جستجوی استاد راهنمای دانشگاهی

• Cognitive Neuroscience
• Multisensory Integration
• Attention Processes
• +۳ مورد دیگر

Jessica Green is an Associate Professor in the Department of Psychology at the University of South Carolina, affiliated with the McCausland College of Arts and Sciences and the Institute for Mind and Brain. Her research focuses on understanding neural and psychological mechanisms of attention and perception, using EEG, fMRI, and combined EEG/fMRI techniques. Key projects include studying voluntary attention processes, multisensory integration, and attention deficits in dyslexia. Her research employs behavioral and neuroimaging methods to link brain activity (via EEG/ERPs and fMRI) with cognitive processes. Current work explores how sensory modality influences attention networks and investigates multisensory integration in perceiving objects, as well as cognitive influences like emotion on this process. She also examines attentional deficits in dyslexia across visual and auditory modalities. Notable research contributions include studies on cross-modal spatial attention, attentional control dynamics, and neuroimaging methodologies like beamformer source reconstruction. Her work bridges cognitive neuroscience with clinical applications, such as ADHD neurofeedback interventions. Labs/Teams: Active in the Institute for Mind and Brain, collaborating on interdisciplinary projects combining neuroimaging and cognitive psychology.

• 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.

Melanie Spenceمشاهده پروفایل

استاد

• Infant Perception
• Face Perception
• Infant-Directed Speech
• +۶ مورد دیگر

Melanie Spence is a Professor in the Department of Psychology at the School of Behavioral and Brain Sciences (BBS) at The University of Texas at Dallas. She serves as Associate Dean of Undergraduate Education and Director of the BBS Honors Program, contributing to academic leadership and student research initiatives. Her educational background includes a Ph.D. and M.A. in Experimental Psychology from the University of North Carolina at Greensboro, a B.A. in Psychology from Emory University, and an additional Psychology degree from Converse College. Infant Perception: Focuses on how infants process communicative cues in faces and voices. Face Perception: Examines scanning patterns and emotional expression recognition. Speech Processing: Studies categorization of infant-directed speech and its affective messages. Recent publications highlight her work on infant learning, auditory-visual integration, and emotional cue recognition. Awards include Fellow of the Association for Psychological Science and the Callier Scholar Award . She collaborates with institutions like the Callier Center for Communication Disorders and Center for Children and Families , and has mentored students through programs such as the Duane and Linda Buhrmester Research Award . Funding from the Timberlawn Psychiatric Foundation and Meadows Foundation supports her research.

Anh Nguyenمشاهده پروفایل

دانشیار

• Deep Learning
• Computer Vision
• Generative Modeling
• +۵ مورد دیگر

Anh Nguyen is an Associate Professor in the Department of Computer Science and Software Engineering at Auburn University, affiliated with the Samuel Ginn College of Engineering. His work focuses on deep learning, computer vision, and explainable AI. He holds a Ph.D. from the University of Wyoming and a B.S. from Assumption University. Research highlights include developing methods to improve AI robustness, analyzing biases in large language models, and creating tools for visual correspondence in image processing. He leads the Center for Artificial Intelligence and Cybersecurity Engineering and directs Auburn's first K-6 AI education program through his AI Club after-school initiative. Recipient of a $460,736 NSF CAREER Award for AI innovation Developed the AI@AU lecture series and multiple benchmark datasets (e.g., ImageNet-Hard) Collaborates with industry partners on real-world AI applications Recent projects explore multimodal model limitations (Zerobench), medical imaging (LiteGPT for chest X-rays), and interactive AI systems that incorporate human feedback. His work bridges theoretical advancements with practical implementations in healthcare, wildlife monitoring, and education.

Alexandra Psarrouمشاهده پروفایل

دانشیار

• Deep learning methods for Image Quality Performance
• Explainable learning models
• Reinforcement learning
• +۳ مورد دیگر

Alexandra Psarrou is a Reader in the School of Computer Science and Engineering at the University of Westminster, serving as Head of School from 2002-2019. She holds a BSc and MSc from Queen Mary University of London and a PhD from Queen Mary, London (1996). Her research focuses on dynamic vision, explainable AI, hyperspectral analysis, and image quality metrics. Education: BSc (1987), MSc (1988), PhD (1996) Roles: Reader, former Head of School, member of multiple University committees Research interests include deep learning, reinforcement learning, and applications in cultural heritage. She founded the Computational Vision Research Group (CVRG) in 1997, advancing techniques like recurrent neural networks and kernel PCA models. Awards include Best Paper Awards at BMVC (1999), IMECS (2008), and IS&T (2020). She led major grants like the NOESIS project (€709k) and diARTgnosis (€518k). Supervised 10+ PhD students in areas like gesture recognition and medical imaging. Labs/Teams: Computational Vision and Imaging Technologies Research Group Grants: NOESIS, diARTgnosis, HISTORIA, HEFCE NFF

David M. Sidhuمشاهده پروفایل

استادیار

• Language Processing
• Sound Symbolism
• Iconicity
• +۵ مورد دیگر

Dr. David M. Sidhu is an Assistant Professor in the Department of Psychology at Carleton University, affiliated with the Faculty of Arts and Social Sciences. He holds a Ph.D. from the University of Calgary and completed a postdoctoral fellowship at University College London, funded by SSHRC. His research focuses on multimodal language processing, sound symbolism, and embodied cognition, exploring how language sounds connect to sensory and conceptual meanings. Education: Ph.D. in Psychology, University of Calgary Postdoctoral Research, University College London (SSHRC-funded) Research Interests: Sound symbolism and iconicity in language Cross-modal associations (e.g., shape-sound mappings) Embodied cognition and conceptual metaphor theory Name symbolism and social perception Language evolution and lexical development Funded by NSERC and SSHRC, his CLaSSI Lab investigates topics like the bouba/kiki effect, vowel symbolism in size perception, and the cognitive mechanisms behind name stereotypes. Recent work includes studies on temporal semantics and affective sound congruence. Lab & Collaborations: Director of the CLaSSI Lab, collaborating with institutions internationally. Research emphasizes experimental methods and large-scale language analyses.

Jingfeng Jiangمشاهده پروفایل

استاد

• Biomechanics
• Medical Imaging
• Machine Learning
• +۳ مورد دیگر

Jingfeng Jiang is a Professor of Biomedical Engineering and Graduate Program Director at Michigan Technological University. His research focuses on translational biomedical engineering, particularly in biomechanics, medical imaging, and machine learning applications. He holds a PhD in Civil Engineering (Computational Mechanics) from the University of Kansas, along with MS degrees in Computer Science and Structural Engineering, and a BS in Civil Engineering from Zhejiang University, China. Research Interests : Dr. Jiang’s work bridges biomechanics, medical imaging, and computational intelligence. He develops tools for transforming biomedical imaging data into clinically relevant parameters, such as soft tissue elasticity and blood flow characteristics. His current projects include real-time elastography systems, AI-driven medical imaging analysis, and precision medicine tools for cardiovascular and oncological applications. He collaborates closely with clinical and industrial partners, notably contributing to Siemens’ real-time elastography system. Education : PhD, Civil Engineering (Computational Mechanics), University of Kansas MS, Computer Science, University of Kansas MS, Structural Engineering (Structural Dynamics), Zhejiang University, China BS, Civil Engineering, Zhejiang University, China Grants and Collaborations : Dr. Jiang’s work involves clinical and industrial collaborations, including contributions to commercial medical imaging systems. His lab focuses on advancing ultrasound technologies, computational fluid dynamics modeling, and AI-driven diagnostics for cardiovascular diseases and cancers. Labs and Future Work : His research lab aims to improve precision medicine through tool development in medical imaging and biomechanics. Current open positions include doctoral students and post-doctoral researchers to support projects in aneurysm rupture prediction, liver fibrosis characterization, and AI-driven diagnostic systems.

Arthur G. Samuelمشاهده پروفایل

استاد

• Speech Perception
• Cognitive Psychology
• Auditory Processing
• +۷ مورد دیگر

Arthur G. Samuel is a SUNY Distinguished Professor in the Department of Psychology at Stony Brook University and an Ikerbasque Research Professor at the Basque Center on Cognition Brain & Language in Donostia, Spain. His research has established him as a leading figure in cognitive psychology with a specialization in speech perception and processing. Samuel received his B.A. in Psychology from Cornell University in 1975, where he completed his undergraduate thesis titled "Yakker II: A Speech Understanding System and its Psychological Basis." He went on to earn his Ph.D. in Psychology from the University of California, San Diego in 1979 under the guidance of David E. Rumelhart, with a dissertation titled "Speech is Specialized, Not Special." His academic career includes faculty positions at Yale University (1981-1991) and Stony Brook University (1991-present), where he was promoted to full Professor in 1993. Samuel's research primarily focuses on how humans process incoming auditory information, with particular emphasis on spoken language perception. His work investigates multiple perspectives on speech processing, including both "bottom-up" approaches examining early representations in speech perception and "top-down" approaches exploring how lexical knowledge influences lower-level processing. He is particularly known for his extensive research on the phonemic restoration phenomenon, which reveals how listeners use contextual knowledge to fill in missing speech segments. Additionally, his laboratory has produced significant findings on how listeners adapt to accented or non-standard speech, and the complex relationship between speech perception and production. Analysis of his recent publications reveals a continued focus on the dynamic nature of speech perception, with increasing attention to individual differences, cross-linguistic influences, and the integration of visual information in speech processing. His work consistently bridges theoretical cognitive psychology with practical applications in understanding language processing across diverse contexts and populations. Samuel has mentored numerous doctoral students and postdoctoral researchers who have gone on to establish their own successful research programs. His laboratory has produced significant work across multiple domains of cognitive psychology, including speech perception, visual attention, and memory. Notably, he has also involved high school students in research through the Intel National Science Talent Search, demonstrating his commitment to fostering scientific talent at all levels. His laboratory has conducted influential research on inhibition of return in visual attention and change deafness in auditory perception, extending his expertise beyond speech processing to broader cognitive mechanisms. Samuel's work consistently emphasizes the importance of understanding attention, perception, and cognition as interconnected processes rather than isolated phenomena.

Kui Wuمشاهده پروفایل

استاد

• Computer Networks
• Wireless and Mobile Networking
• Mobile Computing
• +۵ مورد دیگر

Prof. Kui Wu is a Professor in the Department of Computer Science at the University of Victoria, affiliated with the Faculty of Engineering and Computer Science. His research focuses on computer networks, wireless and mobile networking, mobile computing, and network security. He is part of the Parallel, Networking and Distributed Computing (PANDA) research group. Key areas of expertise include distributed learning frameworks, autonomous systems, IoT anomaly detection, and edge computing architectures. His work integrates machine learning techniques with network optimization, addressing challenges in real-time systems, security, and resource allocation. Notable contributions include advancements in federated learning, privacy-preserving distributed systems, and UAV-based monitoring solutions. Prof. Wu's research also explores edge computing innovations, such as smart contract-aided IoT resource sharing and energy-efficient edge data centers. He has contributed to over 50 peer-reviewed publications, with recent work emphasizing AI-driven network design, anomaly detection in IoT, and reinforcement learning applications in autonomous driving safety. His research has practical implications for improving the reliability and efficiency of next-generation communication and computing infrastructures.

Stephen Stifanoمشاهده پروفایل

دانشیار

• Instructional Communication
• Communication of Emotion
• Nonverbal Communication
• +۳ مورد دیگر

Stephen Stifano serves as Associate Professor in-Residence and Director of Undergraduate Studies in the Department of Communication Education within the University of Connecticut's College of Liberal Arts and Sciences (CLAS). He holds a Ph.D. from UConn (2011) and coordinates the department's large-lecture introductory communication course while providing training for teaching assistants. His research focuses on Instructional Communication , particularly how Immediacy Behaviors shape classroom experiences, alongside the Communication of Emotion in narrative media and health PSAs. Additional interests include Data Visualization for diverse audiences and the revival of digital media production pedagogy. His work bridges Nonverbal Communication theory with practical multimedia design applications. Stifano's publications demonstrate strong engagement with both theoretical frameworks and practical applications, with recent work emphasizing digital learning environments, audience-content creator interaction metrics, and cross-cultural emotional responses to media. His research consistently connects communication theory to educational innovation. Teaching Innovation Award (2019) University Teaching Fellow Award (2022) Five Top Papers Awards from National Communication Association Basic-Course Program of Distinction recognition for COMM 1000 (2016) As Director of Undergraduate Studies, Stifano led a complete curriculum overhaul and developed the FastTrack BA/MA Program. He chairs the CLAS Committee on Curricula and Courses, guiding UConn's largest college through Common Curriculum transition. His teaching portfolio spans COMM 1000 through advanced digital production courses, reflecting his commitment to both foundational communication principles and emerging media technologies. Stifano actively integrates multimedia production into the department's offerings, having revived digital media courses and developed programs for multimedia storytelling and video production. His colloquium talks on 'Multimedia Stimulus Design' and 'Speak as a Storyteller' demonstrate his focus on practical communication skill development across academic and professional contexts.

Tiare Feuchtnerمشاهده پروفایل

استادیار

• Human-Computer Interaction
• Virtual Reality
• Augmented Reality
• +۴ مورد دیگر

Dr. Tiare Feuchtner is a Tenure-Track Assistant Professor of Human-Computer Interaction at the University of Konstanz since 2021. She previously worked as a postdoctoral researcher at the Technical University of Vienna and Aarhus University, where she coordinated the MADE Fast project. PhD: Computer Science, Aarhus University (2018), thesis: 'Designing for Hand Ownership in Interaction with Virtual and Augmented Reality' Master's: Computer Science, Berlin Institute of Technology Bachelor's: Media Informatics, Technical University of Vienna Her research focuses on Human-Computer Interaction, emphasizing embodiment and novel user interfaces for immersive cross-reality (XR) technologies. She investigates embodied user interfaces that enable direct interaction through virtual bodies ('avatars') with transformations, augmentations, and 'superpowers' via multisensory feedback. Current projects include Interoceptive Signalling in Mixed Reality and Real-Time Optimization of XR User Interfaces. Her recent articles explore hybrid input devices, haptic props for 3D manipulation, physiological feedback in collaboration, and adaptive XR interfaces. She has received awards for her work, including the Microsoft Imagine Cup (2013). She actively contributes to academic service through conference organization (e.g., AlpCHI'26, QiVC'23), program committees (CHI, ISMAR), and workshops (Women* in Computing, Hybrid User Interfaces). Her teaching includes courses on human-computer interaction, Unity, and spatially-aware interactive spaces.

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.

• Psychology
• Neuroscience
• Linguistic Studies
• +۵ مورد دیگر

Jeremy Loebach is an Associate Professor of Psychology at St. Olaf College, located in Northfield, Minnesota. He is based in Regents Hall (Natural Science) and can be reached at loebach@stolaf.edu. As of 2023, he is on sabbatical leave until August 2025. His academic roles include teaching courses such as Principles of Psychology, Psychology of Hearing, and Cognitive Neuroscience, reflecting his expertise in auditory perception and cognitive processes. Loebach specializes in advising students pursuing careers in Speech and Hearing Sciences, Speech Language Pathology (SLP), and Audiology (AuD). His research focuses on speech perception, cochlear implants, and perceptual learning, with a notable emphasis on auditory neuroscience and music cognition. For detailed research, visit his lab’s website at SCofLab . His publications (2005–2014) explore topics like emotional attribution in music, perceptual adaptation to vocoded speech, and cochlear implant acoustics, demonstrating interdisciplinary engagement with psychology, neuroscience, and linguistics.

Laurie Hellerمشاهده پروفایل

استاد آموزشی

• Cognitive Neuroscience
• Cognitive Science
• Perception
• +۷ مورد دیگر

Laurie Heller is a Teaching Professor of Psychology at Carnegie Mellon University's Department of Psychology, affiliated with the Dietrich College of Humanities and Social Sciences. She holds additional affiliations with the Carnegie Mellon Neuroscience Institute (CMNI), CMU Music & Technology, CMU Center for Transformational Play, CMU CyLab Security and Privacy Institute, and the Center for the Neural Basis of Cognition (CNBC). Her research focuses on auditory perception, cognitive neuroscience, and the interplay between sound and human cognition. Education includes an S.B. in Brain & Cognitive Sciences from MIT, a Ph.D. in Psychology from the University of Pennsylvania, and a postdoctoral fellowship in Neuroscience at the University of Connecticut Health Center. Her work explores acoustic cues in sound event recognition, sound localization, and the effects of unwanted sounds. Collaborative projects include improving hearing aids, navigation aids for the visually impaired, and machine learning systems for sound classification. Recent research trends emphasize misophonia, environmental sound perception in hearing-impaired populations, and AI-driven sound synthesis. Her courses include Auditory Perception, Research Methods in Cognitive Psychology, and Music Cognition. She leads the Auditory Perception Lab and serves as an Associate Editor for the Journal of the Acoustical Society of America.

Caroline L. Riegerمشاهده پروفایل

دانشیار

• Applied Linguistics
• Cultural Studies
• Intercultural Communication
• +۸ مورد دیگر

Caroline L. Rieger is an Associate Professor at the University of British Columbia’s Department of Central, Eastern, and Northern European Studies, within the Faculty of Arts. Her expertise lies in applied linguistics, cultural studies, and intercultural communication. She holds an M.A. from the Universität Essen (1992) and a PhD from the University of Alberta (2000). Rieger’s research focuses on language in use, particularly pragmatics, sociolinguistics, and language pedagogy, with notable contributions to intercultural competence and politeness studies. Her teaching spans German language courses (all levels), applied linguistics, and graduate seminars on second language acquisition. Rieger emphasizes constructivist learning, fostering curiosity and critical thinking in students. She has authored over 30 publications, including works on translation pedagogy, discourse analysis, and sign language perceptions in medical education. Current research projects include politeness studies, translation, and political discourse analysis. She has presented at international conferences such as the International Pragmatics Conference and the Canadian Association of University Teachers of German. Her work bridges theoretical insights with practical applications in language education and cross-cultural communication.