جست‌وجوی استاد و پژوهشگر

• Music Performance Research
• Jazz Studies
• Popular Music Analysis
• +۳ مورد دیگر

Rafael Jerjen is a Professor at the Institute of Jazz and Folk Music within the Lucerne School of Music (HSLU). His research focuses on musical groove, music psychology, and applied performance studies. He is affiliated with the CC Music Performance Research (MPR) group and leads projects exploring the impact of music on movement disorders like Parkinson's disease, as well as virtual walking and rhythmic analysis in popular music. Key roles: Professor of Jazz Contrabass and Jazz Ensemble Course Research projects: 'The Groovy Drum Beat', 'Musical Strukturanalyse als Data Mining', 'PrüfungsApp' His work bridges experimental psychology and musicology, contributing to understanding how rhythmic patterns influence human behavior. Recent publications analyze groove perception mechanisms and validate psychological models of musical engagement. Notable collaborations include studies on drum pattern complexity measures and the development of a Groove Experience Questionnaire. His research extends to corpus-based analysis of popular music and interdisciplinary studies on music's role in movement disorders.

Adham Atyabiمشاهده پروفایل

استادیار

• Cognitive & Computational Neuroscience
• Autism Biomarker Discovery
• Electroencephalogram (EEG)
• +۷ مورد دیگر

Adham Atyabi is an Assistant Professor in the Department of Computer Science at the University of Colorado Colorado Springs (UCCS). He holds a B.Sc. from Azad University (Iran), an M.Sc. in Swarm Robotics from Multimedia University (Malaysia), and a Ph.D. in Cognitive and Computational Neuroscience from Flinders University (Australia). His postdoctoral research spanned multi-swarm robotics systems at the University of Salford (UK), autism biomarker research at Yale University and Seattle Children’s Research Institute (SCRI), and computational neuroscience in BCI and EEG analysis. Key research areas include cognitive neuroscience, autism biomarkers, EEG/fNIRS analysis, BCI systems, eye-tracking, machine learning, and swarm robotics. His work intersects neuroengineering, computational intelligence, and clinical applications, particularly in autism diagnostics and rehabilitation technologies. He has contributed to multi-site studies like the Autism Biomarkers Consortium for Clinical Trials (ABC-CT), focusing on data analytics and biomarker discovery. Education: B.Sc., Azad University of Mashhad, Iran M.Sc. (Swarm Robotics), Multimedia University, Malaysia Ph.D., Cognitive and Computational Neuroscience, Flinders University, Australia Awards: No specific awards listed. Grants & Labs: Involved in ABC-CT initiatives and DAAC (Data Acquisition and Analytics Core). Active in UCCS-ICORE (Interdisciplinarity & Complexity Oriented Researchers and Educators). Future Work: Expanding BCI applications, autism biomarker validation, and interdisciplinary collaborations in neurotechnology.

• Geomatics
• Photogrammetry
• Structural Monitoring
• +۷ مورد دیگر

Alessandro Capra is a Full Professor at the University of Modena and Reggio Emilia's Department of Engineering 'Enzo Ferrari'. His research focuses on geomatics, photogrammetry, structural monitoring, and BIM/GIS applications. He leads courses in applied geomatics, BIM, and GIS for Civil and Environmental Engineering programs. Key research areas include coral reef monitoring via underwater photogrammetry, Antarctic geodynamics using GNSS networks, and cultural heritage preservation through 3D laser scanning. Capra's work integrates geodetic, remote sensing, and machine learning techniques to address environmental challenges and structural safety. Notable projects include coral bleaching impact analyses using AI, Antarctic crustal motion studies, and BIM modeling of historic structures like Modena's Cathedral and Ghirlandina Tower. His interdisciplinary approach bridges civil engineering, environmental science, and cultural heritage conservation. He has authored over 50 publications since 2010, with recent focus on marine bioconstructors, UAV-based quarry topography, and machine learning for crack detection. Teaching responsibilities include topography and advanced geomatics modules, emphasizing practical skills in BIM software and geospatial data analysis.

Joao VIEIRA DA CUNHAمشاهده پروفایل

استاد

• Management Information Systems
• Organizational Behavior
• Technology Management
• +۶ مورد دیگر

Joao VIEIRA DA CUNHA is a Full Professor and Research Director at IÉSEG School of Management, France. He holds a Ph.D. in Management from the Massachusetts Institute of Technology (MIT), USA, and has held academic positions at institutions including Universidade Europeia, University of Lisbon, and Nova School of Business and Economics in Portugal. His research focuses on Management of Information Systems, Organizational Control, Remote Work Dynamics, and Leadership in the Digital Age. He has led initiatives such as the Institute for Research and Doctoral Studies at Universidade Europeia and has served as a key academic leader in information systems management. Education 2006: Ph.D. in Management, MIT, USA 1999: Master’s in Management Sciences and Organizational Behavior, Instituto Superior de Psicologia Applicada, Portugal 1997: Bachelor’s in Business Administration, Catholic University of Portugal Research Interests His work explores the intersection of technology and organizational behavior, particularly in remote work dynamics, digital transformation, and healthcare quality standards. He has contributed theoretical frameworks such as the axis of accessibility in remote work control and the divergent model of online social movements . Recent publications analyze organizational resilience, AI in workplaces, and mindfulness practices in corporations. Grants & Advising No specific grants or advising roles are detailed in the text, though his leadership roles imply significant academic contributions to research funding and doctoral mentorship. Labs/Teams While specific labs are not mentioned, his involvement in research director roles suggests active collaboration within institutional research groups focused on information systems and organizational behavior.

Eileen Kennedyمشاهده پروفایل

استاد

• Pharmacology
• Biochemistry
• Neuroscience
• +۷ مورد دیگر

Eileen Kennedy, Ph.D., is a Georgia Athletic Association (GAA) Professor of Pharmacy and Interim Associate Department Head for Education at the University of Georgia’s College of Pharmacy, Department of Pharmaceutical and Biomedical Sciences. Her research spans drug discovery, protein kinase signaling, and innovative education technologies. She holds a leadership role in curriculum development and academic administration. Her work focuses on developing therapeutics targeting neurodegenerative diseases like Parkinson’s, malaria parasites, and cancer metastasis. She pioneers constrained peptide technologies for kinase modulation and explores educational strategies for global access, including teacher training in conflict zones through collaborative online platforms. Her publications reflect interdisciplinary expertise in biochemistry, pharmacology, and educational innovation, with recent emphasis on post-pandemic academic resilience, sustainable global collaborations, and the societal impact of digital learning. Notably, Dr. Kennedy’s research bridges molecular mechanisms (e.g., LRRK2 inhibition, WAVE3 complex disruption) with large-scale educational initiatives like CoMOOCs for refugee learners, demonstrating a commitment to both scientific advancement and equitable knowledge dissemination.

Drew Abneyمشاهده پروفایل

دانشیار

• sensorimotor development
• human interaction
• emotion regulation
• +۳ مورد دیگر

Drew Abney is an Associate Professor and Graduate Program Coordinator in the Behavioral and Brain Sciences Program at the University of Georgia's Department of Psychology. His work focuses on understanding how social interactions and sensorimotor behaviors shape developmental trajectories in infants and toddlers. He employs methods like head-mounted eye tracking, fNIRS hyper-scanning, and computational techniques to analyze behavioral and physiological dynamics. Abney leads the Developmental Dynamics Lab, which explores topics such as infant vocalization patterns, parent-child coordination, and neural synchrony. He has held postdoctoral training at Indiana University and earned his Ph.D. in Cognitive and Information Sciences from UC Merced. Abney’s research integrates dynamical systems theory with applied computational methods, emphasizing multimodal data collection (e.g., vocalizations, body movements). Recent studies include investigating maternal facilitation of joint attention, the role of physiological synchrony in infant emotion regulation, and methodological advancements in measuring respiratory sinus arrhythmia in infants. He has secured grants like the OIBR Seed Grant for developing fNIRS hyper-scanning systems to study neural dynamics in dyadic interactions. His lab currently supports graduate students Christopher Bell, Christian Jerry, and Grace Steffen in projects spanning developmental psychobiology and behavioral science. Abney emphasizes translational research, bridging fundamental developmental science with applied questions in education and clinical contexts. Though not recruiting graduate students for the 2024-25 cycle, his work continues to advance understanding of early childhood social and cognitive foundations.

Andreas Gartusمشاهده پروفایل

پژوهشگر

• Empirical Aesthetics
• Visual Perception
• Cognitive Neuroscience
• +۳ مورد دیگر

Andreas Gartus is a researcher at the Faculty of Psychology , University of Vienna , affiliated with the Department of Cognition, Emotion, and Methods in Psychology . His work focuses on empirical aesthetics, exploring how visual features like symmetry and complexity influence aesthetic experiences in art and everyday life. He is responsible for managing the Cognition Research Lab , EEG Lab Vienna , and the EVA LAB (Empirical Visual Aesthetics). His research integrates computational methods, statistical analysis, and neurophysiological techniques to study emotional responses to art, embodied cognition, and decision-making processes. Key research areas include the psychological and neural mechanisms behind aesthetic judgments, the role of context in art perception, and the application of machine learning to analyze visual stimuli. He has contributed to over 28 peer-reviewed publications since 2011, with recent work examining movement behavior in art galleries, symmetry preferences, and emotional video analysis. His activities include international conference presentations and collaborations across disciplines. His studies often address how embodied experiences (e.g., facial muscle responses, movement) interact with aesthetic evaluation, reflecting a multidisciplinary approach to understanding human perception and emotion. Despite no listed awards, his extensive publication record highlights sustained contributions to empirical aesthetic research.

Antonia Lareseمشاهده پروفایل

دانشیار

• Computational Mechanics
• Computational Fluid Dynamics (CFD)
• Fluid Structure Interaction (FSI)
• +۳ مورد دیگر

Antonia Larese is an Associate Professor in Hydraulic and Maritime Constructions and Hydrology at the University of Padova, Italy, and a Hans Fischer Fellow at the Technical University of Munich (TUM-IAS). She holds a PhD in Structural Analysis from the Technical University of Catalonia (UPC) and has extensive postdoctoral experience, including fellowships at the Spanish Ministry and the Catalonian Government. Her research focuses on Computational Mechanics, Fluid-Structure Interaction, and advanced numerical methods like the Material Point Method (MPM) and Finite Element Method (FEM). She is a core developer of the open-source KRATOS Multiphysics platform. Affiliations: University of Padova (Department of Mathematics), TUM-IAS, and the International Center for Numerical Methods in Engineering (CIMNE). Education: M.Sc. in Civil Engineering (University of Padova, 2006), M.Sc. in Numerical Methods (UPC, 2011), PhD in Structural Analysis (UPC, 2012). Research Interests: Computational Fluid Dynamics (CFD), fluid-structure interaction, unfitted numerical techniques, free surface flows, and non-Newtonian materials. Her work emphasizes innovative methods for simulating complex engineering systems, including porous media and protective structures against natural hazards. Her recent publications (2021–2024) address topics like sediment transport optimization, wind engineering applications, and coupled material point-discrete element methods. These studies highlight advancements in numerical modeling for environmental and geotechnical challenges. Awards: - Rita Levi Montalcini Fellowship (2018–2021) - Juan de la Cierva Fellowship (2017–2018) - Special Doctoral Award (UPC, 2014) - Best PhD Thesis finalist (SEMNI, 2012) Advising & Grants: She leads projects like the Digital Twins of Civil Structures (REACT) and collaborates on initiatives such as the Material Point Method (MPM) development. Her work bridges academic research with industrial applications in civil and environmental engineering. Labs/Teams: Active contributor to CIMNE’s research groups and the KRATOS Multiphysics open-source community, advancing computational tools for multiphysics problems.

Marnie Shawمشاهده پروفایل

دانشیار

• Energy Systems
• Energy Storage
• Brain Imaging (fMRI/MEG)
• +۵ مورد دیگر

Marnie Shaw is an Associate Professor and Deputy Director of the School of Engineering at the Australian National University (ANU), within the College of Science. Her research integrates engineering and social science to develop sustainable energy solutions, focusing on resilient decarbonized energy systems. She holds a PhD in Physics from the University of Melbourne and has extensive international experience in academia and industry. Affiliations: Deputy Director, School of Engineering (ANU); Researcher at the Institute for Climate, Energy & Disaster Solutions Leadership Roles: Chloe Munro Scholarship for Transformational Leadership (2023) Research interests span energy storage systems, brain imaging techniques (fMRI/MEG), and machine learning applications. Her work addresses challenges in distributed energy networks and neurodegenerative diseases. Over 40 peer-reviewed publications demonstrate contributions to both engineering and neuroscience domains. Notable projects include strategic partnerships with energy companies (Neoen) and studies on community battery systems, aiming to optimize grid performance and consumer benefits. Her interdisciplinary approach bridges technical innovation with societal impact, particularly in climate and energy policy.

John Goldsmithمشاهده پروفایل

استاد

• Computational Linguistics
• Artificial Intelligence
• Phonology
• +۳ مورد دیگر

Dr. John Goldsmith is a Professor in the Department of Computer Science at the University of Chicago, specializing in computational linguistics and artificial intelligence. His research focuses on understanding symbolic representation in natural language and genomic sequences through software development, notably the open-source Linguistica project, which automates morphological analysis in diverse languages like Somali and Swahili. He co-authored *Battle in the Mind Fields* (2019), exploring the epistemology and sociology of linguistic theory development. Goldsmith's work bridges computational models with phonological theory, including autosegmental phonology and dynamic computational networks. His contributions span morphological algorithms, unsupervised learning techniques, and the historical analysis of linguistic thought. His research interests include phonology, computational morphology, and formal language theory, with a focus on integrating big data and visualization tools. Goldsmith’s academic career spans decades, reflected in his mentorship through *The Chicago Guide to Your Academic Career* (2010), which advises scholars from graduate studies through tenure. His teaching emphasizes modern pedagogical methods, such as applying graphs and networks in linguistics education. Goldsmith’s awards and grants are not explicitly listed, but his extensive publication record and leadership in computational linguistics highlight his disciplinary impact. He collaborates across departments, linking computer science with linguistics and cognitive science. His current projects explore interdisciplinary approaches to language structure and the evolution of linguistic theories, maintaining a lab focused on computational linguistics innovations.

• Rehabilitation Engineering
• Biomechanics
• Human-Computer Interaction
• +۶ مورد دیگر

Xianta Jiang is a research-focused academic at Simon Fraser University's School of Computing Science, specializing in rehabilitation engineering and biomedical computing. With a prolific publication record spanning from 2006 to 2025, Jiang has established expertise in force myography, prosthetic control systems, and human-computer interaction for medical applications. Jiang's research interests center on biomechanics, wearable sensor technologies, and surgical training systems. Their work bridges computer vision with rehabilitation engineering, particularly in facial image processing applications for medical contexts. Recent publications demonstrate a strong focus on diffusion models and generative AI techniques applied to medical image restoration and prosthetic control. The research trajectory shows a clear evolution from fundamental biomechanics research (early work on ankle joint power estimation and gait analysis) to more complex applications involving AI-driven prosthetic control and facial image processing. The 2023-2025 publications reveal a strategic pivot toward leveraging advanced computer vision techniques for medical applications. Jiang collaborates extensively with M. Stella Atkins, Bin Zheng, and Carlo Menon, forming a core research group at Simon Fraser University focused on biomedical computing applications. This collaborative network spans multiple publications in high-impact venues including IEEE Transactions, Sensors, and Frontiers journals.

Stefan Klusمشاهده پروفایل

دانشیار

• Data-driven model reduction
• Transfer operator approximation
• Statistical learning theory
• +۷ مورد دیگر

Stefan Klus is an Associate Professor at the School of Mathematical & Computer Sciences, Department of Mathematics, Heriot-Watt University. He holds a concurrent position as a Fellow at the Free University of Berlin (2022–2026). His research focuses on data-driven model reduction, transfer operator approximation, and applications in dynamical systems, molecular dynamics, and fluid mechanics. Key interests include spectral graph theory, tensor decompositions, and high-performance computing. Klus is actively involved in advancing machine learning methodologies for analyzing complex systems and networks. His work contributes to UN Sustainable Development Goals through interdisciplinary applications in ecology and climate science. He accepts PhD students and maintains collaborations across multiple institutions, with a strong emphasis on bridging theoretical mathematics and real-world computational challenges. External Positions: Fellow, Free University of Berlin (1 July 2022 – 30 June 2026) Research Interests: Data-driven modeling and transfer operators Kernel-based learning and statistical theory Quantum mechanics and molecular dynamics simulations Spectral graph theory and network dynamics Low-rank tensor decompositions and real-time computing Recent Research Trends: Klus’s 2023–2025 articles emphasize spatiotemporal network analysis, Koopman operator applications, and optimization methods for graph problems. His work bridges abstract operator theory with practical challenges in ecology, climate modeling, and agent-based systems.

• Human-Computer Interaction
• Health Informatics
• Persuasive Technology
• +۵ مورد دیگر

Karin Kappel serves as a PostDoc Researcher in the Business Informatics department at Vienna University of Technology's Faculty of Informatics. Her research spans Human-Computer Interaction, Health Informatics, and Ethical Technology Systems with significant contributions to electronic health record design, refugee management systems, and persuasive ambient interfaces. Her research interests focus on User-Centered Healthcare Systems , Ethical Technology Deployment in Crisis Zones , and Behavioral Change through Persuasive Interfaces . Key projects include nation-wide EHR user persona development, European refugee camp registration systems, and ambient water conservation displays. Her methodological expertise combines in-the-wild mobile studies , gamified survey design , and quantitative requirement evaluation for complex socio-technical systems. Kappel's publication trends reveal three dominant research trajectories: (1) Healthcare interface design (35% of recent work), particularly EHR optimization through family-centric modeling; (2) Ethical technology systems (30%), focusing on refugee management and biometric identification; (3) Mobile interaction paradigms (25%), including text entry performance and form navigation. Her work consistently bridges technical implementation with human factors considerations. Kappel has supervised four graduate students on topics including m-banking interfaces, restaurant ordering systems, and developer onboarding tools. Current projects include a 2025-2026 hospital-based study on ML/LLM support in electronic patient records conducted with Dierks+Company Consulting GmbH.

José E. Chacónمشاهده پروفایل

استاد

• Nonparametric Statistics
• Kernel Smoothing Methods
• Density Estimation
• +۳ مورد دیگر

José E. Chacón is a Professor of Statistics in the Department of Mathematics at the University of Extremadura since 2022. Previously, he held roles at the University of Valladolid and other positions within Extremadura. His research focuses on nonparametric statistics, kernel smoothing methods for density estimation, and their applications in clustering. He is actively involved in initiatives like the NICDA Workshop and Statistics Reading Club. Education history details are not explicitly provided in the text. His research interests emphasize advanced statistical methodologies including density derivative estimation, nonparametric clustering, and applications in epidemiology and ecology. Notable contributions include work on Bayesian taut splines, mode-based symmetry estimation, and statistical modeling for animal home ranges. Recent publications (2020–2024) explore cutting-edge topics such as geodesic normal distributions, cross-validation techniques, and SIR modeling for pandemic data. His work bridges theoretical advancements with practical applications in health, ecology, and machine learning. Awards and grants are not explicitly mentioned. Chacón has advised no listed students but collaborates on interdisciplinary projects, including the special issue on Data Science for COVID-19. His research lab focuses on multivariate kernel smoothing and nonparametric methods.

• Economics
• Health Economics
• Data Science
• +۳ مورد دیگر

Kevin Li is a Postgraduate Associate in the Department of Comparative Medicine at Yale University's Yale School of Medicine. His research focuses on economics, health economics, data science, and retail strategy. He explores topics such as dynamic pricing, consumer behavior, public health implications of retail policies, and the application of advanced data analysis techniques to real-world problems like pandemic tracking and vaccine distribution. His work bridges theoretical economic models with empirical evidence from industries like airlines and retail, emphasizing the welfare effects of market strategies and organizational structures. Recent research trends include analyzing the distributional impacts of retail changes, the dynamics of crowdfunding contributions, and the use of smartphone data for understanding movement and social contact during pandemics. Li's studies often combine econometric methods with computational tools to address complex questions in market competition and public health policy. He holds no explicitly stated scientific awards but has published extensively in economics and applied data science. His academic position reflects a focus on research within the medical and scientific community at Yale.