جست‌وجوی استاد و پژوهشگر

• Human-Computer Interaction
• Virtual Reality
• Augmented Reality
• +۱۷ مورد دیگر

Prof. Dr. Antonio Krüger is the CEO of the German Research Center for Artificial Intelligence (DFKI) and Director of the Ubiquitous Media Technology Lab (UMTL) at the Saarland Informatics Campus in Saarbrücken, Germany. He is a leading researcher in human-computer interaction, virtual and augmented reality, multimodal interfaces, and intelligent systems. His research interests span a broad range of topics including virtual reality (VR), augmented reality (AR), gesture interaction, haptic feedback, EEG and eye tracking, gamification, cognitive load estimation, brain-computer interfaces, and smart environments. His work emphasizes user-centered design, perceptual illusions, and real-world applications in domains such as automotive, healthcare, and education. His recent publications (2023–2024) demonstrate a strong focus on advancing VR interaction through techniques like hand redirection, synthetic gesture generation for vehicles, implicit intent recognition using multimodal sensing, and personalized object referencing. These works reflect trends toward seamless, natural, and adaptive interfaces that leverage AI, perception, and real-time feedback. Prof. Krüger supervises a large team of researchers and students, including Mansi Sharma, Amr Gomaa, André Zenner, and Martin Feick, indicating active mentorship and collaborative research leadership. His lab, UMTL, develops innovative technologies in immersive environments, wearable systems, and intelligent user assistance, contributing to both academic knowledge and practical applications.

Redwan Alqasemiمشاهده پروفایل

استاد پژوهشی

• Rehabilitation Robotics
• Assistive Technologies
• Human-Robot Interaction
• +۹ مورد دیگر

Dr. Redwan Alqasemi is a Research Professor in the Department of Mechanical Engineering at the University of South Florida's College of Engineering and serves as the Lead Researcher at the Center for Assistive, Rehabilitation and Robotics Technologies (CARRT). He is actively involved in research, teaching, and laboratory leadership on the USF Tampa campus. His research focuses on the development of innovative technologies for individuals with disabilities, particularly in the domains of rehabilitation robotics and assistive systems. Key areas include brain-computer interfaces (BCI), virtual and augmented reality for vocational training, haptic feedback systems, and intelligent robotic manipulation. Notable projects include the Wheelchair-Mounted Robotic Arm (WMRA), VR4VR (Virtual Reality for Vocational Rehabilitation), and neural control of robotic systems using EEG signals. Dr. Alqasemi leads multiple advanced research laboratories—Assistive and Rehabilitation Robotics (ARR), Rehabilitation Robotics & Prosthetics Testbed (RRT), and Simulation and Virtual Reality (SVR)—equipped with state-of-the-art robotics, motion capture, VR/AR systems, and prosthetic testing environments. His work has resulted in over 200 technical publications and four U.S. patents, with several technologies approaching commercialization. He is recognized for his contributions through membership in the National Academy of Inventors, Senior Membership in IEEE, and service on advisory panels for NSF, NIH, and the Department of Veterans Affairs. He also serves as an Associate Editor for IEEE/RSJ IROS and MDPI Sensors Journal. Dr. Alqasemi teaches courses in robotic systems, covering kinematics, control, and simulation using MATLAB, Python, and ROS. He mentors graduate students through hands-on research in his labs, fostering innovation in assistive and rehabilitation technologies.

• Brain-Computer Interface
• Artificial Intelligence
• Machine Learning
• +۵ مورد دیگر

Dr. Shams Al Ajrawi is an Assistant Professor in the Department of Data Analytics at the California School of Management and Leadership, Alliant International University, San Diego. She holds a Ph.D. in Electrical and Computer Engineering from the joint doctoral program of the University of San Diego and San Diego State University (JDP), completed in 2021. Her academic journey includes an M.S. from the New York Institute of Technology (2009) and a B.S. from the University of Technology (2005). She has held teaching positions at numerous institutions, including Coleman University (lead and core faculty), San Diego State University, University of California San Diego, University of San Diego, University of North Texas, Carnegie Mellon University, and community colleges such as MiraCosta, Grossmont, and Miramar College. Dr. Al Ajrawi's research focuses on Brain-Computer Interface (BCI) applications , integrating key technologies such as Artificial Intelligence, Machine Learning, Advanced Signal Processing, Wireless Communication, and Cybersecurity . Her work bridges engineering and data science, aiming to advance human-computer interaction systems. She has contributed significantly to academic scholarship as an editor and reviewer for various IEEE Transactions journals, reflecting her standing in the engineering research community. Full Fellowship (SDSU/UCSD/NSF) in Electrical and Computer Engineering (2016–2021) Dr. Al Ajrawi has advised and taught students across multiple universities over 15 years, contributing to graduate and undergraduate programs in engineering, technology, and data analytics. While specific grants are not listed, her fellowship support indicates prior funding success. She is actively involved in curriculum development and interdisciplinary research mentorship. Though no formal lab or research team is mentioned in the text, her affiliations with research-intensive institutions and editorial roles suggest engagement in collaborative research environments focused on BCI and intelligent systems.

Lazar Teodoraمشاهده پروفایل

مدرس

• Electrical Engineering
• Energy Security
• Power Systems
• +۵ مورد دیگر

Teodora Lazar is a Lecturer and Head of Department at the University of Petroșani's Faculty of Mechanical and Electrical Engineering, specifically within the Department of Automation, Computers, Electrical and Power Engineering. Their research focuses on electrical safety, energy security, power systems resilience, and occupational health in critical infrastructure sectors such as mining and energy production. They have authored numerous technical courses and publications addressing modernization of electrical installations, renewable energy integration, and hazard mitigation strategies. Key research areas include: Electrical safety protocols for underground mines and power substations Risk assessment methodologies for critical infrastructure Sustainable energy solutions and grid modernization Analysis of power quality issues in renewable energy systems Policy implications for national energy security Recent publications emphasize multidisciplinary approaches to energy system vulnerabilities, combining technical analysis with policy frameworks. Their work often addresses practical implementation challenges in Romania's energy infrastructure, including coal and uranium mining subsectors. Teodora has contributed to lab modernization projects at the University of Petroșani's Electroenergetics Laboratory and developed innovative applications like BCI-based mental state recognition systems. Their work bridges theoretical engineering principles with real-world industrial safety requirements.

Müjdat Çetinمشاهده پروفایل

استاد

• Signal Processing
• Image Processing
• Data Science
• +۱۲ مورد دیگر

Müjdat Çetin is a Professor of Electrical and Computer Engineering and serves as the Robin and Tim Wentworth Director of the Goergen Institute for Data Science and Director of the New York State Center of Excellence in Data Science at the University of Rochester. He previously held faculty positions at Sabancı University and was a Research Scientist at MIT, with visiting roles at Boston University, Northeastern University, and MIT. Education: PhD in Electrical Engineering, Boston University, 2001 MS in Electrical Engineering, University of Salford, 1995 BS in Electrical Engineering, Boğaziçi University, 1993 His research lies at the intersection of signal processing, machine learning, and data science, with applications in biomedical imaging, radar, and brain-computer interfaces. He develops probabilistic and deep learning models for robust information extraction from noisy and complex data. His work emphasizes computational imaging, sparse representations, and multimodal data fusion. The recent publications reflect a strong trend toward integrating Bayesian methods and deep learning in imaging sciences, particularly in medical image reconstruction, neuroimaging analysis, and radar systems. His group actively explores transformer architectures, federated learning, and model-based deep learning for solving inverse problems in imaging. Scientific Awards and Honors: IEEE Fellow IEEE Signal Processing Society Best Paper Award IET Radar, Sonar and Navigation Premium Award Elsevier Signal Processing Best Paper Award Turkish Academy of Sciences Distinguished Young Scientist Award (GEBİP) ODTÜ Mustafa Parlar Foundation Research Incentive Award TÜBİTAK Career Award Boston University Best Engineering Research Award Professor Cetin has advised numerous PhD and Master’s students and led significant research grants in data science and imaging. He has served as a Senior Area Editor for IEEE Transactions on Image Processing and IEEE Transactions on Computational Imaging, and held editorial roles in several top journals. He has chaired major conferences including ICASSP, ICIP, and IVMSP workshops. He leads a multidisciplinary research group focused on data science and imaging, collaborating with neuroscientists and medical researchers. The team develops novel algorithms for brain-computer interfaces, medical image analysis, and remote sensing systems, often integrating machine learning with physical models of data acquisition.

• Artificial Intelligence
• Machine Learning
• Human-Computer Interaction
• +۱۶ مورد دیگر

Professor Damien Coyle is the Director of the Bath Institute for the Augmented Human at the University of Bath, where he leads cutting-edge research in artificial intelligence, machine learning, and human-computer interaction. His work is centered on brain-computer interfaces (BCI), neurotechnology, and cognitive computing, with applications in healthcare, rehabilitation, and intelligent systems. His research interests include Brain-Computer Interfaces , Spiking Neural Networks , Deep Learning , Emotion Recognition , Virtual and Extended Reality , and Neurofeedback Systems . He applies advanced AI techniques to decode neural signals, enabling real-time interaction between the brain and external devices. His interdisciplinary approach integrates neuroscience, computer science, and engineering. His recent publications from 2023–2024 reveal a strong focus on anomaly detection in industrial systems , EEG-fMRI data fusion for inner speech decoding , multi-level IT incident prediction using AI , and enhancing neurofeedback with immersive VR . These works demonstrate a trend toward multimodal data integration, real-time BCI applications, and AI-driven decision support in both clinical and technological domains. He has supervised numerous students and collaborators, many of whom are co-authors on his publications. His research is frequently published in top-tier IEEE and Springer conferences. He actively contributes to the advancement of neuroadaptive technologies and is involved in high-performance computing for BCI calibration. His leadership in organizing major conferences further underscores his influence in the field.

• Data Science
• Neural Engineering
• Machine Learning
• +۷ مورد دیگر

Seif Eldawlatly is a Professor in the Department of Computer Science and Engineering at The American University in Cairo (AUC), where he joined as an associate professor in Fall 2022 and has since been promoted. He has prior affiliations with the Faculty of Engineering at Ain Shams University and the Faculty of Media Engineering and Technology at the German University in Cairo. Education: PhD in Electrical Engineering, Michigan State University, East Lansing, Michigan, USA (2011) MSc in Electrical Engineering (Computer and Systems), Faculty of Engineering, Ain Shams University, Cairo, Egypt (2006) BSc in Electrical Engineering (Computer and Systems), Faculty of Engineering, Ain Shams University, Cairo, Egypt (2003) His research lies at the intersection of data science, machine learning, and neural engineering , with a strong emphasis on developing both invasive and non-invasive Brain-Computer Interface (BCI) systems. His work applies signal processing and electrophysiology techniques to innovate in areas such as visual prosthetic systems and early diagnosis of neurodegenerative diseases. He also develops assistive technologies enabling disabled individuals to interact with computers using EEG signals. Although specific publication titles are not listed, his body of work includes over 70 refereed publications reflecting sustained contributions in neuroscience, machine learning, and biomedical signal processing. His research trajectory shows a consistent focus on applying computational intelligence to solve clinical and assistive challenges in neuroengineering. Scientific Awards: Seif Eldawlatly has served as the principal investigator on multiple research projects, demonstrating leadership in securing and managing research grants focused on machine learning applications in neural engineering and BCI development. While specific grant names and funding agencies are not mentioned, his role as PI highlights his active involvement in funded research. He has not listed any formal advisees in the provided text, but his senior academic position and research output suggest potential mentorship activities. There is no mention of specific labs or research teams in the provided text, though his research areas imply collaboration in neural engineering and data science laboratories focused on electrophysiological signal analysis and BCI prototyping.

Nick Holmesمشاهده پروفایل

دانشیار

• Motor Control
• Rehabilitation
• Somatosensory System
• +۸ مورد دیگر

Dr Nick Holmes is an Associate Professor in Motor Control and Rehabilitation at the School of Sport, Exercise and Rehabilitation Sciences, University of Birmingham. He leads The Hand Laboratory, focusing on the neural and behavioral mechanisms of hand and body movement coordination, and the human somatosensory system, particularly tactile perception on the hands. His research integrates transcranial magnetic stimulation (TMS), electromyography (EMG), motion tracking, and psychophysics. BSc Psychology & Neuroscience MSc Neuroscience D.Phil Neuroscience His research interests span motor control, rehabilitation, somatosensation, and statistical methods in neuroscience. He employs brain stimulation and behavioral techniques to explore how we perceive and control movement across the lifespan. His work has significant implications for neurorehabilitation and understanding sensorimotor integration. His recent publications reveal a strong focus on tactile perception, neural mapping of somatosensory cortex, aging and cognitive control, and methodological rigor in neuroscience. He has contributed to high-impact journals such as Journal of Neurophysiology , Experimental Brain Research , and Cortex , with emerging themes in scientific communication and research transparency. Dr Holmes is actively involved in academic discourse and science communication, serving as an editor and contributing to discussions on research ethics and methodology. Member of the Experimental Psychology Society He currently supervises one PhD student in their final year and welcomes new PhD candidates interested in motor control, somatosensation, and brain stimulation methods. He also produces a science news podcast called The Error Bar , demonstrating a commitment to public engagement and scientific literacy. His laboratory, The Hand Laboratory, serves as a hub for innovative research in human sensorimotor function, combining experimental rigor with translational potential in rehabilitation science.

• Multisensory Perception
• Physiological Computing
• Neurofeedback
• +۵ مورد دیگر

Aleksander Väljamäe is an Associate Professor in Physiological Computing at Tallinn University's School of Digital Technologies (HCI group) and a Grant Consultant at Tartu University. His research focuses on multisensory perception, physiological computing, and neurofeedback applications in brain disorders, BCI, and neurocinema. He has held postdoctoral roles at institutions like Pompeu Fabra University and Graz University, and was a Marie Skłodowska-Curie Fellow (2013–2015). He actively participates in EU projects (e.g., Future BNCI) and art-science collaborations, such as the Multimodal Brain Orchestra. His administrative roles include chairing Tallinn University’s internal research committee and advising for the European Commission and Italian Ministry of Health. Education: PhD in Applied Acoustics (Chalmers University, 2007) M.Sc. in Digital Communication (Chalmers, 2003) BSc in Radio Engineering (Tallinn University of Technology, 2000) Research Interests: Developing novel methods for diagnosing brain disorders (e.g., depression, migraine) using audiovisual media and BCI. Explores wearable technologies, affective computing, and the psychophysiology of emotion. Recent projects include SoniWeight Shoes (2024) and Magic Lining (2019), which investigate body-perception modulation via wearable devices. Grants & Awards: Marie Skłodowska-Curie International Outgoing Fellowship (2013–2015). Active in EU-funded initiatives like POEMS and BrainAble. Labs/Teams: Leads the HCI group at Tallinn University, collaborating with institutions globally. Co-developed the eXperience Induction Machine for mixed-reality interaction studies.

• Electronic Materials
• 2D Materials
• Nanotechnology
• +۳ مورد دیگر

Jose Antonio Garrido is an ICREA Research Professor and Group Leader at the Catalan Institute of Nanoscience and Nanotechnology (ICN2). He leads the Advanced Electronic Materials and Devices Group, focusing on graphene and 2D materials for electronic and bioelectronic applications. He holds a PhD in Telecommunication Engineering from the Universidad Politécnica de Madrid (2000) and a habilitation in experimental physics from Technische Universität München (2010). He has coordinated major projects like the i-VISION retinal implant initiative and the MINIGRAPH brain implant project, involving international collaborations. His work bridges nanotechnology and neuroscience, with contributions to graphene-based neural interfaces, biosensors, and neuroprosthetics. He founded INBRAIN Neuroelectronics to commercialize his group's ICN2-patented technology, achieving regulatory approval for graphene neural interfaces in clinical trials. Education: PhD in Telecommunication Engineering, Universidad Politécnica de Madrid (2000) Habilitation in Experimental Physics, Technische Universität München (2010) Engineer Degree, Universidad Politécnica de Madrid (1996) Research Interests: Development of graphene and 2D materials for neural interfaces, bioelectronics, biosensors, and energy storage. Key areas include neural recording/stimulation, retinal implants, and brain-computer interfaces (BCIs). His work emphasizes translational research, with clinical validation of graphene-based devices. Funding & Grants: Graphene Flagship Core Projects (EU) i-VISION retinal implant (La Caixa Foundation) MINIGRAPH (EIC Pathfinder) RescueGRAPH (MINECO, Spain) Labs & Teams: Leads the ICN2's Advanced Electronic Materials and Devices Group and collaborates with INBRAIN Neuroelectronics. His lab integrates material science, nanotechnology, and neuroengineering for medical applications.

Pino Alexandrosمشاهده پروفایل

مدرس

• Human-Computer Interaction
• Accessibility Technologies
• Assistive Technologies
• +۳ مورد دیگر

Pino Alexandros is a Lecturer in the Department of Informatics and Telecommunications at National and Kapodistrian University of Athens (NKUA), affiliated with the School of Sciences. He has held roles including Laboratory Teaching Staff (EDIP) since 2014 and researcher in the Voice and Accessibility Lab since 1997. His expertise spans Human-Computer Interaction, Assistive Technologies, and Web Accessibility. Educations: PhD (2012): NKUA, Topic: Open Source Software for AAC Applications. MSc (2003): NKUA, Major: Communications and Networks. BEng (1995): Democritus University of Thrace, Field: Energy Engineering. Research Interests: Development of assistive technologies for motor and sensory impairments. Accessibility of digital content (web, eTextbooks, cultural heritage). Human-Computer Interaction design for inclusive systems. Gesture-based interfaces and real-time signal processing. Grants & Projects: EU-funded projects (e.g., InSIDE, HERMOPHILOS) focusing on inclusive education and accessible technologies. National initiatives on assistive tech inventory systems and web accessibility frameworks. Labs/Teams: Active contributor to the Voice and Accessibility Lab, leading work on AAC systems and assistive tech evaluation.

• Robotics
• IoT Security
• Brain-Computer Interfaces
• +۳ مورد دیگر

Dr. Usman Ghafoor is a researcher specializing in robotics, IoT security, and neuroengineering. His work bridges machine learning with biomedical systems, focusing on brain-computer interfaces (BCIs), neuromodulation, and robotic control mechanisms. Key Research Areas: Robotics, IoT Malware Detection, Hybrid EEG-fNIRS Systems, Deep Learning Applications His recent publications highlight interdisciplinary approaches to multibody robot control, neurorehabilitation, and real-time BCI optimization. Collaborative work with experts like Keum-Shik Hong demonstrates his integration into cutting-edge neuroscience and robotics projects. While specific institutional affiliations are not detailed in the provided text, his contributions to journals such as Robotics , Scientific Reports , and Frontiers in Neurorobotics indicate significant academic engagement.

Julia Scottمشاهده پروفایل

استادیار مدعو

• Medical imaging
• EEG
• Virtual reality
• +۳ مورد دیگر

Julia Scott serves as an Adjunct Assistant Professor in the Department of Bioengineering at Santa Clara University's School of Engineering. She directs the Brain and Memory Care Lab, pioneering XR applications in healthcare. Her academic foundation includes a Ph.D. in Neuroscience from UC Davis (2010), an M.S. in Neuroscience from UC San Diego (2006), and a B.S. in Neurobiology, Physiology and Behavior from UC Davis (2003). Her research integrates medical imaging, virtual reality, and neural engineering to address neurodegenerative disorders and cognitive healthcare. Key domains include: Brain-computer interfaces for therapeutic gaming EEG and neuroimaging biomarkers for Alzheimer's VR-enabled cognitive interventions Engineering education innovation Publication analysis reveals cross-disciplinary convergence in neurotechnology, healthcare applications, and educational methodology, with consistent focus on translational neuroscience. No awards or student advisees are documented. She leads the Brain and Memory Care Lab, developing immersive technologies for memory disorders. Grant and team details are unspecified.

Dávid Gulyásمشاهده پروفایل

پژوهشگر ارشد

• Biomedical Engineering
• Brain-Computer Interface
• Motor Control
• +۷ مورد دیگر

Dávid Gulyás is a Research Fellow at the Department of Health Science and Technology , Faculty of Medicine , Aalborg University. His work focuses on Biomedical Engineering , Brain-Computer Interfaces (BCI) , and Neurorehabilitation Robotics , particularly for late-stage ALS patients. He utilizes technologies like EEG signal processing , Virtual Reality interaction , and machine learning to enhance communication and movement detection systems. Current Role : PhD Fellow in Biomedical Engineering Location : Selma Lagerløfs Vej 249, 9260 Gistrup, Denmark His research aligns with the UN Sustainable Development Goals, particularly those related to Health and Well-being and Innovative Technology . Recent work includes analyzing brain activity for hand and tongue movements via around-ear EEG and studying feedback mechanisms in BCI virtual reality systems. Notable activities include organizing the 2025 User-Panel Meeting. Publications span journals like Frontiers in Psychology and Sensors , focusing on classification accuracy, spectral features, and user agency in BCI systems.

Christian Klaesمشاهده پروفایل

استاد

• Neurotechnology
• Brain-Computer Interfaces
• Neuroscience
• +۷ مورد دیگر

Prof. Dr. Christian Klaes leads the KlaesLab at the Ruhr-University Bochum 's Department of Neurotechnology , focusing on advanced neuroprostheses and assistive devices for paralysis rehabilitation. His work integrates neuroscience , machine learning , and virtual reality to decode brain signals for controlling exoskeletons and BCI systems . Key research areas: Brain-Computer Interfaces , Neural Implants , VR-based Neurorehabilitation , and AI-driven Medical Diagnostics Collaborations with Caltech , German Primate Center , and University of Madeira expand his interdisciplinary impact. Recent publications highlight advancements in EEG decoding accuracy , spike sorting algorithms , and somatosensory feedback systems , demonstrating his lab's contributions to neural signal processing and embedded AI platforms for future implants. Current projects include developing smart upper-limb exoskeletons , exploring terahertz brain imaging , and pioneering phantom touch illusions for sensory augmentation in VR environments.