جست‌وجوی استاد و پژوهشگر

Wu, Jingمشاهده پروفایل

مدرس

• Second Language Acquisition
• Language Assessment and Evaluation
• Chinese Pedagogy
• +۳ مورد دیگر

Jing Wu is an Instructor of Chinese and PhD student in the Department of East Asian Languages and Literatures at the University of Hawai‘i at Mānoa. She has over 10 years of teaching experience in Chinese language courses across all proficiency levels, including in-person and online formats. Currently serves as Faculty Resident Director for UH Mānoa’s Shanghai study abroad programs since 2018, and previously served as Faculty/Instructor Evaluator for the Center for Teaching Excellence (2019-2020). Affiliations: College of Arts, Languages and Letters Roles: Study Abroad Program Director, Teaching Evaluator Research focuses on second language assessment, pedagogy, and sociolinguistics with emphasis on classroom multimodal interactions. Recent work explores digital language corpora and performance-based assessment frameworks in Mandarin education. Notable achievement includes the 2022 Excellence in Teaching Award from her college. Research Keywords: Language Assessment, Synchronous Online Teaching, Multimodal Pedagogy Publications emphasize advancing assessment methodologies and integrating innovative practices into Chinese language education. Active contributor to both theoretical and applied research in L2 Chinese education.

STEFANO RICCIARDIمشاهده پروفایل

دانشیار

• Augmented Reality
• Biometrics
• Computer Vision
• +۳ مورد دیگر

Prof. Stefano Ricciardi is an Associate Professor at the Department of Biosciences and Territory, University of Molise. His research focuses on augmented reality, biometrics, computer vision, and medical simulation technologies. He has contributed to projects involving industrial maintenance systems, healthcare rehabilitation, and cultural heritage applications. His work often integrates advanced algorithms with real-world applications such as facial recognition, context-aware security frameworks, and virtual reality environments. Prof. Ricciardi's recent research emphasizes innovations in augmented reality for maintenance tasks, implicit biometric authentication, and wearable health monitoring systems. He has explored the use of machine learning techniques in medical diagnostics and developed frameworks for home rehabilitation using Microsoft Azure Kinect. His work bridges technological advancements with practical solutions in healthcare, industrial automation, and cultural heritage preservation. Key projects include the EDISON authentication framework and the 2Vita-B Physical rehabilitation system. His publications highlight interdisciplinary collaborations, combining computer science, biomedical engineering, and human-computer interaction principles. He actively publishes in top-tier venues, addressing topics like head pose estimation, dynamic simulation for production facilities, and augmented reality applications in archaeological exploration.

• Cybersecurity
• Machine Learning
• Privacy-Preserving Techniques
• +۷ مورد دیگر

Xichen Zhang is an Assistant Professor at the Department of Finance, Information Systems and Management Science within the Sobey School of Business at Saint Mary's University. His research focuses on cybersecurity, privacy-preserving techniques, federated learning, fake news detection, and machine learning applications in edge-cloud collaboration and mobile crowdsensing. He holds a Ph.D. in a relevant field and has contributed to interdisciplinary projects involving blockchain-based voting systems and IoT security solutions. His work emphasizes practical solutions to modern challenges in data privacy, misinformation detection, and distributed computing. Notable contributions include the development of the TruthSeeker dataset for real/fake content analysis and frameworks like SCORE for scalable contact tracing. His articles explore topics from adversarial machine learning defenses to temporal user credibility models in social networks. Dr. Zhang's research integrates technical innovations with societal impact areas like healthcare informatics and election security. He collaborates across disciplines to address privacy challenges in both academic and industrial contexts. Current projects investigate federated reinforcement learning for IoT systems and multimodal fake news detection using image-text consistency analysis.

• Signal Processing
• Financial Signal Analysis
• Machine Learning
• +۵ مورد دیگر

Ali Akansu is a Professor in the Department of Electrical and Computer Engineering at NJIT. His academic career spans multiple decades, with significant contributions to signal processing, financial engineering, and multimedia communications. He has led or co-led four major NSF-funded projects, including the Center for Digital Video & Media Research and the Laboratory for Multimedia Signal Processing and Communication. His research focuses on topics such as eigenanalysis for financial portfolios, machine learning in network analysis, and multimodal affective state assessment using EEG and fNIRS. Key research areas include financial signal processing, portfolio optimization, eigensubspace applications, and data hiding techniques. Notable projects involve FPGA-based real-time risk analysis systems and GPU implementations for eigenportfolio analysis. He has published over 190 peer-reviewed articles, with impactful work in journals like Journal of Investment Strategies and Brain Sciences . His recent work combines machine learning with signal processing to address challenges in network traffic forecasting and financial market dynamics. He has also contributed to biomedical signal processing through studies on affective state assessment using neuroimaging techniques. Awards and recognitions include a h-index of 27 and over 2,694 citations. Grants: National Science Foundation (1991-1993, 1997-2002): Real-Time Color Video Workstation, Multimedia Signal Processing Lab, and Digital Video Research Center Labs/Teams: Leadership in NJIT's Laboratory for Multimedia Signal Processing and Financial Signal Processing groups

• Heritage Studies
• Memory and Justice
• Post-colonialism
• +۴ مورد دیگر

Dr. Kate Moles is a Reader in Sociology at Cardiff University's School of Social Sciences, specializing in heritage, memory, and post-colonialism. Her research combines ethnography with innovative methods like soundwalks and video documentation to explore how communities navigate legacies of colonialism and industrial decline. She co-leads the EdJAM network, funded by UKRI/GCRF, which uses creative approaches to teach about violent histories. Her work on wild swimming examines cultural practices and environmental ethics. Moles has supervised numerous PhD students and teaches courses in qualitative methods and decolonizing social sciences. Education: BA (Trinity College Dublin), MA and PhD (Cardiff University). Professional roles include HEA Fellowship and leadership in WISERD research projects. Research focuses on two core areas: 1) Heritage/memory in post-conflict societies, including Uganda and Northern Wales, and 2) Swimming cultures and environmental ethics. Recent projects include mobile exhibitions in Uganda and digital heritage initiatives. Her work bridges academia with civil society through participatory methods. Key publications include studies on wild swimming ethics, post-industrial memory, and youth futures. Awarded HEA Fellowship (2016). Current projects involve the National Trust's Penrhyn Castle labor history initiative and global water studies.

• Educational Linguistics
• Second Language Teaching
• Bilingualism
• +۹ مورد دیگر

Beatriz Chaves Yuste is an Assistant Professor (part-time) at the Complutense University of Madrid's Department of English Studies: Linguistics and Literature. She holds a PhD in Applied Linguistics for Language Teaching, along with BAs in English and Hispanic Philology and a Master's in Bilingual Education. With over 20 years of teaching experience, her primary focus is on English as a Foreign Language (EFL) and English for Specific Purposes (ESP). Her research interests span educational linguistics, foreign language teaching methodologies, active learning strategies, bilingualism, and the integration of ICT in education. She has contributed to national and international conferences and peer-reviewed journals such as Encuentros and Didacticae . Dr. Yuste explores innovative pedagogical approaches like flipped classrooms, gamification, and cooperative learning, emphasizing their impact on student engagement and linguistic competence. Her work often addresses affective variables (e.g., anxiety) in language learning and the role of technology in enhancing educational outcomes. While she has no current PhD supervision experience, she welcomes proposals in her research areas, particularly in secondary education contexts. She actively participates in curriculum development and educational innovation projects, including the creation of digital tools for vocabulary acquisition and collaborative learning environments. Her publications highlight themes such as digital reading comprehension, the efficacy of active methodologies in grammar instruction, and the application of gamification in multilingual settings. She also advocates for inclusive education through adaptive teaching strategies and sustainability awareness integration in language curricula.

• Biometrics
• Signal Processing
• Biomedical Engineering
• +۳ مورد دیگر

Dr. Stephanie Schuckers is a Visiting Professor and Director of the Center of Identification Technology Research (CITeR) at Clarkson University's Coulter School of Engineering & Applied Sciences. Her research focuses on signal processing from human-derived data, including biometric systems like fingerprints, iris, and electrocardiograms. She holds a PhD in Electrical Engineering from the University of Michigan and has extensive industry collaboration through CITeR, a National Science Foundation-funded center. Her work addresses liveness detection, spoof attack mitigation, and multimodal biometric systems. Over 100 academic publications and congressional testimony highlight her expertise. She teaches courses in stochastic processing, biometrics, and biomedical engineering. Education: PhD/MSE (University of Michigan), BSE (University of Iowa) Research emphasizes statistical techniques, pattern recognition, and algorithm development for biomedical signals. Key areas include pediatric biometrics, cybersecurity for authentication systems, and sensor data analysis. Her lab evaluates systems against advanced persistent threats and develops standards for biometric equity across demographics. Recent publications explore deepfake detection, iris segmentation in infants, and fusion of behavioral biometrics. She leads the LivDet competitions for biometric liveness detection and pioneered datasets for keystroke dynamics and mobile behaviometrics. Grants: NSF, DHS, and industry partnerships Labs/Teams: CITeR, BIOSAL Experience

Lindi Liaoمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Machine Learning
• Natural Language Processing
• +۹ مورد دیگر

Dr. Lindi Liao is an Associate Professor in the School of Computing at George Mason University. She specializes in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), and has over 20 years of R&D experience. Her research includes multimodal AI, generative AI, edge AI, self-driving cars, robotics, and geospatial computing. She holds a PhD in Computer Science from George Washington University and an MS from Purdue University. Education: PhD in Computer Science, George Washington University MS in Computer Science, Purdue University Research Interests: Dr. Liao's work spans Artificial Intelligence , Machine Learning , Natural Language Processing , Computer Vision , and Big Data Computing . She explores cutting-edge areas like Generative AI , Agentic AI , Human-Robot Interaction , and AI for Arts & Music . Her contributions include frameworks for multimodal knowledge retrieval , automated defect detection , and music generation algorithms . Advising & Grants: Dr. Liao oversees rigorous GTA/GRA selection processes with stringent academic and technical criteria. She prioritizes candidates with top-tier academic performance, research passion, and collaborative skills. Her industry collaborations include Fortune Global 30 companies and government agencies like the U.S. Department of Transportation. Labs/Teams: While specific lab names are not mentioned, Dr. Liao's work bridges academia and industry through collaborative R&D initiatives in AI, robotics, and Big Data.

• Glottology
• Linguistics
• Speech Production
• +۳ مورد دیگر

Francesco Sigona is a Researcher in Glottology and Linguistics at the University of Salento's Department of Humanities, affiliated with the DReAM Laboratory (Diffused Laboratory of Interdisciplinary Research Applied to Medicine) at Vito Fazzi Hospital in Lecce. He holds a PhD in Information Technologies for Engineering. His research explores the intersection of linguistics, neuroscience, and technology, with focus areas including: Neural mechanisms of language processing and speech production Voice biometrics and forensic speaker recognition Articulatory phonetics and speech technology development Clinical applications of linguistic analysis in voice disorder detection His extensive publication record demonstrates a consistent focus on multimodal approaches combining physiological measurements, neurophysiological data, and computational methods across medical and linguistic domains.

Mariusz Rybnikمشاهده پروفایل

مدرس

• Artificial Intelligence
• Machine Learning
• Cognitive Modeling
• +۴ مورد دیگر

Mariusz Rybnik is a Lecturer at the Institute of Informatics, University of Bialystok. He holds an MSc in fuzzy c-means classification from Bialystok University of Technology and a PhD in task decomposition and Artificial Neural Networks from Paris XII Val-de-Marne University. His research focuses on cognitive modeling, music information processing, biometric systems, and embedded safety technologies. He contributes to projects like Religion, Ideology & Prosociality , implementing computational models to study secularizing societies. Education: MSc: Fuzzy C-Means Classification (Bialystok University of Technology) PhD: Task Decomposition & Artificial Neural Networks (Paris XII Val-de-Marne University) Research Interests: Artificial Intelligence & Machine Learning applications Cognitive modeling and agent-based simulations Biometric authentication systems (e.g., keystroke dynamics, face recognition) Music information retrieval and harmonization models Embedded systems for automotive safety (eCall, accident detection) Projects & Contributions: Lead developer for computational models in the Religion, Ideology & Prosociality project Advances in eCall systems for vehicle safety and emergency response Innovations in fusion of biometric traits for security initiatives Advising & Grants: No formal advisees listed; active in collaborative research projects. Labs/Teams: Affiliated with the Institute of Informatics' research groups in AI and embedded systems.

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +۴ مورد دیگر

Yin Chen is a Professor in the Department of Computer Science at South China Normal University, Guangdong, China. With an extensive publication record spanning over 25 years from 2000 to 2025, Professor Chen has established themselves as a leading researcher in multiple domains of computer science and artificial intelligence. Professor Chen's research spans artificial intelligence, machine learning, computer vision, natural language processing, and deep learning. Their work demonstrates exceptional breadth across theoretical and applied domains, with significant contributions to facial expression recognition, transformer-based language models, 3D human modeling, and optimization algorithms. Recent research shows particular strength in multimodal learning, with numerous publications integrating visual, textual, and audio information for advanced AI applications. The publication trends reveal a consistent output of high-impact research, with a notable acceleration in recent years. Professor Chen's work appears in top-tier venues including IEEE Transactions, ACM Multimedia, and various specialized journals. Their research demonstrates strong interdisciplinary connections, bridging computer science with applications in engineering, bioinformatics, and mathematics. Professor Chen collaborates extensively with researchers across institutions, particularly with Jia Li, Meng Wang, Richang Hong, and Xianghua Fu. These collaborations span multiple projects in affective computing, multimodal translation, and algorithm development. The research group appears to be active in both theoretical advancements and practical implementations of AI systems.

Jessica Pedersen Belisle Hansenمشاهده پروفایل

دانشیار

• Interaction and Social Interaction
• Video-mediated Interaction
• Multilingualism
• +۳ مورد دیگر

Jessica Pedersen Belisle Hansen is an Associate Professor at Oslo Metropolitan University's Department of Languages, Literature and Culture. Her research focuses on interaction and social interaction (particularly video-mediated contexts), multilingualism, and communication in professional settings like healthcare and education. She holds a PhD from the University of Oslo (2021) and has published extensively on interpreting practices, remote interpreting dynamics, and linguistic diversity. Education Background: PhD in Multilingualism (University of Oslo, 2021) Master's in Nordic Studies (University of Oslo, 2016) Bachelor's in Sign Language and Interpreting (University of Oslo) Research Interests: Video-mediated interaction analysis, institutional communication, interpreter training, and multilingualism's societal impact. She leads studies on how technology shapes professional interpreting practices, particularly in healthcare and educational settings. Her recent publications explore repair mechanisms in interpreted conversations, the role of visual ecology in remote interpreting, and the integration of sign language in education. She collaborates with research groups like Multilingual Upbringing and Education, and RIDE (Research in Digital Education). Teaching involves courses on multilingualism, linguistic diversity, and literature education.

Elizabeth Aldertonمشاهده پروفایل

استاد

• Adolescent Literacy
• Teacher Professional Development
• Forgiveness Education
• +۳ مورد دیگر

Elizabeth Alderton is a Professor and Graduate Program Coordinator in the Department of Leadership, Literacy, and Social Foundations at the University of Wisconsin Oshkosh. She holds a Ph.D. in Curriculum and Instruction from the University of Wisconsin-Madison (2007) and an MSE in Reading from UW Oshkosh (1995). Her career spans 25+ years, including 5 years in P-12 education as a teacher and reading specialist before transitioning to higher education. Research Interests: Dr. Alderton focuses on teacher learning, professional development, and forgiveness education implementation in urban schools. She emphasizes qualitative research methods and practical applications of educational theories. Her work bridges classroom practice with systemic leadership challenges, particularly in literacy and middle school environments. Teaching Philosophy: She advocates student-centered learning, hands-on experiences, and high expectations for diverse learners. Courses taught include Adolescent Literacy, Middle School Education Methods, and Administration of Reading Programs. Recent Scholarship Trends: Her 2024 work addresses mental health support for nontraditional students, while 2021 articles explore inclusive science pedagogy and visual literacy. Earlier work (2013-2017) established her focus on forgiveness education's impact on teachers and classrooms. Professional Background: Employed continuously at UW Oshkosh since 1999, she has contributed to both teacher preparation and graduate leadership programs. Her expertise combines K-12 experience with university-level curriculum development.

RICHARD LAMBمشاهده پروفایل

دانشیار

• Education Technology
• Neuroscience in Education
• Virtual Reality Applications
• +۵ مورد دیگر

Richard Lamb, Ph.D. is an Associate Professor in the Department of Clinical and Administrative Pharmacy at the University of Georgia's College of Pharmacy. He directs the Neurocognition Science Laboratory, focusing on integrating neuroscience, artificial intelligence, and extended reality (XR) technologies into education. His work emphasizes STEM education, special education, and mental health interventions. Education and Background : While detailed educational qualifications are not explicitly listed, Dr. Lamb’s extensive research and publications in education technology and neuroscience indicate advanced academic training in these fields. Research Interests : Dr. Lamb’s research spans AI-driven adaptive learning systems for students with disabilities, XR applications in clinical therapy and STEM training, neurocognitive mechanisms of learning, policy and workforce development in STEM education, and mental health interventions using digital tools. Recent Trends in Publications : His recent work (2023–2025) highlights advancements in AI integration for special education, VR-based therapies for phobias and mental health, and the role of XR in enhancing STEM instruction. He also explores systemic challenges like STEM workforce gaps and national security implications of education policies. Grants and Labs : As director of the Neurocognition Science Lab, he oversees research on educational technology and cognitive processes. Grant support focuses on projects like AI in literacy coaching and virtual reality simulations for teacher training. Labs/Teams : The Neurocognition Science Laboratory collaborates on projects blending neuroscience, AI, and education to develop innovative learning tools and therapeutic interventions.

Nick Rahimiمشاهده پروفایل

استادیار

• Cybersecurity
• Artificial Intelligence
• Decentralized Systems
• +۳ مورد دیگر

Dr. Nick Rahimi is an Assistant Professor in Computer Science and Computer Engineering at the University of Southern Mississippi. He serves as Director of the Cyber Innovations Lab and Cybersecurity Program Coordinator. Rahimi holds a Ph.D. and master's in Computer Science from Southern Illinois University and dual bachelor's degrees in Software Engineering and Information Systems Technologies. His research focuses on: Cybersecurity and trustworthy AI systems Brain-computer interface security Decentralized network architectures Digital warfare strategies Computing education pedagogy Recent publications (2023-2025) demonstrate strong trends in AI-driven cybersecurity, neural signal processing, and decentralized IoT systems. Over 30 articles explore machine learning applications in threat detection, network optimization, and human-computer interaction. Rahimi teaches courses including: CSC 428: Machine Learning in Cybersecurity CSC 460: Python in Data Science CSC 327: Secure Software Development ITC 510: Cyber Law & Policy He directs the Cyber Innovations Lab where he mentors graduate students in cybersecurity research and develops industry partnerships.