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اطلاعات پروفایل‌ها از صفحات عمومی دانشگاه‌ها گرفته شده و ممکن است به‌روز نباشد.

Stefania Benettiمشاهده پروفایل

مربی

University of TrentoItaly

Stefania Benetti serves as a Research collaborator at the Interdepartmental Center for Mind/Brain Sciences (CIMEC) and holds a Tutor position in the Department of Psychology and Cognitive Sciences at the University of Trento. Her work bridges cognitive neuroscience, psycholinguistics, and sensory processing research, with particular emphasis on understanding brain reorganization mechanisms following sensory deprivation. Dr. Benetti's research expertise spans cognitive neuroscience with specialization in multisensory perception , particularly examining how visual and auditory information integrate during social interactions. Her groundbreaking work on brain plasticity investigates cross-modal adaptations in deaf individuals, demonstrating how visual processing recruits brain regions typically dedicated to auditory functions. Through advanced neuroimaging techniques including fMRI, MEG, and diffusion-based tractography, she explores face and voice processing mechanisms, neural decoding approaches, and structural connectivity underlying cognitive functions. Her technical skills encompass multivariate pattern analysis, brain connectivity mapping, and neural decoding methodologies applied to fundamental questions about perception and cognition. Analysis of Dr. Benetti's publication record reveals a clear research trajectory focused on sensory processing and brain adaptation. Her recent work demonstrates how prior expectations shape multisensory integration during face-to-face communication (2025), while her ongoing investigations into cross-modal plasticity show how early deafness leads to functional reorganization where visual stimuli recruit temporal regions typically dedicated to voice processing. This research bridges psycholinguistics and sensory neuroscience, revealing fundamental principles about brain organization and adaptation that have implications for understanding neurodevelopmental processes and potential rehabilitation strategies.

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Jeff Orchardمشاهده پروفایل

دانشیار

University of WaterlooCanada

Jeff Orchard is an Associate Professor at the Cheriton School of Computer Science , University of Waterloo , with cross-appointments to the Department of Applied Mathematics and Department of Education . He directs the Neurocognitive Computing Lab and is a core member of the Centre for Theoretical Neuroscience . In 2022, he completed a 6-month sabbatical at the International Centre for Neuromorphic Systems (Western Sydney University). Education: PhD in Computing Science, Simon Fraser University (2003) MSc in Applied Mathematics, University of British Columbia (1996) BMath in Applied Mathematics, University of Waterloo (1994) Dr. Orchard's research focuses on understanding the brain through computational and mathematical modeling, particularly through neural networks , predictive coding , and vector symbolic architectures . His work bridges neuroscience , machine learning , and neuromorphic engineering , seeking mechanistic rules governing cognition and behavior. Earlier research involved medical image processing , including MRI motion compensation , image denoising , and retinal vessel segmentation . Recent publications (2022-2025) highlight his exploration of biologically-plausible learning algorithms , neuromorphic computing , and AI alignment through active inference models. His work on predictive coding networks and hyperdimensional computing demonstrates interdisciplinary innovation across computer science , mathematics , and cognitive neuroscience .

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Todd Lewisمشاهده پروفایل

مدرس ارشد

University of the West of EnglandUnited Kingdom

Dr Todd Lewis serves as a Senior Lecturer in Ecology within the Department of Geography and Environmental Management at the University of the West of England (UWE Bristol), teaching across ecology, biogeography, conservation, and environmental science themes with practical field experience integrated into his instruction. His academic qualifications are: BSc in Environmental Biology from University of London Wye College PhD from University of Surrey investigating environmental influences on amphibian populations in Central American tropical forests PGCHE (Postgraduate Certificate in Higher Education) Dr Lewis specializes in ecological statistics and population analysis using frequentist and Bayesian frameworks, with core research spanning: Tropical herpetofauna biogeography and conservation Animal behaviour in natural and captive settings Human perceptions of ecological issues Climate change impacts on amphibian population dynamics Species distribution modelling applications Community ecology dynamics His profile highlights collaborative research with colleagues, students, and independent researchers but provides no specific details on advising history, grant funding, scientific awards, or laboratory facilities.

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Luciano Serafiniمشاهده پروفایل

پژوهشگر

University of TrierGermany

Luciano Serafini is a researcher at Fondazione Bruno Kessler in Trento, Italy, specializing in Artificial Intelligence with a focus on Neuro-Symbolic Integration and Knowledge Graphs . His work bridges Machine Learning and Symbolic Reasoning , emphasizing Planning , Relational Learning , and Visual-Textual Grounding . Key Research Areas : Neuro-symbolic systems, logic-based knowledge representation, planning under uncertainty, and computer vision. Recent Publications highlight trends in Embodied AI for open-world tasks, Weighted Model Counting , and Graph Generative Models . His contributions include Logic Tensor Networks for integrating deep learning with formal logic and methods to mitigate Data Sparsity through knowledge transfer. Collaborations span institutions like the University of Trento and research teams in Computer Vision and Reasoning , with applications in Social Navigation and Event Recognition .

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Paola Ferrettiمشاهده پروفایل

دانشیار

Ca' Foscari University of VeniceItaly

Paola Ferretti is an Associate Professor at the Department of Economics, Ca' Foscari University of Venice. Her research focuses on Mathematical Methods in Economics, Actuarial Sciences, and Finance , with specific expertise in Decision Theory, Stochastic Orderings, and Insurance modeling. She serves as the Department Delegate for Teacher Training and contributes to editorial boards like Mathematical Methods in Economics and Finance . Teaching: Courses in Mathematics for Economics, Optimization, Risk Theory, and Decision Theory at undergraduate, graduate, and PhD levels Research Grants: Funded by MIUR (PRIN 2007) and Dipartimento di Management (2011) Collaborations: Works with Andrea Ellero, Giovanni Fasano, Daniela Favaretto, and Raluca Elena Buia Her publications analyze sustainability dimensions, Bayesian confirmation measures, and reinsurance contracts using mathematical frameworks. She applies Data Mining techniques to tourist demand forecasting and studies risk attitudes in multi-period contexts. Key conferences organized include MAF 2008/2012/2016 (Mathematical Finance), RUD 2001 (Risk Uncertainty Decision), and EURO Working Group 1997 (Financial Modeling).

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Timothy R Johnsonمشاهده پروفایل

استاد

University of IdahoUnited States

Timothy R Johnson is a Professor and Department Chair of Mathematics and Statistical Science at the University of Idaho's College of Science. His work bridges statistical methodology with ecological applications, focusing on Bayesian statistics, simulation-based inference, categorical/ranking data analysis, and statistical disclosure control. PhD in Quantitative Psychology (2001) from University of Illinois at Urbana-Champaign MS in Statistics (1999) from University of Illinois at Urbana-Champaign MS (1994) and BA (1993) in Psychology from Western Washington University His research spans wildlife ecology, physiological monitoring, and statistical modeling. Key themes include habitat selection, risk perception in foraging behavior, energy expenditure estimation, and ecological survey methodology. Publications demonstrate expertise in mixed-effects models, tetrad analysis, and noninvasive genetic sampling. Recent articles focus on animal monitoring techniques, conservation biology, and statistical methods for ranking data. His statistical innovations often address practical challenges in ecological research, such as DNA degradation rates, thermal refuge mapping, and field data calibration. As Department Chair, he oversees academic programs combining mathematics and statistical science. His interdisciplinary work connects statistical theory with real-world conservation applications across diverse ecosystems.

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James A. Waltzمشاهده پروفایل

دانشیار

University of Maryland, BaltimoreUnited States

James A. Waltz, PhD , is Associate Professor in the Department of Psychiatry at the University of Maryland School of Medicine and Principal Investigator of the IDRIS lab at the Maryland Psychiatric Research Center (MPRC) in Catonsville, Maryland. His federally-funded program uses behavioral experiments, functional neuroimaging, and computational modeling to understand how disturbances in reinforcement learning and reward processing give rise to the motivational and cognitive deficits observed in schizophrenia. Education & Training BA, Psychology (Cognitive Science), Yale University (1994) MA, Psychology (Cognitive Neuroscience), University of California, Los Angeles (1995) PhD, Psychology (Cognitive Neuroscience), UCLA (1999) Post-doctoral Fellow, Neurophysiology Department, Max Planck Institute for Brain Research, Frankfurt, Germany (1999–2004) Post-doctoral Fellow, Maryland Psychiatric Research Center (2004–2006) Research Interests Dr. Waltz’s work centers on the neural and computational mechanisms of reinforcement learning and decision-making , with a translational focus on schizophrenia . His lab combines functional MRI, EEG, eye-tracking, and computational modeling to dissect how abnormalities in dopaminergic reward circuits—particularly fronto-striatal networks—contribute to anhedonia , avolition , and other negative symptoms of psychotic illness. Current projects examine (1) altered reward-prediction-error signaling in striatal and cortical regions; (2) effort-cost computations and motivational impairment; and (3) cognitive flexibility deficits and their relationship to delusions and hallucinations. Ongoing clinical protocols recruit first-degree relatives, patients with schizophrenia/schizoaffective disorder, and healthy volunteers to probe the impact of stress, genetics, and antipsychotic medications on reward processing and learning. Scientific Awards & Honors National Research Service Award, NIH (1998–1999) Joseph A. Gingerelli Award for Distinguished Dissertation, UCLA (1999) H. McKee Jarboe Award for Outstanding Research in Psychiatry, UMSOM (2009) Young Investigator Mentor, International Congress on Schizophrenia Research (2013) Funding & Collaborations Dr. Waltz’s research is supported by an NIH R01 grant (R01MH094460) and is conducted in close collaboration with the Gold CANS Lab at MPRC, the Neuroimaging Research Branch at NIDA (Dr. Elliot Stein), and the Section of Human Neurogenetics at NIAAA (Dr. David Goldman). The IDRIS lab is embedded within MPRC’s Center for Brain Imaging Research (CBIR) , which houses a 3-Tesla Siemens Trio MRI scanner, 64-channel EEG suites, and eye-tracking facilities. Advising & Team The laboratory trains a continuum of researchers, from undergraduate volunteers through post-doctoral fellows. Current trainees include Adam J. Culbreth, PhD (Assistant Professor), Jacob Nudelman, BS (Senior Clinical Research Assistant), Elie Holzel, BA, and Safa Riaz, BA. Lab alumni have progressed to faculty positions at Charité Medical University, Maastricht University, KU Leuven, and Northwestern University.

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Daniel Senkowskiمشاهده پروفایل

استاد

Charité - Universitätsmedizin BerlinGermany

Professor Daniel Senkowski serves as Head of the research division Computational Neuroimaging and leads the Multisensory Integration Research Group at the Department of Psychiatry and Neurosciences, Charité – Universitätsmedizin Berlin. His work bridges clinical neuropsychology with advanced neuroimaging techniques to investigate fundamental neural mechanisms underlying human cognition and perception. Dr. Senkowski's primary research focus centers on multisensory integration processes, particularly examining how neural oscillations across multiple time scales contribute to information processing in both healthy individuals and clinical populations, especially those with schizophrenia and ADHD. His laboratory employs sophisticated methodologies including transcranial alternating current stimulation, eye tracking, computational modeling, and electroencephalography to unravel the complex dynamics of sensory integration. Analysis of his recent publications reveals a strong emphasis on neural oscillatory mechanisms, particularly gamma and beta band activity, in mediating multisensory processing. His 2024 Nature Reviews Neuroscience article on multi-timescale neural dynamics represents a significant theoretical contribution to understanding how the brain integrates information across different sensory modalities through oscillatory synchronization. His research group actively investigates cognitive deficits in schizophrenia, with particular attention to attention deficits, working memory impairments, and multisensory processing abnormalities. The team has produced numerous high-impact studies examining how oscillatory brain activity relates to perceptual and cognitive functions in both healthy and clinical populations.

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CHANG-YA HUمشاهده پروفایل

استاد

National Chengchi UniversityTaiwan

CHANG-YA HU is a Professor at the Department of Business Administration , National ChengChi University , with a focus on Organizational Behavior , Leadership and Motivation , and Human Resource Management . His expertise extends to Measurement Methodology , Employee Satisfaction Survey , and Organizational Climate Survey . Education : Ph.D. in Industrial/Organizational Psychology from the University of Georgia (2003), M.A. in Psychology from National ChengChi University (1997), and B.A. in Psychology from National Taiwan University (1995). Research Interests : Central to his research are mentoring dynamics, leadership styles, and workplace psychological phenomena. He has extensively studied abusive supervision , career plateaus , and cross-cultural measurement equivalence . Recent Publications highlight his work on mentoring relationships, emotional blackmail scales, and political contexts in leadership. These contributions span high-impact journals like Journal of Vocational Behavior and Asia Pacific Journal of Management , reflecting interdisciplinary engagement across organizational psychology and cross-cultural studies. Scientific Awards : Recipient of multiple accolades including the 13年度管理學報最佳審查人獎 , 國科會研究獎勵 , and 資深優良教師(20年) from National ChengChi University. Grants & Projects : Principal Investigator for 15+ National Science and Technology Council projects (2007–2027) examining mentoring, organizational climate, and ethical leadership, including generative AI applications in workplace well-being.

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Alberto José Bugarín Dizمشاهده پروفایل

استاد

University of Santiago de CompostelaSpain

Alberto José Bugarín Diz is a Full Professor of Artificial Intelligence at the University of Santiago de Compostela (USC), where he serves as coordinator of the Intelligent Systems Group (GSI), founded in 1990 and recognized as a competitive reference group by the Xunta de Galicia since 2006. He previously served as Deputy Director of the School of Engineering of the University of Santiago de Compostela (ETSE) and currently acts as the USC coordinator of the Degree in Artificial Intelligence taught across the three universities in Galicia. His research focuses on various areas of artificial intelligence and its applications, including natural language generation (Data-To-Text systems), soft computing, automatic learning, and approximate knowledge and reasoning representation. He has co-authored nearly 230 scientific papers and participated in over 63 R&D projects and innovation contracts, serving as principal researcher in 25 of them. His work spans healthcare applications, manufacturing processes, conversational agents, and linguistic descriptions of data, with particular emphasis on making AI systems more transparent and understandable to users. Prof. Bugarín Diz is actively involved in the AI community, currently serving as a Board Member of the Spanish Society for Artificial Intelligence (AEPIA), Secretary of the Spanish Society for Natural Language Processing (SEPLN), and as a member of the Organizing Committee of the 27th European Conference on Artificial Intelligence (ECAI), which took place in Santiago de Compostela in October 2024. He also participates in the TELSEC4TAI network about 'Trustworthy AI: technical, ethical, legal, cultural and socio-economic challenges.' His recent publications reveal a strong focus on explainable AI, trustworthy systems, and the application of fuzzy logic to complex reasoning problems, particularly in medical diagnosis, automotive manufacturing, and conversational systems. His work consistently bridges theoretical AI concepts with practical applications that address real-world challenges in healthcare, industry, and human-computer interaction. Board Member, Spanish Society for Artificial Intelligence (AEPIA) Secretary, Spanish Society for Natural Language Processing (SEPLN) Organizing Committee Member, 27th European Conference on Artificial Intelligence (ECAI 2024) Coordinator, Intelligent Systems Group (GSI) USC Coordinator, Degree in Artificial Intelligence (Galicia)

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Jean-Luc Schwartzمشاهده پروفایل

استاد پژوهش

Grenoble Alps UniversityFrance

Jean-Luc Schwartz is a Research Director at the CNRS (Centre National de la Recherche Scientifique) affiliated with Grenoble Alpes University. He formerly directed the Institut de la Communication Parlée (ICP) from 2003 to 2006 and currently directs the Grenoble Cognition Cluster. He serves as Principal Investigator for the ERC Advanced Grant project "Speech Unit(e)s - The multisensory-motor unity of speech" and participated in establishing the Carnot Cognition Institute as a "Tremplin" in the Carnot 3 call. His research centers on perceptual processing, audiovisual speech perception, and the phonetic foundations of phonological systems, utilizing Bayesian robotics frameworks and mirror system hypothesis investigations. Work spans cognitive psychology (Cognition, Perception & Psychophysics), neuroscience (Neuroimage, Human Brain Mapping), signal processing (IEEE Transactions), and computational linguistics (Journal of Phonetics), examining how low-level speech units interact with general cognitive principles. Dr. Schwartz has coordinated special journal issues for Speech Communication and Philosophical Transactions of the Royal Society B, while organizing international workshops on audiovisual speech and language emergence. His scientific recognition includes the prestigious ERC Advanced Grant award: ERC Advanced Grant for "Speech Unit(e)s" project He actively shapes Grenoble's research infrastructure through the Grenoble Cognition Hub and IDEX NeuroCoG project, fostering interdisciplinary collaboration across psychology, neuroscience, linguistics, and computer science for cognitive research advancement.

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Jennifer M. Grohمشاهده پروفایل

استاد

Duke UniversityUnited States

Jennifer M. Groh is a Professor at Duke University with appointments in Psychology and Neuroscience, Neurobiology, Biomedical Engineering, and Computer Science . She is a Faculty Network Member of the Duke Institute for Brain Sciences and a Center for Cognitive Neuroscience member. Ph.D. in Neuroscience, University of Pennsylvania (1993) M.S. in Psychology, University of Michigan, Ann Arbor (1989) Her research explores sensorimotor integration , particularly how vision and hearing interact to create embodied cognition . Key findings include demonstrating that eye position alters auditory pathway responses , challenging traditional views of sensory processing. Recent publications focus on eardrum oscillations , neural multiplexing , and cross-modal signal interactions . Awards include the Guggenheim Fellowship and Sloan Research Fellowship . Current grants investigate neural coding mechanisms and multisensory processes in hearing . Her lab examines auditory cortex dynamics , inferior colliculus function , and visual-auditory signal coordination through experimental and computational approaches.

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Shangfei Wangمشاهده پروفایل

استاد

University of Science and Technology of ChinaChina

Shangfei Wang is a full Professor at the School of Computer Science and Technology, University of Science and Technology of China (USTC). His research focuses on pattern recognition, affective computing, and probabilistic graphical models, with significant contributions to facial expression analysis, emotion recognition, and multimodal human-robot interaction. He leads the Key Laboratory of Computing and Communication Software of Anhui Province and has received multiple international competition awards including placements in the OMG Empathy Prediction Challenge and Detecting Depression with AI Sub-Challenge. PhD in Computer Science, USTC (2002) MSc in Electronic Science and Technology, USTC (1999) BSc in Electronic Engineering, Anhui University (1996) His work combines domain knowledge with advanced machine learning techniques, including adversarial learning, dual learning, and multimodal deep regression Bayesian networks. Research themes include: Emotion-aware medical consultation systems Thermal image-based facial recognition Privileged information learning for emotion detection Spontaneous vs. posed expression differentiation EEG and physiological signal integration AI applications in mental health support Key projects include multiple National Nature Science Foundation of China grants and international collaborations with French institutions. He serves as Associate Editor for IEEE Trans. on Affective Computing and ACM Trans. on Multimedia Computing, and organized several international conference tracks.

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Vikranth Rao Bejjankiمشاهده پروفایل

دانشیار

Hamilton CollegeUnited States

Vikranth Rao Bejjanki is an Associate Professor of Psychology at Hamilton College. His research focuses on the neural and computational mechanisms underlying human learning, employing methods such as psychophysics, computational modeling, and functional neuroimaging. He is affiliated with the Princeton Neuroscience Institute as a former postdoctoral researcher and maintains memberships in the Society for Neuroscience, Vision Sciences Society, Sigma Xi Scientific Honor Society, and the American Association for the Advancement of Science. Ph.D. in Brain and Cognitive Sciences, University of Rochester M.A. in Brain and Cognitive Sciences, University of Rochester B.A. in Cognitive Science, State University of New York at Buffalo B.S. in Computer Engineering, State University of New York at Buffalo Bejjanki’s research explores how humans learn from experiences through probabilistic inference, cue integration, and neural plasticity. His work bridges experimental psychology with computational models to understand visual perception, spatial localization, and the impact of video game training on cognitive adaptability. He has contributed to journals like Nature Neuroscience , Proceedings of the National Academy of Sciences , and PLoS Computational Biology , often integrating neuroimaging and behavioral analysis to decode learning mechanisms. His publications highlight interdisciplinary themes, merging neuroscience with artificial intelligence, cognitive modeling, and sensory processing. Key trends include the role of noise correlations in brain pattern classification, the development of perceptual templates through video games, and the application of Bayesian inference to spatial tasks. Scientific Awards & Affiliations: Sigma Xi Scientific Honor Society Society for Neuroscience Vision Sciences Society American Association for the Advancement of Science Bejjanki has taught courses such as Fundamentals of Human Neuroscience and Psychology and Neuroscience of Learning , reflecting his expertise in cognitive systems and neural mechanisms of learning. While his student advising record is not explicitly detailed, his collaborative research with institutions like Princeton underscores his commitment to advancing neuroscience through both theoretical and empirical approaches.

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Timothy D Johnsonمشاهده پروفایل

استاد

University of Michigan-Ann ArborUnited States

Timothy D Johnson is a Professor in the Biostatistics department at the University of Michigan School of Public Health . His research focuses on Bayesian statistical methods, neuroimaging analysis, and biomedical data modeling. Education: PhD, University of California, Los Angeles (1997) MS, University of California, Riverside (1986) BS, University of California, Riverside (1984) Research Interests: Dr. Johnson develops advanced Bayesian methodologies for high-dimensional biomedical data, particularly in neuroimaging applications. His work addresses challenges in spatial statistics, mixture models, and variable parameter spaces, with applications spanning neuroscience, cancer, endocrinology, and radiology. Publications Trends: His recent work emphasizes scalable Bayesian frameworks for neuroimaging, applications of stimulated Raman histology in oncology, and statistical solutions for clinical radiology. Many articles focus on improving diagnostic accuracy in gliomas and understanding social cognition through neuroimaging.

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