جستجوی استاد راهنمای دانشگاهی

Mathieu Cholletمشاهده پروفایل

مدرس

• Social Virtual Agents
• Social Signal Processing
• Human-Computer Interaction
• +۲ مورد دیگر

Mathieu Chollet is a Lecturer in Healthcare Technologies at the University of Glasgow's School of Computing Science. His research explores social virtual agents, social signal processing, and human-agent interaction, with applications in social skills training, healthcare, and remote collaboration. He employs multimodal machine learning to assess user performance and virtual reality for public speaking pedagogy. His work spans experimental studies on psychosocial stress in virtual interactions and the design of AI-driven training systems. Recent publications focus on VR-based collaboration frameworks, fairness in AI, and persuasive communication analysis, reflecting a cross-disciplinary approach integrating computer science, psychology, and education. Dr. Chollet collaborates internationally with institutions in France, Japan, and the UK. He mentors students in healthcare technology innovation and leads projects funded by EU and national grants. His lab investigates affective computing and human-centered AI, aiming to enhance digital literacy and accessibility in virtual environments.

• High Performance Computing
• Parallel Computation
• Novel Architectures
• +۳ مورد دیگر

Dr. Steven Wright is a Senior Lecturer in Computer Science at the University of York, specializing in High Performance Computing (HPC), Parallel Computation, and Novel Architectures. He joined the Department of Computer Science in 2018 and is a member of the Real-Time and Distributed Systems research group. His research focuses on optimizing supercomputers and scientific applications for performance, energy efficiency, and programmability. He collaborates with national laboratories, universities, and industry partners such as the UK Atomic Energy Authority and Intel. Prior to York, he was a Research Fellow at the University of Warwick, working on projects involving fusion physics and Rolls-Royce collaborations. Dr. Wright holds a Ph.D. (2014) and M.Eng. from the University of Warwick, where his doctoral thesis addressed I/O optimization in parallel applications. His teaching responsibilities include leading the High-Performance Parallel and Distributed Systems (HIPC) module and serving as Programme Lead for on-campus Undergraduate CS Programmes. He has also contributed to the Software Testing (SOTE) module and departmental roles such as Chair of the Board of Examiners. Research interests span HPC, energy-efficient computing, and application optimization. Recent work emphasizes performance portability, fusion simulations, and parallel I/O systems. His projects, such as the P3 Explorer database and EMPIRE-PIC framework, highlight contributions to HPC software and simulation tools. Collaborations with institutions like Sandia National Laboratories and industry partners like NVIDIA reflect his interdisciplinary approach to advancing computational science.

• Cognitive Neuroscience
• Neurophysiology
• Language Processing
• +۴ مورد دیگر

Matthias Schlesewsky is a Professor at the University of South Australia (UniSA), affiliated with UniSA Justice and Society. His research focuses on cognitive neuroscience, neurophysiology, and language processing, with a particular emphasis on EEG analysis and mindfulness interventions. He leads studies on how mindfulness training impacts resting-state EEG parameters in high-demand cohorts, such as military personnel. His work also explores the neurobiological foundations of syntax processing, predictive mechanisms in memory, and the role of individual alpha frequency in cognitive tasks. Key affiliations include the Cognitive Neuroscience Laboratory and the Australian Research Centre for Interactive and Virtual Environments. His research integrates experimental psychology, neuroimaging, and computational modeling to investigate language comprehension, attention, and decision-making. Notable projects include studies on EEG-based cognitive workload monitoring in military training and the effects of mindfulness on dynamic task performance. His articles highlight interdisciplinary approaches, combining EEG, ERP, and behavioral data to understand neural mechanisms underlying language, memory, and attention. Collaborations span institutions like Georgetown University, the University of Miami, and the Defence Science and Technology Group.

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

Dr. Benjamin Volmer is a Lecturer at the UniSA STEM division of the University of South Australia. His research focuses on cognitive load reduction in augmented reality (AR) and virtual reality (VR) environments through predictive cue design, human-computer interaction (HCI), and neural response analysis using electroencephalography (EEG). Current Lecturer at University of South Australia Research Degree Supervisor Member of Wearable Computer Lab Collaborator with international institutions Research Trends: Recent publications analyze incongruent information processing in AR systems, multi-level precueing for procedural tasks, and brain-computer interface (BCI) applications in immersive environments. His work demonstrates how EEG metrics and ERP components (e.g., N400, P600) can optimize AR/VR interfaces. Grants: Supported by Australian Research Council (ARC DP180100755) and TU Graz Open Access Publishing Fund. Collaborative efforts span institutions including Columbia University, University of Tokyo, and Keio University. Labs & Collaborations: Affiliated with the Wearable Computer Lab and Australian Research Centre for Interactive and Virtual Environments at the University of South Australia. International partnerships include Graz University of Technology, Columbia University, and Keio University.

Claudio Savaglioمشاهده پروفایل

استادیار

• Internet of Things (IoT)
• Edge Computing
• Edge Intelligence
• +۶ مورد دیگر

Claudio Savaglio is a Tenure-Track Assistant Professor in Computer Engineering at the University of Calabria, Italy , and a Researcher at the Institute for High Performance Computing and Networking (ICAR-CNR) . He is actively involved in IoT and Edge Computing research, with a focus on smart cities, middleware development, and simulation tools.

• Artificial Intelligence
• Multi-Agent Systems
• Automated Negotiation
• +۷ مورد دیگر

Bao Quoc Vo is an Associate Professor at Swinburne University of Technology's School of Science, Computing and Emerging Technologies. He is also a researcher in the Centre for Computing and Engineering Software Systems (SUCCESS). His primary research areas include artificial intelligence (AI), multi-agent systems, automated negotiation, and their applications in cloud computing, traffic management, and energy systems. Dr. Vo has received grants from organizations like the Australian Research Council (ARC), the Commonwealth Scientific and Industrial Research Organisation (CSIRO), and industry partners such as Suncorp Group and SmartSat CRC. His research interests span AI planning under uncertainty, market-based mechanisms, and ethical AI auditing. Notable contributions include work on proactive self-exploration for adversarial environments, distributed task allocation algorithms, and resilient space systems. He has supervised numerous PhD and master’s students on topics ranging from AI-driven anomaly management to healthcare applications of machine learning. Dr. Vo has been awarded the RMIT Vice-Chancellor’s Research Excellence Award and is a Senior Member of the ACM. His work frequently appears in top-tier journals like Expert Systems with Applications and IEEE Transactions on Services Computing .

• Cognitive Science
• Artificial Intelligence
• Virtual Reality Applications
• +۳ مورد دیگر

Marie Šafář is a Full Professor at Tilburg University, affiliated with the School of Humanities and Digital Sciences and the Department of Cognitive Science and AI. Her research focuses on the intersection of artificial intelligence, cognitive science, and human-technology interaction, with notable contributions in virtual reality applications, neuroimaging analysis, and ethical AI development. She leads or co-leads multiple high-impact projects such as STEADFAST (swarm technology for emergency response) and MEGaNorm (neuroscience normative modeling). Her work spans diverse domains including virtual reality's psychological effects, robotic animals in education, and AI ethics. She collaborates internationally, contributing to datasets like the Overview Effect study and facial expression analysis in healthcare. Her projects often bridge academic research with practical applications in healthcare, education, and disaster management. Key research themes include cognitive modeling, neuroimaging techniques, and the societal implications of AI. She actively publishes in interdisciplinary journals and conferences, emphasizing real-world impact through collaborative frameworks.

Xingfu Wuمشاهده پروفایل

استاد پژوهش

• High-performance computing
• Performance modeling and analysis
• Energy and power modeling and analysis

Xingfu Wu is a Research Professor of Computer Science affiliated with Argonne National Laboratory (ANL). He holds a Ph.D. in Computer Science from Beijing University of Aeronautics and Astronautics and M.S. and B.S. degrees in Mathematics from Beijing Normal University. His research focuses on high-performance computing, performance modeling and analysis, and energy-efficient computing. Education: Ph.D. in Computer Science, Beijing University of Aeronautics and Astronautics, Beijing, China M.S. in Mathematics, Beijing Normal University, Beijing, China B.S. in Mathematics, Beijing Normal University, Beijing, China Research Interests: Xingfu Wu's research is centered around high-performance computing, performance modeling and analysis, and energy and power modeling. His work emphasizes optimizing parallel systems, developing frameworks for performance prediction (e.g., MuMMI), and enhancing energy efficiency in high-performance computing environments. Scientific Awards: Best Paper Award, 14th IEEE International Conference on Computational Science and Engineering (CSE-2011), 2011 Second Place, Beijing Science and Technology Advancement Awards, 1997 Labs/Teams: Wu contributes to research at Argonne National Laboratory, particularly through initiatives like the MuMMI framework for performance modeling and analysis.

Susanne Schmidtمشاهده پروفایل

پژوهشگر

• Economics Education
• Educational Measurement
• Cognitive Psychology
• +۳ مورد دیگر

Susanne Schmidt is a Researcher at the Chair of Business Education within Johannes Gutenberg University Mainz's Department 03. Her work focuses on evaluating educational outcomes, digital learning frameworks, and cross-disciplinary reasoning skills across professional fields. She specializes in measuring economic knowledge acquisition, critical online reasoning, and multilevel analysis of student competencies. Core research areas: Educational measurement, quantitative reasoning in economics, and digital pedagogy. Leadership in projects like ILLEV (innovative teaching-learning networks) and TWIND-WiPäd (professional training frameworks). Expertise in cross-cultural studies, migration impact on education, and competency assessment methodologies. Her research bridges cognitive science, educational technology, and business pedagogy, with recent emphasis on professional development in law, medicine, and teaching through digital tools. Over 50 peer-reviewed articles demonstrate contributions to higher education innovation and evidence-based policy. Publications emphasize longitudinal studies on student knowledge growth, including effects of gender, language, and migration background. Collaborative projects address practical challenges like e-assessment systems and teacher training through video-based methods.

Amanda Agnes Østervig Buusمشاهده پروفایل

استادیار

• Nursing Care
• Patient-Reported Outcomes
• Total Knee Arthroplasty
• +۳ مورد دیگر

Amanda Agnes Østervig Buus is an Assistant Professor at the Department of Clinical Medicine, Aalborg University, affiliated with Aalborg University Hospital. She holds dual email addresses at the university's clinical and nursing research units. Her primary affiliation is with The Faculty of Medicine, focusing on healthcare quality improvement and patient-centered care. Her research interests center on nursing care quality, patient-reported outcomes in orthopaedic surgeries (especially total knee arthroplasty), and healthcare professional challenges such as missed nursing care due to staffing and time constraints. She also explores patient experiences in post-stroke rehabilitation programs and educational interventions. Recent work includes studies on systemic factors contributing to missed nursing care in Danish hospitals, predictive models for knee surgery outcomes, and group-based recovery programs for transient ischemic attack patients. Her 2022 publication on Oxford Knee Score subscales demonstrated innovative clinical prediction methodologies. Buus has contributed two datasets on patient information needs in knee arthroplasty, emphasizing evidence-based practice. Though no explicit awards are listed, her work has been cited across peer-reviewed journals and accessed via platforms like Mendeley and Figshare.

• Cyber-Physical Systems
• Systems Biology
• Formal Methods
• +۷ مورد دیگر

Radu Grosu is a full professor and head of the Institute of Computer Engineering at the Faculty of Informatics, Vienna University of Technology (TU Wien). He also serves as a research professor in the Department of Computer Science at the State University of New York at Stony Brook (USA). His leadership extends to directing the Cyber-Physical Systems research group at TU Wien and previously co-directing the Concurrent-Systems Laboratory and co-founding the Systems-Biology Laboratory at SUNY Stony Brook. His research focuses on the modeling, analysis, and control of cyber-physical and biological systems. Key application domains include distributed automotive and avionic systems, Internet of Things (IoT), autonomous mobility, green operating systems, mobile ad-hoc networks, and biological networks such as cardiac, neural, and genetic regulatory systems. His methodological expertise lies in formal methods, hybrid systems, and compositional design. The recent trend in his publications emphasizes formal frameworks for cyber-physical system design, verification of AI-based controllers, green computing, and modeling of biological systems using hybrid and stochastic models. His work bridges theoretical rigor with practical applications in safety-critical domains. Scientific Awards: National Science Foundation Career Award State University of New York Research Foundation Promising Inventor Award Association for Computing Machinery Service Award Advising and Grants: Radu Grosu has co-directed research laboratories and mentored students in concurrent and systems biology research. He has secured competitive funding, evidenced by the NSF CAREER Award and other institutional recognitions. His leadership in founding and directing labs indicates strong grant acquisition and team mentorship capabilities. Labs and Research Groups: He leads the Cyber-Physical Systems group at TU Wien and previously co-directed the Concurrent-Systems Laboratory and co-founded the Systems-Biology Laboratory at SUNY Stony Brook, fostering interdisciplinary research in formal methods and biological computing.

Gabriele Variscoمشاهده پروفایل

پژوهشگر ارشد

• Biomedical Engineering
• Neonatology
• Machine Learning
• +۴ مورد دیگر

Gabriele Varisco is a Research Fellow at Eindhoven University of Technology (Netherlands), affiliated with the Applied Physics and Science Education department and the Eindhoven MedTech Innovation Center . His work bridges biomedical engineering, neonatal diagnostics, and machine learning to address critical challenges in preterm infant care. Research Focus : Neonatal monitoring, machine learning for apnea and sepsis prediction, physiological signal analysis, and optimizing clinical workflows in NICUs. Projects : Key contributor to the TKI-HTSM/21.0219/TKI2112P11 PISANO SPS project (2021-2026) on perioperative innovations and newborn diagnostics. Collaborations : Works closely with X. Long, Z. Peng, P. Andriessen, and C. van Pul on multimodal signal processing for clinical applications. Article Trends : His publications emphasize machine learning integration with multichannel physiological data to predict conditions like central apnea and late-onset sepsis. Key subfields include real-time monitoring algorithms, heart rate variability analysis, CPAP failure prediction, and reducing NICU alarm fatigue through signal optimization. Advising & Grants : No direct student mentoring information is available. Collaborates on projects funded by institutions such as the Eindhoven MedTech Innovation Center and TKI-HTSM (Dutch innovation program).

• Biomedical Engineering
• Biocybernetics
• Signal Processing
• +۴ مورد دیگر

Piotr Augustyniak is a Professor in the Department of Biocybernetics and Biomedical Engineering at the Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, AGH University of Science and Technology, Kraków, Poland. His research spans biomedical signal processing, wearable health monitoring systems, and advanced diagnostic algorithms. Key areas include ECG/EEG analysis, non-invasive physiological measurements, and human-computer interaction in medical contexts. Recent publications highlight his work on: mobile ECG monitoring with approximate computing video thermography for heart failure diagnostics CO2-based occupancy estimation eye-tracking in forensic deception detection neural network optimization for non-uniform sampling EEG entropy metrics for anesthesia monitoring His methodological focus combines: empirical mode decomposition machine learning real-time physiological analytics multimodal sensor fusion

• Human-Computer Interaction
• Automotive Human Factors
• Virtual Reality Applications
• +۳ مورد دیگر

Marine Capallera is a Researcher at the HumanTech Institute within the Fribourg School of Engineering and Architecture at HES-SO. Her work focuses on Human-Computer Interaction, particularly in automotive human factors and virtual reality applications. She leads the AdVitam project on driver-vehicle interaction in autonomous vehicles and the Pro-GIS initiative using VR for social skills training with intellectually disabled youth. Core Affiliations: HumanTech Institute (HES-SO), Fribourg School of Engineering and Architecture Research Themes: Driver monitoring, multimodal interfaces, assistive VR systems Her research explores physiological signal analysis for driver state assessment, adaptive HMI designs for automated vehicles, and VR applications in education/training contexts. Recent projects include developing VR simulators for healthcare training and creating context-aware driver assistance systems using machine learning. Key contributions include a dataset on driver physiological states in automated vehicles (2023), multimodal systems for situational awareness (IEEE Access 2023), and VR-based social training for disabled adolescents (Applied Sciences 2023). Collaborations involve EPFL+ECAL Lab, University of Fribourg, and social educators. Current work emphasizes empathic AI companions for vehicles and haptic-audio-visual immersion enhancements in VR environments.

Lena Kallingsمشاهده پروفایل

دانشیار

• Physical Activity and Health
• Cardiovascular Disease Prevention
• Sedentary Behavior
• +۳ مورد دیگر

Lena Kallings is an Associate Professor at The Swedish School of Sport and Health Sciences, Stockholm, Sweden, and an Associate Researcher at Uppsala University's Department of Public Health and Caring Sciences. She specializes in physical activity, sedentary behavior, and cardiovascular health, with extensive research on lifestyle interventions in occupational settings and post-cardiac care. Department of Physical Activity and Health, Section of Health Sciences Researcher ID: B-3712-2013 Scopus Author ID: 23985231900 Her research focuses on: Lifestyle behavior clustering in middle-aged adults Workplace health assessment trends Post-myocardial infarction activity monitoring Dog-owner exercise program interventions Osteoarthritis rehabilitation strategies Recent publications address: Accelerometer reliability in older adults Occupational sickness absence patterns 24-hour movement behavior analysis Cardiorespiratory fitness forecasting Covid-19 risk factors Her work frequently involves large-scale epidemiological studies (n>40,000) and randomized controlled trials targeting health behavior change in office workers and clinical populations.