جست‌وجوی استاد و پژوهشگر

• Exercise and Health
• Physical Activity Promotion
• Multimodal Exercise Programs
• +۳ مورد دیگر

Rui Miguel Marques Brás is an Assistant Professor at the Department of Sports Sciences, University of Beira Interior (UBI), and a researcher at the Sports, Health and Human Development Research Center (CIDESD). His academic activities include teaching courses such as Exercise and Aging , Nutrition and Food in Sports , and Biochemistry Applied to Sports . Research Focus Brás specializes in promoting exercise and physical activity, with a focus on multimodal exercise programs and the assessment of determinants in physical activity practice among young people and adults. His work intersects health sciences, exercise physiology, and public health domains. Publication Trends His recent publications (2015–2023) examine topics like ankle biomechanics, physical activity determinants, and cross-cultural health comparisons. These studies span disciplines including Sports Science , Public Health , and Health Communication , emphasizing practical applications for diverse populations. Laboratory Affiliation Brás contributes to CIDESD, a multidisciplinary research center advancing knowledge in sports sciences, health sciences, and human development through collaborative projects and innovative methodologies.

• Audio Engineering
• Room Acoustics
• Binaural Sound Reproduction
• +۷ مورد دیگر

André Siegel is a Lecturer for special tasks at the Electronic Media Technology Group, Department of Electrical Engineering and Information Technology, Technical University of Ilmenau. He is actively involved in research and teaching related to audio engineering and acoustics, with a focus on spatial sound reproduction and simulation. His research interests span Audio Engineering , Room Acoustics , Binaural Sound Reproduction , Spatial Audio , Acoustic Simulation , and Audio Signal Processing . His work emphasizes practical implementations in real environments, including crosstalk cancellation, head-related transfer function measurement, and sound field analysis. The publications reflect a consistent research trajectory from 2005 to 2013, with a concentration on spatial audio technologies, room simulation methods, and perceptual aspects of sound reproduction. Key themes include the optimization of stereo and binaural systems, low-frequency acoustic behavior, and advanced measurement techniques using vector sensors and spherical arrays. André Siegel has not been awarded any scientific prizes or fellowships mentioned in the available data. He collaborates with researchers such as Hans-Peter Schade, Stephan Werner, and Julius T. Fricke. His work contributes to both academic knowledge and practical applications in room acoustical consultancy and immersive audio systems. He is based in Helmholtz Building, Room H 3529, and can be contacted at andre.siegel@tu-ilmenau.de.

• Robot Cooperation
• Human-Robot Interaction
• People Motion Behavior
• +۵ مورد دیگر

Anaís Garrell Zulueta is an Associate Professor at the Polytechnic University of Catalonia (UPC) and a Robotics Researcher at the Institut de Robòtica i Informàtica Industrial (CSIC-UPC) . She serves as Vice-Director of the Mobile Robotics and Intelligent Systems subline and supervises the RAIG - Mobile Robotics and Artificial Intelligence Group . PhD (2013): European Doctorate with highest honors from UPC B.S. in Mathematics (2006) from University of Barcelona Diploma d'Estudis Avançats (DEA) in Control, Vision, and Robotics from UPC Her research focuses on Human-Robot Interaction (HRI) and robot cooperation , particularly in urban environments . Key themes include: Explainable AI for robot transparency Human motion behavior prediction Socially aware navigation systems Collaborative transport robotics Autonomous last-mile delivery systems Cybernetic avatars and societal implications Recent projects (2023-2025) include: TORNADO: Foundation models for robots handling deformable objects HandIA: AI-based rehabilitation tools LENA: Lifelong navigation learning TRIFFID: First responder assistance robotics SOCIAL PIA: Cybernetic avatar modeling Scientific recognition includes: Second Prize for Best Spanish Robotics Thesis Best Paper Award Nomination (IEEE/RSJ IROS, 2009) As an advisor, she supervises: PhD students: Ferran Gebelli Guinjoan, Lavinia Hriscu, Edison Bejarano Final year projects: 8 students on topics like LLM-enhanced interaction and LiDAR SLAM systems She operates within the Institut de Robòtica i Informàtica Industrial (IRI) and collaborates with Carnegie Mellon University.

Mats Küssnerمشاهده پروفایل

پژوهشگر

• Multimodal perception of music
• Music and mental imagery
• 4E music cognition
• +۳ مورد دیگر

Mats Küssner is a Researcher at Humboldt University of Berlin's Department of Musicology, specializing in Transcultural Musicology and Historical Anthropology of Music. Previously, he held a Peter Sowerby Research Associate position at the Royal College of Music in London. He earned his doctorate from King's College London, focusing on cross-modal mappings between sound and visual forms. His work bridges music psychology, cognitive science, and cultural studies, emphasizing how music shapes human thought and emotion through multi-method approaches. Research interests include multimodal perception, music-induced mental imagery, 4E cognition (embodied/embedded/enactive/extended), and performance science. Notable awards include the Aubrey Hickman Award for music psychology research and a teaching excellence award. He teaches courses like 'Diversity in Berlin's Sound Scene' and 'Emotions in Music' at both BA and MA levels. His publications span over 40 peer-reviewed articles across journals like Music & Science , Psychomusicology , and Frontiers in Psychology , with a focus on visual-aural interplay, music cognition disorders (e.g., aphantasia), and cross-cultural performance dynamics. He co-edited the landmark volume Music and Mental Imagery (Routledge, 2022). Recent work explores environmental ecomusicology education and music's role in mitigating social isolation. Küssner leads projects on music-induced emotion prediction using cross-modal correspondences and is part of Berlin's interdisciplinary music psychology scene, collaborating with neuroscientists and cultural anthropologists. His lab employs eye-tracking, EEG, and behavioral experiments to study embodied music cognition processes.

Wei-Tang Changمشاهده پروفایل

استادیار

• Neuroimaging
• Magnetic Resonance Imaging (MRI)
• Functional MRI (fMRI)
• +۴ مورد دیگر

Dr. Wei-Tang Chang is an Assistant Professor in the Department of Radiology at the University of North Carolina School of Medicine. His research focuses on advancing ultrahigh-resolution functional and diffusion MRI techniques, with emphasis on improving spatial and temporal resolution while reducing scan times. Key projects include submillimeter isotropic-resolution fMRI for hippocampal subfield analysis (funded by NIH R21), novel dMRI approaches to overcome resolution limits, and clinical translation of robust imaging methods resistant to motion/noise artifacts. Dr. Chang holds a PhD in Biomedical Engineering from National Taiwan University and completed postdoctoral training at the Martinos Center for Biomedical Imaging (MGH), Massachusetts General Hospital, and Singapore BioImaging Consortium (SBIC). His research innovations include SORDINO fMRI for awake rodent imaging, pPRISM diffusion MRI for submillimeter resolution, and ZTE pulse sequences for ultra-fast acquisitions. Awards include the 2011 OHBM Trainee Award for work on MEG source localization and fMRI temporal resolution breakthroughs. Current work bridges basic neuroimaging science with clinical applications, particularly in neurodegenerative disease biomarker development and rodent disease model studies. Education: PhD in Biomedical Engineering, National Taiwan University Postdoctoral Fellowships: Martinos Center for Biomedical Imaging (MGH) Singapore BioImaging Consortium (SBIC) Key Technologies Developed: ZTE pulse sequences (25 ms temporal resolution fMRI) pPRISM diffusion MRI (navigator-free submillimeter imaging) Draining-vein suppression layer-dependent fMRI Awards & Funding: NIH R21 Grant (2019) for hippocampal subfield fMRI OHBM Trainee Award (2011) Dr. Chang's translational focus involves adapting laboratory innovations for clinical use, with particular interest in Alzheimer's disease biomarkers through hippocampal network analysis and Huntington's disease models using rodent functional connectivity studies. His lab actively develops open-source MRI reconstruction algorithms and collaborates internationally on multi-center neuroimaging projects.

• Human-Computer Interaction
• Quality of Experience (QoE)
• User Experience (UX)
• +۷ مورد دیگر

Lieven De Marez is a Professor at Ghent University, affiliated with the Faculty of Engineering and Architecture and the Department of Information Technology. His research spans human-computer interaction, quality of experience (QoE), smart homes, digital education, and social media behavior, reflecting a strong interdisciplinary approach combining technical and social sciences. His research focuses on understanding user interactions with emerging technologies, particularly in educational, healthcare, and domestic environments. Key interests include learning analytics, privacy in social media, VR/AR experiences, and the impact of digital technologies on youth and vulnerable populations. He frequently investigates how users perceive and adapt to new systems, emphasizing user-centered design and ethical implications. The most recent publications highlight a trend toward digital well-being, algorithmic transparency in education, and the integration of AI in health and urban contexts. His work often involves mixed-method studies, longitudinal data analysis, and experimental designs to assess user acceptance, behavior, and experience. Recipient of multiple collaborative research grants (inferred from sustained publication output). Active advisor and collaborator with PhD and postdoctoral researchers (inferred from co-authorship patterns). He has contributed to major projects on mobile TV, smart cities, and digital inclusion, often in collaboration with Flemish and European institutions. His work appears in top journals such as Telematics Informatics , New Media & Society , and IEEE Transactions . Lieven De Marez leads or contributes to interdisciplinary research teams focused on interactive technologies, including work on VR prototyping, personal data stores (Solid), and ambient intelligence in public spaces. His recent involvement in projects like ExperienceDNA and Art and Science Interaction Lab underscores his leadership in experimental and user-centric research infrastructures.

Jeffrey Girardمشاهده پروفایل

استادیار

• Affective Communication
• Affective Computing
• Clinical Assessment
• +۴ مورد دیگر

Dr. Jeffrey Girard serves as Assistant Professor and M. Erik Wright Scholar in the Psychology Department at the University of Kansas, directing the Brain, Behavior & Quantitative Science Program and co-leading the Kansas Data Science Consortium. His interdisciplinary research bridges psychology, computer science, and statistics to investigate emotional expression through verbal and nonverbal behavior, with emphasis on individual differences and social contexts. Dr. Girard's educational background includes: Ph.D. in Psychology (Clinical) from the University of Pittsburgh M.S. in Psychology (Clinical) from the University of Pittsburgh B.A. in Psychology & Philosophy from the University of Washington His research centers on affective communication and affective computing , examining how emotions manifest in interpersonal interactions across clinical and non-clinical populations. Key focus areas include transdiagnostic psychiatry, multimodal behavior analysis, and the development of computational tools for clinical assessment. This work integrates statistical modeling with machine learning to address questions in interpersonal functioning and mental health diagnostics. Analysis of Dr. Girard's recent publications (2023-2025) reveals strong trends in computational psychiatry, with emphasis on multimodal datasets for emotion recognition, AI-driven clinical assessment tools, and transdiagnostic approaches to psychopathology. His work consistently bridges technical innovation in affective computing with real-world clinical applications, particularly in depression assessment and psychosis research. Scientific recognition includes: M. Erik Wright Scholar Dr. Girard actively contributes to academic service through editorial roles at IEEE Transactions on Affective Computing, Clinical Psychological Science, and other leading journals. He serves on executive boards for the Society for Interpersonal Theory and Research, Society for Affective Science, and Hierarchical Taxonomy of Psychopathology society, demonstrating leadership in advancing interdisciplinary research methodologies. He directs the Affective Communication and Computing Lab, which develops computational frameworks for analyzing emotional expression in clinical contexts, and co-leads the Kansas Data Science Consortium to foster cross-departmental data science initiatives.

• Gesture Studies
• Multimodality
• First Language Acquisition
• +۵ مورد دیگر

Maria Graziano is an Associate Professor (Docent) and Educational Developer at Lund University Humanities Lab, with additional appointments as Senior Lecturer in Italian Studies at the Centre for Languages and Literature. She is also a researcher with LAMiNATE (Language Acquisition, Multilingualism, and Teaching) and a member of LU Profile Area: Natural and Artificial Cognition. Her educational background includes a double PhD in Linguistics from SESA (European School of Advanced Studies) at the University 'Suor Orsola Benincasa' (Napoli-Italy) and Université Stendhal (Grenoble-France), following postdoctoral work at the University of Alberta, Canada. She has qualifications as Assistant Professor/Senior Lecturer in Linguistics issued by Conseil National des Universités (CNU) France (2010-2014 and 2018-2022). Graziano's research focuses on gesture and its relation to spoken language from developmental and crosslinguistic perspectives. Her work examines how gesture development relates to textual and pragmatic abilities, temporal coordination between gesture and speech in bilingual and monolingual speakers, and gesture production in relation to speech fluency. She currently compares spoken and gestural behaviors across cultures, particularly between Italian and Swedish adult speakers, and investigates cohesion in narrative discourse in Italian children. Her publication record shows a strong focus on gesture-speech relationships, with significant impact as evidenced by 78 citations for her 2018 Frontiers in Psychology article 'When speech stops, gesture stops.' Her recent 2024 article in Frontiers in Communication provides evidence for cultural differences in gesture use between Italians and Swedes. Qualified Teaching Practitioner (2025) New Society of Letters at Lund (2024) Postdoctoral Fellow Research Day - University of Alberta (2011) Third prize for poster presentation at the Postdoctoral Fellow Research Day, University of Alberta (2011) Scholarship for Short Term Scientific Mission from European Science Foundation (2009) Graziano coordinates the research platform LAMiNATE (Language Acquisition, Multilingualism and Teaching) since 2020 and previously coordinated the Language Acquisition Seminar (2017-2019). She provides BA supervision and examination at Örebro University, teaches at Kristianstad Högskola and Malmö University, and has taught Italian Studies at Lund University since 2012. She is actively involved in numerous research projects including TEAM: Transdisciplinary Approaches to Learning, Acquisition, Multilingualism (2024-2029), and previously led projects on gesture production and the expression of pragmatic meaning across languages. She is an active member of the research community with 131 recorded activities including conference participation, public lectures, invited talks, and supervisory roles. Her work demonstrates strong international collaboration, particularly with researchers in Canada, the Netherlands, and across Europe.

Lalit Jainمشاهده پروفایل

استادیار

• Machine Learning
• Data Science
• Artificial Intelligence
• +۹ مورد دیگر

Lalit Jain is an Assistant Professor at the Foster School of Business , University of Washington. His research bridges theoretical mathematics with practical machine learning systems, focusing on adaptive data collection under budget constraints, applied to marketing, cognitive psychology, and humor detection. Research Interests : Adaptive machine learning algorithms Bandit optimization and experimental design False discovery rate control Human-AI interaction Applications in marketing and cognitive science Advising : Justin Weltz (Neurips 2023) Zhaoqi (AISTATS) Romain (AISTATS) Zhihan (Amazon collaboration) Jennifer Brennan (ICML 2022 workshop) Projects : Co-developer of the New Yorker Caption Contest voting system Collaboration with Amazon on adaptive pricing systems

Lucy Wangمشاهده پروفایل

استادیار

• Artificial Intelligence
• Human-Centered Computing
• Natural Language Processing
• +۳ مورد دیگر

Lucy Lu Wang is an Assistant Professor at the University of Washington Information School and holds adjunct appointments in Biomedical Informatics & Medical Education , Human Centered Design & Engineering , and Computer Science & Engineering . She leads the LARCH lab focused on language accessibility research. Research Interests : Designing language technologies for information accessibility Reducing barriers in scientific/healthcare domains Human-AI collaboration for research translation Recent Article Trends : Focus on accessibility evaluation frameworks, generative AI customization, LLM abstention behavior, multimodal generation benchmarks, and clinical AI applications across journals like ASSETS, DIS, and TACL. Scientific Awards : Best Artifact Award, ASSETS 2021 Best Paper: Honorable Mention, CHI 2021 Advising & Grants includes Microsoft's Accelerating Foundation Models Research Award and Google's Gemma Academic Program Award . She contributes to open-access tools like FigurA11y and PaperPlain .

Octavian Mihai Machidonمشاهده پروفایل

استادیار

• Mobile Computing
• IoT-based Systems
• Smart Public Governance
• +۸ مورد دیگر

Octavian Mihai Machidon is an Assistant Professor at the Faculty of Computer and Information Science (FRI), specializing in mobile computing, IoT systems, and approximate computing. His research bridges technological innovation with diverse applications in agriculture, cultural heritage, and smart governance. Current research focuses on energy-efficient mobile systems, UAV-based agricultural monitoring, and smart governance frameworks Previously led H2020 Smart4All AgriAdapt project Recipient of multiple awards for research excellence and innovation His work demonstrates cross-disciplinary impact through projects like Mobiprox (IEEE IoT Journal) and SqueezeSlimU-Net (IEEE Journal of Selected Topics in Applied Earth Observations). Key trends include adaptive algorithms, real-time processing, and sustainable technology integration. 2024 - FRI Special Award for Exceptional Research Achievement 2023 - Agrobiznis 'Best Idea' award for AgriAdapt project As member of the Computer Communications Laboratory , he contributes to digital transformation initiatives and teaches courses in process automation and mobile sensing platform development.

• Human-Computer Interaction
• Collaborative and Social Computing
• Computer Supported Cooperative Work
• +۷ مورد دیگر

Dr. Ioanna Lykourentzou is an Associate Professor in the Software Technology for Learning and Teaching department at Utrecht University's Faculty of Science. She leads the Collaborative Technologies Lab and coordinates the Computing Science Master's and Information Sciences Honors Bachelor's programs. Additionally, she serves as a Fair Data and Software fellow within the Open Science Team of the Faculty of Science and as a member of the Ethics Review Board for the Faculties of Science and Geosciences. Her research focuses on collaborative and crowd systems, developing methods that help people work together, coordinate efforts, and innovate at scale, both online and in physical spaces. Her interdisciplinary approach combines computational science (machine learning, agent-based modeling, mathematical optimization) with social sciences (personality testing, team building). Her expertise spans Human-Computer Interaction, Algorithms, Agent-Based Modelling, Telecollaboration, Creativity, and Innovation. Her recent publications (2021-2025) demonstrate a strong focus on human-AI interaction, generative models, and applications in cultural heritage and education. She examines how technology can facilitate collaboration, with particular attention to team formation, personality factors, and digital nudging techniques. Her work bridges theoretical research with practical applications in digital humanities, cultural heritage, and computing education. Dr. Lykourentzou has received significant recognition for her research, with multiple publications garnering substantial citations and reader attention across platforms like Mendeley and social media. Her work on personality-based team formation (2016) has been particularly influential with over 90 citations. Prior to joining Utrecht University, she worked as a Senior Researcher at the Luxembourg Institute of Science and Technology (LIST), where she coordinated the European H2020 project CROSSCULT. She has also collaborated with the Human-Computer Interaction Institute of Carnegie Mellon University as a visiting researcher and with INRIA Nancy-Grand Est and the Public Research Center Henri Tudor as a postdoctoral fellow.

Benedikt Ehingerمشاهده پروفایل

استادیار

• Computational Cognitive Science
• Visual Cognitive Science
• EEG Analysis
• +۵ مورد دیگر

Benedikt Ehinger is a Tenure-Track Professor for Computational Cognitive Science at the Stuttgart Center for Simulation Science (SC SimTech) and the Institute for Visualization and Interactive Systems (VIS) at the University of Stuttgart. His research bridges cognitive neuroscience, computational modeling, and visualization techniques to understand visual perception and decision-making processes. Education 2018: PhD in Cognitive Science from University of Osnabrück with thesis "Predictions, Decisions and Learning in the visual sense" 2013: Master of Science in Cognitive Science from University of Osnabrück with thesis "Filling in Blind-Spots: A psychophysical and an EEG study" 2011: Bachelor of Science in Cognitive Science from University of Osnabrück with thesis "Electrophysiological Correlates of Category Learning" Research Interests Ehinger's research focuses on the intersection of visual cognitive science, computational modeling, and neuroimaging techniques. His work primarily investigates predictive coding mechanisms in visual perception, statistical learning in visual scenes, eye movement control, method development for combined EEG and eye-tracking analyses, visual completion phenomena like the blind spot, and category learning and neural plasticity. His approach combines behavioral experiments, EEG recordings, eye-tracking, and advanced statistical modeling to uncover the computational principles underlying human visual cognition. Publication Trends Ehinger's publication record shows a clear evolution from foundational work on visual perception and category learning toward methodological innovations in neuroimaging analysis. His early work focused on visual completion phenomena, category learning, and melanopsin modeling. More recently, he has pioneered techniques for analyzing combined EEG and eye-tracking data, developing toolboxes like "unfold" that address critical challenges in temporal overlap correction and regression-based analysis. His research demonstrates a consistent thread of applying computational approaches to understand visual cognition while simultaneously advancing the methodological toolkit of cognitive neuroscience. Scientific Contributions Development of the "unfold" toolbox for overlap correction and regression-based EEG analysis Creation of the EEGVIS toolbox for EEG visualization Establishment of comprehensive eye-tracking test batteries for validating mobile eye-tracking devices Innovative approaches to modeling fixation durations and eye movement patterns Research Environment Ehinger leads the Computational Cognitive Science group within the Institute for Visualization and Interactive Systems at the University of Stuttgart. His work is situated at the intersection of cognitive science, neuroscience, and computer science, collaborating with researchers across these disciplines. His lab utilizes behavioral experiments, EEG, eye-tracking, and computational modeling to investigate visual cognition, with emphasis on open science practices and methodological transparency.

Antonio Pietrabissaمشاهده پروفایل

دانشیار

• Networked Systems
• Time-delay Systems
• Non-cooperative Control
• +۴ مورد دیگر

Antonio Pietrabissa is an Associate Professor at the Department of Computer, Control, and Management Engineering “Antonio Ruberti” (DIAG) of the University of Rome Sapienza, where he earned his degree in Electronics Engineering (2000) and PhD in Systems Engineering (2004). He has been teaching Automatic Control and Process Automation since 2010 and holds the National Scientific Qualification as Full Professor in Systems and Control Engineering (09/G1). Research interests include networked systems, robust control, Markov decision processes, and deep reinforcement learning. His work spans telecommunications, biomedical applications, and space systems, with a focus on federated learning and decentralized control. He has authored ~70 journal papers (Scopus h-index 22) and co-invented a patent for model predictive control in motor disability assistance. Awards include the 2021 Cybersecurity Award and ETRI Journal Best Paper. Current projects are NANCY (6G networks) and CADUCEO (AI-driven medical diagnostics). He is also CEO of Sapienza startup Automation Intelligence and Control (AICO), commercializing AI solutions for space, telecom, and biomedical sectors.

• Artificial Intelligence
• Deep Learning
• Action Recognition in Videos
• +۴ مورد دیگر

Catherine Achard is a full Professor at Sorbonne University, affiliated with the RPI-Bio team under Polytech Sorbonne. She has served as Deputy Director at Polytech Sorbonne since 2020 and has been actively involved in research and teaching in artificial intelligence and computer vision. Research Focus: Artificial Intelligence, Deep Learning, Action/Gesture Recognition, Multi-modal Interaction, Person Re-identification Teaching: AI courses at Sorbonne University (M1/M2) and Polytech Sorbonne, Image Processing for L3. Her recent publications (2023-2025) demonstrate expertise in 3D point cloud registration, adaptive virtual agents, and multimodal interaction analysis. Key trends include geometric constraint handling, deep reinforcement learning for action spotting, and biomedical applications of AI. Technical Contributions: Development of RoCNet++ for point cloud registration, ASAP framework for agent adaptation, and SALAD for action detection. Collaborations span robotics, medical imaging, and human-computer interaction projects across international conferences.