جست‌وجوی استاد و پژوهشگر

• Signal Processing
• Biomedical Signal Processing
• Medical Technology
• +۳ مورد دیگر

Cindy C.A.G. Verstappen is a University Researcher at the Department of Electrical Engineering, Eindhoven University of Technology, and an active member of the Eindhoven MedTech Innovation Center. Her work focuses on non-contact physiological monitoring technologies and their clinical applications. Primary Affiliation: Eindhoven University of Technology Department: Electrical Engineering Research Focus: Signal Processing Systems for Medical Applications Her research interests center on biomedical signal processing, particularly video-based detection of cardiac arrhythmias and vital signs. Key areas include: Remote cardiac monitoring using RGB camera data Machine learning for arrhythmia classification Optic flow analysis in medical imaging Telemedicine applications for heart failure patients Non-contact respiration rate monitoring ICU patient safety systems Recent publications highlight advancements in camera-based vital sign monitoring (2025) and telemedicine protocols for heart failure rehabilitation (2023). Collaborations span multiple institutions including Maxima Medical Centre and SPIE conference participants. Research outputs demonstrate a clear trajectory toward integrating computer vision and clinical practice, with specific emphasis on: Detection of supraventricular tachycardia Continuous heart/respiration rate monitoring Optimizing cardiorespiratory diagnostics Validation of non-contact monitoring systems Tele-rehabilitation frameworks Clinical implementation challenges

• Face Recognition
• Biometrics
• Synthetic Data Generation
• +۴ مورد دیگر

Ivan DeAndres-Tame is an Assistant Professor in the Department of Signal Theory and Communications at the School of Engineering, Universidad Autónoma de Madrid. His research focuses on advancing biometric systems with particular emphasis on face recognition and behavioral biometrics using cutting-edge computer vision and machine learning techniques. His research interests span face recognition systems, synthetic data generation for biometric applications, explainable AI in biometric contexts, and keystroke verification systems. DeAndres-Tame has made significant contributions to the field through his leadership in major international challenges including the FRCSyn Challenge at CVPR and WACV, and the Keystroke Verification Challenge at IEEE BigData. His work bridges theoretical advances with practical applications in biometric security systems. Analysis of his recent publications reveals a strong focus on evaluating and improving face recognition systems using synthetic data, with a growing interest in the intersection of large language models and biometric systems. His research demonstrates consistent innovation in benchmarking methodologies and evaluation frameworks for biometric systems. Throughout his career, DeAndres-Tame has collaborated extensively with leading researchers in the biometrics community, including Ruben Tolosana, Rubén Vera-Rodríguez, Aythami Morales, Julian Fiérrez, and Javier Ortega-Garcia, contributing to the advancement of biometric technologies through both theoretical and applied research.

• Constitutional Law
• European Union Law
• International Law
• +۵ مورد دیگر

Dr. Ewa Michałkiewicz-Kądziela is an Assistant Professor and Vice-Dean for International Cooperation at the Faculty of Law and Administration of the University of Szczecin. Her research focuses on constitutional law, European Union law, international law, and human rights protection mechanisms. Key areas of interest include digital identity legal frameworks, challenges posed by emerging technologies like deepfakes, and comparative analyses of human rights protection across national, EU, and international systems. She holds a doctorate in law from the University of Szczecin (2019) with a dissertation on 'The Right to Human Identity in Polish and International Law.' Her teaching spans constitutional law, EU law, bioethics legal foundations, and human rights protection. Dr. Michałkiewicz-Kądziela actively contributes to academic governance through roles in international cooperation teams, educational quality assurance, and curriculum development. Her recent publications address pressing issues such as constitutional court reform, digital disinformation threats, and legal boundaries of emerging technologies. Her work bridges theoretical legal scholarship with practical policy implications, particularly in areas like electoral integrity, judicial independence, and bioethics. She maintains strong ties with the Centre for Legal Analysis at the University of Szczecin, contributing to interdisciplinary research projects.

Karon MacLeanمشاهده پروفایل

استاد

• Haptic Interfaces
• Human-Computer Interaction (HCI)
• Multisensory Interaction
• +۶ مورد دیگر

Karon MacLean is a Professor of Computer Science and Director of the SPIN (Sensory Perception and Interaction Research Group) at the University of British Columbia. She joined UBC in 2000 after working at Interval Research Corp. in Palo Alto. Her research focuses on restoring physicality to human-computer interaction through haptic interfaces, multisensory interaction, and affective communication. She holds a Bachelor's degree from Stanford University and graduate degrees from MIT. Her work emphasizes application-driven design, exploring haptic feedback in robotics, embedded systems, and healthcare contexts. Current projects include developing Calmer, a robotic device for preterm infant pain management, and CuddleBits, affective robot pets. She leads the SPIN Lab, which investigates haptic languages, low-power interfaces, and evaluation techniques for tangible computing. Her academic contributions span over two decades, with key areas including physical user interfaces, parasitic power systems, and the integration of haptics into medical and everyday technologies. She advises students on HCI topics and collaborates internationally on projects that merge engineering, psychology, and design.

• Cybersecurity
• Privacy and Data Protection
• Cloud Computing Security
• +۶ مورد دیگر

Stefanos Gritzalis is a Professor of Information and Communication Systems Security at the University of Piraeus, Greece (2019+), leading the Lab. of Systems Security. Previously, he served as Rector of the University of the Aegean (2014-2018) and held academic roles at the University of the Aegean, including Professor and Head of the Department of Information and Communication Systems Engineering. His expertise spans cybersecurity, privacy, and regulatory compliance, particularly in cloud computing and IoT. He is a member of the Hellenic Authority for Communication Security and Privacy and the National Commission for Human Rights (2024+). Education includes a BSc in Physics, MSc in Electronic Automation, and PhD in Information and Communications Security from the University of Athens. His research focuses on cybersecurity, privacy preservation, and GDPR compliance, with over 336 publications, including 14 books and 37 chapters. He has an h-index of 55 and is ranked in the top 2% of global ICT researchers (Elsevier, 2024). He serves as Area Editor for IEEE Communications Surveys and Tutorials , and has edited 35 journals. He has supervised 17 PhD theses and over 150 Master’s and 300 BSc theses. His work includes designing privacy-aware systems and frameworks for cloud forensics, with grants exceeding €6 million. He advises on EU-funded projects and evaluates proposals for global research bodies like the ERC and Swiss National Science Foundation. His contributions to policy include co-creating Greece’s Open Government Partnership National Action Plan and advising on digital transformation strategies. He promotes cybersecurity education through gamification and has published on privacy literacy initiatives.

• Cybersecurity
• Digital Watermarking
• Industrial Internet of Things
• +۵ مورد دیگر

Sani Abdullahi is an Assistant Professor at the Maersk Mc-Kinney Moller Institute within the University of Southern Denmark. He specializes in cybersecurity, digital watermarking, and privacy-preserving technologies, with a focus on Industrial Internet of Things (IIoT), audio signal processing, and biometric security. Research Interests : Cybersecurity, digital watermarking, IIoT, biometric security, privacy-preserving technologies, computer vision, and audio signal processing. Teaching : Courses include Advanced Cybersecurity and Biometric Security and CyberSafe: Mastering the Art of Cybersecurity (Summer School) . His recent work explores audio data authentication, recaptured image detection, and secure IIoT frameworks. Notably, he received the Best Paper Runner-up Award at the International Workshop on Distributed Digital Twins for his contributions to cybersecurity.

• Biometrics
• Soft Biometrics
• Traumatic Stress Disorder
• +۵ مورد دیگر

Mubashir Ali is an Assistant Professor in Computer Science, actively contributing to interdisciplinary research. His work intersects Natural Language Processing Machine Learning Biometrics Public Health Informatics Smart City Technologies with focus on addressing UN Sustainable Development Goals through computational methods.

• LIDAR technology
• Point cloud analysis
• Big data algorithms
• +۹ مورد دیگر

Adrian Widłak is a Teaching Assistant at the Department of Computer Science, Faculty of Computer Science and Telecommunications, Cracow University of Technology. His research focuses on information and communication technology (ICT) with specialization in point cloud analysis, visibility mapping, and network security. Specializes in LIDAR technology and Digital Surface Model (DSM) processing for viewshed generation Conducts research in big data algorithms, cryptography, and artificial intelligence Active in edge computing optimization and intelligent transportation systems His work spans multiple interdisciplinary domains including environmental monitoring, biomedical applications, and blockchain security. Recent publications demonstrate a focus on: 3D spatial analysis techniques using point cloud data Machine learning applications in ecological modeling Cybersecurity challenges in modern network architectures Optimization of edge computing infrastructures Blockchain consensus mechanisms and security frameworks

Shuang Haoمشاهده پروفایل

دانشیار

• Security and Privacy
• AI Techniques in Cybersecurity
• Adversarial Attacks
• +۳ مورد دیگر

Shuang Hao is an Associate Professor in the Department of Computer Science at the University of Texas at Dallas , affiliated with the Erik Jonsson School of Engineering & Computer Science . He leads research at the intersection of cybersecurity and artificial intelligence. Undergraduate: Tsinghua University PhD: Georgia Institute of Technology (advisor: Nick Feamster) Postdoc: University of California, Santa Barbara (collaboration with Giovanni Vigna and Christopher Kruegel) His research focuses on security and privacy , particularly data-driven and AI-based techniques to combat adversarial attacks, illicit activities, and vulnerabilities in digital infrastructure. Key areas include AI security , big data security , and next-generation network systems . Recent publications analyze ad attribution laundering , AI-synthesized face detection , and machine unlearning vulnerabilities . Awards include the NSF CAREER Award (2022) and IETF Applied Networking Research Prize (2020) . He mentors PhD, Master’s, and undergraduate students , including Matthew Joslin, Xian Wang, and Melissa Fulfer. Courses taught include CS 6349: Network Security and CS 4390: Computer Networks . Media coverage spans MIT Technology Review , Wired , and The Wall Street Journal . His work exposes threats in Zigbee protocols , DNS resolution interception , and ultrasound cross-device tracking .

• Applied Human Physiology
• Exercise Performance
• Cycling Biomechanics
• +۴ مورد دیگر

Professor Chris Abbiss is the Dean of Graduate Research and a Professor of Exercise Physiology at Edith Cowan University's School of Medical and Health Sciences. His research focuses on applied human physiology and exercise performance, particularly in cycling, fatigue, thermoregulation, pacing strategies, and recovery. He collaborates with national and international sports agencies like the Australian Institute of Sport and Cycling Australia, and his work has attracted over $9 million in competitive grants. With an Scopus h-index of 32 and 140+ peer-reviewed articles, his research spans high-intensity training, environmental physiology, and athlete health. Qualifications : PhD and First-Class Honours in Sports Science from ECU. Research Interests : Abbiss's work examines fatigue mechanisms, thermoregulation during exercise, and pacing strategies across cycling and multi-sport events. He explores recovery techniques like cold water immersion, precooling, and blood-flow restriction, alongside biomechanical and physiological adaptations in athletes. His studies often involve combat sports, triathlon, and endurance cycling, with a focus on environmental stress and performance optimization. Article Trends : His recent articles analyze HIIT in thermal extremes, single-leg vs. double-leg cycling, athlete monitoring practices, and pacing in multi-disciplinary sports. Themes include muscle oxygenation, metabolic profiling, and data-driven training adjustments. Collaborative work spans cross-country mountain biking, hydration, and biofeedback in elite boxing. Supervision & Grants : Abbiss supervises PhD candidates in gut health, cycling performance, and neurological profiling. His grants include $5.7M from the Multiple Sclerosis Society and $9.8M from the Australian Institute of Sport. He co-ordinates projects on weight-cutting in combat sports and cycling data analytics.

Suyong Songمشاهده پروفایل

دانشیار

• Econometrics
• Corporate Finance
• Empirical Industrial Organization
• +۵ مورد دیگر

Suyong Song is an Associate Professor in both the Department of Economics and the Department of Finance at the Tippie College of Business, University of Iowa. He is also a Henry B. Tippie Research Fellow, recognizing his contributions to research in economics and finance. His academic appointments reflect a strong interdisciplinary profile bridging econometric theory and financial applications. Education: Ph.D. in Economics, University of California-San Diego (2010) M.A. in Economics, Korea University (2004) B.A. in Economics, Korea University (2002) Suyong Song's research lies at the intersection of econometrics, corporate finance, and machine learning. His work focuses on developing and applying advanced statistical methods to economic and financial problems, particularly in the areas of quantile regression, measurement error models, network analysis, and non-Euclidean data. He investigates how social and interfirm networks influence corporate decisions, and applies machine learning techniques to diverse domains such as body shape-income relationships and social media sentiment analysis. His methodological rigor is evident in his publications in top-tier econometrics and finance journals. The recent publications highlight a consistent trend toward integrating modern data science tools—especially machine learning and network analytics—into traditional economic frameworks. His work spans corporate governance, supply chain resilience, monetary policy evaluation, and labor economics, demonstrating broad applicability of his methodological innovations. The articles reflect a strong emphasis on causal inference, robust estimation, and the use of novel data sources such as social media and biometric data. Scientific Awards and Recognitions: Henry B. Tippie Research Fellow Suyong Song actively engages in research advising and has collaborated with numerous scholars across institutions. While specific grant details are not listed, his publication record in high-impact journals suggests successful funding and research leadership. His interdisciplinary collaborations indicate involvement in team-based research projects, particularly in econometrics and applied finance. There is no mention of formal student advising in the provided text, but his role as a research fellow and associate professor implies mentorship responsibilities. He is involved in the broader research ecosystem at the Tippie College of Business, contributing to seminars and research initiatives in business analytics and econometrics. His work with the Tippie Analytics Cooperative and participation in research seminars suggest engagement with data-driven research platforms and academic discourse. His research program appears poised to continue advancing econometric methods and their application to pressing economic and business challenges.

• Digital Signal Processing
• Biomedical Engineering
• Audio Processing
• +۷ مورد دیگر

Rafik Goubran is a Professor in the Department of Systems and Computer Engineering at the Faculty of Engineering and Design, Carleton University. He holds the distinguished title of Chancellor’s Professor and currently serves as the Vice-President (Research and International). He earned his Ph.D. from Carleton University and is a licensed Professional Engineer (P.Eng.). His research expertise spans digital signal processing, biomedical engineering, audio processing, and the development of smart environments for senior independent living, with applications in patient monitoring, sensor systems, and real-time analytics. Dr. Goubran's recent publications highlight a strong focus on applying machine learning and sensor technologies to healthcare challenges, particularly in gerontechnology. His work involves non-invasive monitoring of sleep apnea, cognitive decline, driving behavior in older adults, and ambient health monitoring using smart homes and IoT systems. He explores innovative methods such as using pressure mats, audio analysis, and video magnification for vital sign detection and behavioral assessment. Life Fellow, IEEE Fellow, Canadian Academy of Engineering (CAE) Chancellor’s Professor, Carleton University Dr. Goubran has co-supervised 24 Ph.D. and 72 Master’s students and has secured significant research funding from NSERC, CIHR, NCE, and OCE for projects related to aging, health monitoring, and smart technologies. He is the co-leader of the TAFETA project and was the founding Director of the Ottawa-Carleton Institute for Biomedical Engineering. His work involves extensive collaboration with institutions like the Bruyère Research Institute and industry partners such as QNX and BlackBerry. He leads a research lab focused on technology-assisted environments, developing systems for patient monitoring, fall detection, and cognitive assessment, contributing significantly to the field of assistive and ambient intelligence for healthcare.

• Security and Reliability of VR/AR Systems
• Internet of Things and Mobile Sensing
• Blockchain and Distributed Systems
• +۷ مورد دیگر

Dr. Henry Hong-Ning Dai is an Associate Professor in the Department of Computer Science at the Faculty of Science, Hong Kong Baptist University (HKBU). He previously held academic positions at Lingnan University and Macau University of Science and Technology, where he advanced from Assistant to Associate Professor. He holds a Ph.D. from the Chinese University of Hong Kong and a D.Eng. from Shanghai Jiao Tong University. Education: Ph.D. in Computer Science and Engineering, Chinese University of Hong Kong (2008) D.Eng. in Computer Technology Application, Shanghai Jiao Tong University (2012) M.Eng. in Computer Science and Engineering, South China University of Technology (2003) B.Eng. in Computer Science and Engineering, South China University of Technology (2000) Dr. Dai's research focuses on security and reliability of VR/AR systems , Internet of Things , blockchain and distributed systems , federated learning , and cyber-physical systems . His work integrates AI, networking, and software engineering to address real-world security and performance challenges in emerging technologies. He has published over 300 papers in top journals and conferences such as IEEE JSAC, TMC, ICSE, INFOCOM, and AAAI, accumulating more than 24,000 citations. The 15 most recent publications (2023–2025) highlight his leadership in VR/AR security (e.g., AcouListener, Meta VR study), blockchain scalability and fairness (e.g., Porygon, Auncel, Justitia), federated and robust learning (e.g., EBS-CFL, FedDP), and edge-AI and wireless security (e.g., HARBOR, Smart Shield). His recent work also explores AI-generated art evaluation and LLM-driven manufacturing systems , showcasing interdisciplinary innovation. Scientific Awards and Recognition: Holder of 1 U.S. patent and 1 Australia innovation patent Winner of more than 17 awards Senior Member of ACM, IEEE, and EAI Dr. Dai has been Principal or Co-Investigator on over 12 research projects totaling HK$16 million, funded by UGC, NSFC, FDCT, and HKBU. He serves as an Associate Editor for IEEE Communications Surveys & Tutorials , IEEE Transactions on Intelligent Transportation Systems , and several other IEEE journals. He has chaired program committees and served on the PC of top conferences including ICSE, KDD, and INFOCOM. He is actively recruiting Ph.D. students and RAs in security, blockchain, and AI. Laboratories and Research Teams: While not explicitly named, Dr. Dai leads a research group focused on secure and intelligent distributed systems, with active projects in blockchain, VR security, and edge AI. His team has developed open-source tools such as VR-SP Detector , PrettySmart , and RLF for smart contract analysis and security assessment.

• Veterinary Epidemiology
• Biometry
• Veterinary Public Health
• +۳ مورد دیگر

Jenny Linstädt is a researcher at the Institute of Veterinary Epidemiology and Biometry within the Department of Veterinary Medicine at Freie Universität Berlin. Her work focuses on veterinary public health, epidemiological modeling, and biometric analysis of animal disease data. Key research areas include: Veterinary epidemiology and disease transmission Biometric data analysis in animal health Antibiotic usage and resistance monitoring (KAbMon project) One Health approaches to zoonotic diseases She is based at Königsweg 67, Berlin, and her research aligns with the institute's emphasis on veterinary public health and disease surveillance systems.

Elias N. Zoisمشاهده پروفایل

دانشیار

• Digital Signal Processing
• Image Processing
• Pattern Recognition
• +۴ مورد دیگر

Elias N. Zois is an Associate Professor in the Department of Electrical & Electronics Engineering at the University of West Attica, where he has taught since 2019. Previously, he held positions as Lecturer (since 2009), Assistant Professor (2015-2022), and Adjunct Professor at multiple institutions including the Hellenic Army Academy and Hellenic Police Academy. He received his B.Sc. (1994), M.Sc. (1997), and Ph.D. (2000) in Physics and Electronics Engineering from the University of Patras, Greece. His research focuses on digital signal processing , image processing , pattern recognition , and specialized applications in handwriting biometry and offline signature verification . Recent work extends to smart grid optimization , including load forecasting and non-technical loss detection using machine learning techniques. Analysis of his 15 most recent publications reveals strong interdisciplinary trends: 60% focus on advanced biometric verification using Riemannian geometry and metric learning, while 40% apply machine learning to energy systems. Key methodologies include sparse coding, manifold learning, and neural network ensembles, with consistent applications in security systems and smart grid resilience. He has led multiple funded projects including: BioControl (2021-2023): Experienced Researcher for biometric systems Ireact-NG (2018-2021): Experienced Researcher in smart grid technologies ESA SimSat Engine Enhancement (2011-2015): Theoretical Project Manager for aerospace simulations He directs research at the TELSIP Laboratory (Building Z, University of West Attica), specializing in signal processing and pattern recognition systems.