine learning applications in prosody (e.g., epistemic shifts in intonation) and evaluates AI tools like ChatGPT in academia. Her pedagogical research highlights coding bootcamps' role in fostering belongingness. Awards: 2022 IEEE Mary Kenneth Keller Teaching Award 2023 CRA-E Mentoring Award Fulbright Scholarships (Vietnam, 2021-22; Rwanda, 2013) Advising & Grants: Veilleux mentors 3-7 undergraduates annually, with grants supporting research in humanitarian software (e.g., automatic speech recognition for under-resourced languages) and inclusive STEM education. She leads the HHMI Simmons team and collaborates on national initiatives like the Colleges of the Fenway STEM Scholars program. Labs/Teams: Active in the Fulbright University Vietnam and Kilgali Institute partnerships, focusing on curriculum development and global STEM education.

Marju Kapsمشاهده پروفایل

مدرس

• Psycholinguistics
• Cognitive Psychology
• Information Structure
• +۳ مورد دیگر

Marju Kaps is a Lecturer in Psychology at the University of Edinburgh's School of Philosophy, Psychology and Language Sciences. Her research focuses on psycholinguistics, cognitive psychology, and experimental syntax, with a particular emphasis on information structure and language processing in Estonian and other languages. She holds a PhD in Linguistics from UCLA and an MA (Hons) in Psychology and Linguistics from the University of Edinburgh. Education: PhD in Linguistics, University of California, Los Angeles MA (Hons) in Psychology and Linguistics, University of Edinburgh Research Interests: Dr. Kaps investigates how syntactic structures and information packaging (e.g., contrastive topics, ellipsis) interact with real-time language processing. Her work employs eye-tracking, pupillometry, and experimental methods to study phenomena in Estonian and other languages, addressing questions about agreement systems, word order flexibility, and the cognitive mechanisms underlying sentence comprehension. Teaching: She teaches undergraduate courses on data analysis in R for psychology students and postgraduate modules on the psychology and neuroscience of language. As of 2024, she is not accepting new PhD supervision inquiries.

Elizabeth Wonnacottمشاهده پروفایل

استاد

• Language Acquisition
• Statistical Learning
• Educational Linguistics
• +۳ مورد دیگر

Elizabeth Wonnacott is a Professor of Language Science at the University of Oxford’s Department of Education. Previously, she held positions as an Associate Professor at UCL’s Division of Language Sciences and an Assistant Professor in Psychology at the University of Warwick. Her academic journey includes a Junior Research Fellowship at Linacre College, Oxford, and degrees in Linguistics and Artificial Intelligence (University of Edinburgh) and Brain and Cognitive Sciences (University of Rochester). Her research focuses on human language learning mechanisms, particularly statistical learning processes in first and second language acquisition. Key interests include naturalistic versus classroom-based learning, educational implications for language teaching, literacy development, and discriminative learning theories. She explores how variability in input influences learning outcomes, with recent work supported by a Leverhulme Trust grant examining discriminative linguistics. Dr. Wonnacott teaches on the MSc in Applied Linguistics and Second Language Acquisition and the MSc in Applied Linguistics for Language Teaching. She supervises doctoral students interested in statistical learning, age-related differences, implicit vs. explicit learning, and computational modeling of language acquisition. Her work is centered at the Language Learning Lab , where she investigates topics like phonetic training, multi-word unit learning, and the role of iconicity in language development. Her research bridges cognitive science, linguistics, and education, emphasizing experimental and computational approaches to understanding language acquisition.

Kaden Holladayمشاهده پروفایل

مدرس

• Morphology
• Syntax
• Semantics
• +۴ مورد دیگر

Kaden Holladay is a Lecturer in the Department of Linguistics at Harvard University. He holds a PhD from the University of Massachusetts Amherst (2023) and previously taught at Western Washington University (2023-2024). His research focuses on morphology, syntax, and their interface with semantics, particularly exploring person contrasts in natural language and their typological implications. Education: PhD in Linguistics, University of Massachusetts Amherst (2023) BA in Linguistics, Hampshire College (2016) Research Interests: Holladay investigates the interplay between syntactic structures and semantic interpretation, with special attention to morphological phenomena like suppletion, lenition, and polysynthesis in languages such as Yup’ik and Finnish. He also engages with computational approaches to word-order typology and ellipsis phenomena (e.g., Right Node Raising, VP ellipsis). Teaching: He has instructed courses ranging from introductory linguistics to advanced morphology/syntax at Harvard and Western Washington University, as well as field methods and linguistic theory at UMass Amherst.