جست‌وجوی استاد و پژوهشگر

Aniruddh Patelمشاهده پروفایل

استاد

• Music Cognition
• Music-Language Relations
• Rhythmic Processing
• +۱ مورد دیگر

Dr. Aniruddh Patel is Professor of Psychology at Tufts University's School of Arts and Sciences. His pioneering research program in music cognition examines the mental processes underlying music perception and production, with emphasis on music-language relationships, rhythmic processing, and cross-species studies. He employs diverse methodologies including brain imaging, behavioral experiments, and comparative research with nonhuman animals. Education includes a PhD in Organismic and Evolutionary Biology from Harvard University. Dr. Patel previously served as Senior Fellow at The Neurosciences Institute (2005-2012) and President of the Society for Music Perception and Cognition (2009-2011). He is currently Fellow in the Azrieli Brain, Mind, and Consciousness program at the Canadian Institute for Advanced Research. His research output focuses on evolutionary foundations of rhythm perception, cross-species comparisons of musicality, and neural mechanisms underlying auditory illusions and predictive processing, with recent expansion into clinical applications for neurodevelopmental disorders. Fellow, Azrieli Brain, Mind, and Consciousness Program (CIFAR)

• Reading
• Language Processing
• Dyslexia
• +۳ مورد دیگر

Manon Jones is a Professor in Psychology and Director of Research at Bangor University's School of Psychology and Sport Science. She directs the Miles Dyslexia Centre, a research hub providing assessment services and professional development for practitioners, and leads the RILL project—a bilingual literacy program for primary schools funded by UKRI, Nuffield Foundation, and Welsh Government. Her research explores cognitive and neurocognitive foundations of reading, dyslexia, and bilingualism. Key themes include: Cross-modal learning in dyslexia Orthographic processing across languages Remote literacy instruction efficacy Neurodivergent cognition models Syntax acquisition in bilinguals Analysis of her 15 most recent publications (2014–2025) reveals dominant foci on dyslexia mechanisms (9 papers), bilingual language processing (7 papers), and literacy intervention design (4 papers). Methodologies include eye-tracking, ERP, and randomized controlled trials, with increasing emphasis on computational modeling since 2021. She leads multiple grants including: RILL randomized control trial (Welsh Government, 2022–2026) Welsh literacy scale-up project (2024–2025) Neurodevelopmental disorder screening tool development (2022–2023) COVID-19 remote teaching research (2020–2022) She directs the Reading Brain lab and collaborates with NHS services to translate research into clinical/educational practice.

Jianxi Gaoمشاهده پروفایل

دانشیار

• Network Science
• Artificial Intelligence
• Control Theory
• +۳ مورد دیگر

Jianxi Gao is an Associate Professor in the Department of Computer Science at Rensselaer Polytechnic Institute (RPI). His research focuses on network science, particularly network resilience, robustness, and control, integrating network theory, control theory, statistical physics, and operations research. He also explores the intersection of network science and AI, including applications of AI to network analysis and vice versa. His work aims to understand, predict, and control the resilience of complex systems against cascading failures. Key research areas include network resilience in transportation systems, quantum networks, and biological systems, with applications to pandemic response and infrastructure optimization. Gao's contributions span theoretical frameworks and computational tools, such as the NuRsE MATLAB package for network resilience analysis. His GitHub repositories (e.g., NuRsE and NON) showcase his open-source contributions to network science and computational methods. His recent publications address topics like AI-driven network analysis, quantum network percolation, and pandemic-induced healthcare system stress. He actively collaborates on interdisciplinary projects, emphasizing real-world applications of network science principles.

Ibrahim RADWANمشاهده پروفایل

دانشیار

• Machine Learning
• AI
• Computer Vision
• +۹ مورد دیگر

Ibrahim RADWAN is an Associate Professor in Machine Learning/AI and Robotics at the University of Canberra. His research focuses on advancing AI techniques in areas such as human pose estimation, affective computing, and healthcare technology. He leads projects addressing challenges in robotics, autonomous systems, and human behavior analysis. RADWAN’s work bridges theory and application, contributing to fields like sports science, medical diagnostics, and security through innovative machine learning approaches. Research Projects: Assistive Technologies for Young People Safety on Two-Wheelers AI-Based Methods for Driver Sentiment and Mood Prediction Robotics Applications in Organic Waste Management Research Interests: RADWAN’s expertise spans human pose reconstruction , nonverbal behavior analysis , and EEG-based healthcare diagnostics . He pioneers methods for real-world applications such as: 6G Extended Reality systems using wearable sensors Multimodal deception detection via motion analysis Affective computing for mood and emotion inference Publications: His recent work emphasizes trends in spatiotemporal data analysis, few-shot learning, and synthetic data applications in healthcare and robotics. Key contributions include novel architectures like CrossFormer for 3D pose estimation and Resanet for dense prediction tasks. Advising & Grants: RADWAN supervises PhD students and has secured grants for projects integrating AI with robotics and medical technology. His team collaborates on interdisciplinary challenges, including railway safety and surgical instrument tracking. Labs/Teams: Part of the AI and Robotics research group at the University of Canberra, contributing to cutting-edge solutions in autonomous systems and human-centered AI.

• Applied Mathematics
• Mathematical Biology
• Epidemiology
• +۴ مورد دیگر

Paul Tupper is a Professor in the Department of Mathematics at Simon Fraser University (SFU), part of the Faculty of Science. He holds a Ph.D. in Scientific Computing from Stanford University (2002). His research focuses on applied mathematics with emphasis on mathematical modeling in epidemiology, speech perception, neural networks, and computational linguistics. He teaches advanced courses in probability, numerical linear algebra, and calculus for social sciences. His work bridges theoretical mathematics and real-world applications, particularly in understanding complex systems like disease transmission dynamics and cognitive processes. Recent studies include modeling the transition of pandemics to endemic states, genomic analysis of viral spread, and audio-visual perception mechanisms in speech. He actively contributes to public health policy discussions through epidemic modeling research. Professor Tupper's research has been published in high-impact journals and conferences, with notable contributions to diversity metrics in biology and geometry, stochastic differential equations, and connectionist models of linguistic phenomena. His courses reflect interdisciplinary interests, integrating mathematical rigor with practical computational methods.

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.

David S. Marchمشاهده پروفایل

استادیار

• Social Psychology
• Implicit Cognition
• Threat Perception
• +۳ مورد دیگر

David S. March is an Assistant Professor in the Department of Psychology at Florida State University's College of Arts and Sciences. His research focuses on implicit cognition and threat processing, particularly how subconscious threat evaluation influences attitudes, prejudice, and behavioral responses. He actively recruits graduate students for Fall 2026 and oversees the March Research Laboratory. His research integrates social cognition, cognitive neuroscience, and behavioral psychology to challenge dual process models by introducing a speed-strength distinction between threatening and nonthreatening stimuli. Key areas include automacity of threat responses, racial bias mechanisms, and methodological advancements in mouse-tracking analysis. Dr. March's publications examine threat perception in contexts ranging from snake fear to police bias, contributing to understanding how implicit threat evaluations shape social behaviors and policy compliance. His work bridges evolutionary psychology with modern social issues like racial prejudice and pandemic health behaviors. Scientific Awards: Student Publication Prize by the Society for Personality and Social Psychology (2017)

• Hardware Security
• Machine Learning
• 3D IC Design
• +۴ مورد دیگر

Wafi Danesh is an Assistant Professor in the Department of Engineering Programs at SUNY New Paltz, part of the School of Science & Engineering. He holds a PhD in Electrical and Computer Engineering from the University of Missouri Kansas City (2022). Prior to academia, he served as a Senior Engineer I - Design at Microchip Technology Inc. (2022-2023). His research focuses on hardware security, leveraging machine learning for FPGA Trojan detection and secure 3D IC design. Teaching interests include System-on-Chip Design, Digital Logic Fundamentals, and Computer Architecture. Education: PhD in Electrical and Computer Engineering, University of Missouri Kansas City, 2022 Research Interests: Dr. Danesh explores cutting-edge methods to enhance hardware security, including AI-driven approaches for IoT device protection and thermal management in 3D integrated circuits. His work bridges machine learning and physical hardware vulnerabilities, emphasizing FPGA security and PUF-based solutions for wireless systems. Publications Trends: His articles span FPGA Trojan detection via NLP and unsupervised learning, thermal challenges in 3D ICs, and neuromorphic computing innovations. Recent work highlights automated security tools and multi-valued computing for energy efficiency. Awards: None explicitly listed in the provided materials. Advising & Grants: No formal advisees or grants are mentioned. His professional activities center on research and teaching.

Indratmoمشاهده پروفایل

دانشیار

• Information Visualization
• Human-Computer Interaction
• Social Computing
• +۳ مورد دیگر

Dr. Indratmo is an Associate Professor and Chair of the Department of Computer Science at MacEwan University. He holds a PhD from the University of Saskatchewan, an M.Sc. from the University of Manitoba, and a B.Eng. from Petra Christian University. His research focuses on information visualization, human-computer interaction, and social computing, with a particular emphasis on developing tools for analyzing social media data. He has contributed to projects like a visual analytical tool for sentiment analysis in Edmonton's traffic-related social media data and studies on multimedia content effectiveness in communication strategies. Indratmo teaches a range of computer science courses, emphasizing student engagement through transparent pedagogical practices. His work bridges technical innovation with social impact, aiming to enhance communication strategies for organizations through data-driven insights. He has published extensively in journals like Big Data Research and Visual Informatics , and his research spans topics from educational visualization tools to smart mirror applications and geospatial heritage systems. Outside academia, he enjoys outdoor activities in the Canadian Rockies. Notable collaborations include work on stacked bar chart efficacy, web-based course registration models, and exploratory browsing frameworks. His research portfolio demonstrates a commitment to both theoretical advancement and practical applications in computing.

Scott Moffatمشاهده پروفایل

استاد

• Spatial Cognition
• Navigation
• Cognitive Aging
• +۲ مورد دیگر

Scott Moffat is a Professor of Psychology at Georgia Institute of Technology, affiliated with the School of Psychology. He holds a Ph.D. in Psychobiology & Clinical Neuropsychology from the University of Western Ontario (1998). His research focuses on the cognitive neuroscience of aging, particularly the interplay between hormonal systems (e.g., cortisol, testosterone, insulin) and spatial cognition, navigation, and brain aging. He employs neuroimaging (fMRI/PET), behavioral assessments, and biochemical assays to study these topics. A key innovation is his use of virtual reality environments to evaluate spatial memory in older adults. Research interests emphasize stress physiology, including cortisol’s role in hippocampal atrophy and Alzheimer’s risk, testosterone’s impact on cognitive aging, and insulin’s effects on neural function. His work highlights individual differences in cognitive aging and the biological mechanisms underlying such variability. He has published extensively on spatial navigation strategies, age-related neural changes, and the application of virtual technologies for cognitive assessment. Labs/Teams: Director of the Cognitive Neuroscience of Aging Lab at Georgia Tech’s Center for Advanced Brain Imaging. His lab investigates brain-behavior relationships in aging using multimodal neuroimaging and endocrine measures.

Lynn Carol Millerمشاهده پروفایل

استاد

• Health Communication
• Virtual Environments
• Behavioral Neuroscience
• +۷ مورد دیگر

Lynn Carol Miller is a Professor of Communication at the University of Southern California’s Annenberg School for Communication and Journalism. Her research focuses on leveraging virtual environments, AI agents, and computational models to address health-related social behaviors, particularly in HIV/AIDS prevention and mental health. Funded by NIH, CDC, and DARPA (over $20M), her work integrates neuroscience, behavioral science, and technology. She pioneered interventions like SOLVE (Socially Optimized Learning in Virtual Environments) and Systematic Representative Design. Education: PhD in Personality Psychology from University of Texas at Austin. Key areas include health communication, gaming for behavior change, and computational modeling of social processes. She has supervised 17 doctoral students and collaborators across universities globally. Research emphasizes scalable interventions using fMRI-compatible tools and virtual reality. Notable contributions include reducing shame in HIV prevention games and analyzing neural correlates of risk-taking behaviors. Awards include the Early Career Award (2003) and ICA’s Outstanding Contribution to Communication Science (2020). Labs/Teams: Active in multidisciplinary teams at USC and collaborating institutions, focusing on virtual environment design, AI-driven interventions, and neurobehavioral studies. Current projects explore AI for public health and inclusive avatar representations in social VR.

Taylor Johnsonمشاهده پروفایل

دانشیار

• Formal Verification
• Cyber-Physical Systems (CPS)
• Artificial Intelligence
• +۷ مورد دیگر

Taylor Johnson is an Associate Professor of Computer Science and Electrical and Computer Engineering at Vanderbilt University's School of Engineering. He directs the Verification and Validation for Intelligent and Trustworthy Autonomy Laboratory (VeriVITAL) and serves as a Senior Research Scientist in the Institute for Software Integrated Systems. Previously, he was an Assistant Professor at the University of Texas at Arlington from 2013 to 2016. His research focuses on formal verification techniques for cyber-physical systems (CPS), emphasizing safety, reliability, and security through hybrid systems, formal methods, and control theory. He has published extensively on neural network verification, earning best paper awards and recognition from IEEE, IFIP, and ACM. Education: Ph.D., Electrical and Computer Engineering (University of Illinois at Urbana-Champaign, 2013) M.Sc., Electrical and Computer Engineering (University of Illinois at Urbana-Champaign, 2010) B.S.E.E., Electrical and Computer Engineering (Rice University, 2008) Research Interests: Formal verification of neural networks and CPS, safety-critical systems, autonomous systems, and AI/ML security. His work bridges theoretical foundations (e.g., hybrid systems) with practical applications in aerospace, energy systems, and robotics. Key Contributions: Developed the NNV tool for neural network verification, led the Verification of Neural Networks Competition (VNN-COMP), and pioneered techniques for robust federated learning and malware detection. Awards: AFOSR YIP Award (2016), NSF CRII Award (2015), and multiple best paper honors. His research is funded by AFRL, NSF, Intel, NVIDIA, and industry partners. Labs & Collaborations: VeriVITAL Lab (Vanderbilt), collaborations with United Technologies Research Center, Boeing, and Toyota.

Bart Bonikowskiمشاهده پروفایل

دانشیار

• Politics
• Culture
• Nationalism
• +۶ مورد دیگر

Bart Bonikowski is an Associate Professor of Sociology and Politics at New York University, serving as Director of Graduate Studies in the Department of Sociology. He is affiliated with NYU’s Center for Data Science and leads initiatives such as the Political Polarization and Radicalization Working Group at the Institute for Public Knowledge. His research integrates cultural sociology with computational methods to study nationalism, populism, and automation’s political impacts in the U.S. and Europe. Education: Ph.D., Sociology, Princeton University (2011) M.A., Sociology, Princeton University (2008) M.A., Sociology, Duke University (2005) B.A., Sociology, Queen’s University (Canada, 2003) Research Interests: Bonikowski’s work focuses on nationalism, populism, radical-right politics, and the sociopolitical implications of technological change. He employs relational surveys, experiments, and computational text analysis to explore topics like AI-driven job displacement, anti-immigrant attitudes, and ideological polarization. Recent research bridges AI governance with globalization studies. Articles Trends: His 2020s publications emphasize automation’s electoral consequences, AI policy dynamics, and the intersection of geopolitics with anti-immigrant sentiment. Earlier work established frameworks for measuring populism and nationalism in political discourse. Awards: 2023–present: Fellow, Canadian Institute for Advanced Research’s Boundaries, Membership, and Belonging Program Advising & Grants: While specific student advisees are not listed, Bonikowski directs NYU’s Sociology graduate program and collaborates on projects funded by research initiatives like CIFAR. He edits Sociological Science and contributes to editorial boards of top journals. Labs/Teams: Co-organizes NYU’s Identities & Ideologies Project and participates in the Sociology of Culture Workshop. His working groups at the Institute for Public Knowledge address radicalization and polarization.

Jia Wuمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Data Mining
• Deep Learning
• +۷ مورد دیگر

Dr. Jia Wu is an Associate Professor and Research Director of the Centre for Applied Artificial Intelligence at Macquarie University. He holds a PhD in Computer Science from the University of Technology Sydney (2009) and is an IEEE Senior Member. His research focuses on artificial intelligence, data mining, graph neural networks, and anomaly detection, with over 200 publications in top-tier journals/conferences like IEEE TPAMI, TKDE, and conferences like KDD, IJCAI, and NeurIPS. He has received awards including the Heidelberg Laureate Forum Fellowship (2019) and multiple best paper awards. Education: PhD in Computer Science (UTS, 2009). Current roles include Director of HDR (Higher Degree Research) and Associate Editor for IEEE TNNLS and ACM TKDD. He leads projects in AI-driven cybersecurity, personalized banking solutions, and disaster response systems. Research interests emphasize graph-based learning, fake news detection, and deep learning applications. His recent work explores hypergraph neural networks for fraud detection and brain graph analysis for neurological disorders. He has pioneered scalable semi-supervised clustering techniques and transformer-based hypergraph models for anomaly detection. Awards include CIKM'22 Best Paper Runner-Up, ICDM'21 Best Student Paper, and the 2023 Faculty of Science and Engineering Collaboration Award. His work spans 13 active research projects, including mitigating AI deepfakes in identity systems and enhancing disaster response networks through graph-based simulations. Labs/Teams: Leads teams in the Data Horizons Research Centre, Future Communications Research Centre, and Hearing Research Centre. Collaborates internationally in AI, data mining, and social network analysis.

Jiaxiang Zhangمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Cognitive Neuroscience
• +۲ مورد دیگر

Jiaxiang Zhang is Professor of Artificial Intelligence in the Department of Computer Science at Swansea University's Faculty of Science and Engineering. He holds a PhD in Computational Neuroscience from the University of Bristol and previously held positions at the University of Birmingham, MRC Cognition and Brain Sciences Unit (Cambridge), and Cardiff University where he founded the Cognition and Computational Brain Lab. Zhang's research integrates computational modeling, machine learning, brain imaging (MEG/EEG/fMRI), and experimental approaches to study human cognition, aging, and neurological disorders. Key focus areas include: Neural mechanisms of decision-making and problem-solving Computational models of cognitive processes AI applications in healthcare diagnostics and neuroimaging Brain network dynamics in neurological conditions Recent publications emphasize deep learning models for neural data, multimodal brain connectivity, decision-making impairments in Parkinson's disease, and neuroinformatics tools. His work shows strong clinical translation through epilepsy biomarker development and emergency department outcome prediction. Zhang has led research grants from ERC, MRC, BBSRC, and Wellcome Trust. As primary investigator for multiple projects, he oversees significant computational neuroscience initiatives. He is available for postgraduate supervision.