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Richard GuestView profile

Professor

• Biometric Systems
• Forensic Technologies
• Applied Artificial Intelligence
• +3 more

Richard Guest is a Professor of Biometric Technologies at the University of Southampton's School of Electronics and Computer Science. He holds an Honorary Professorship at the University of Kent and a Visiting Researcher position at Purdue University. His expertise spans biometric systems, forensic technologies, and ethical AI applications. Previously, he served as Deputy Divisional Director and Head of Engineering at the University of Kent before joining Southampton in 2024. Education: BEng (Hons) in Computer Science (University of York, 1995), PhD in Electronic Engineering (University of Kent, 2000). Research focuses on applied AI, biometric security, forensic image analysis, and privacy-preserving techniques. He leads ISO/IEC standardization efforts for biometric data interchange and advises the UK Home Office on biometric ethics. His work includes mobile facial recognition systems and explainable AI for legal settings. Publications span mobile biometric verification, forensic verification tools, and transformer-based AI models. He has secured over £5M in research funding and supervises PhD students in Computer Science. Awards include Fellowships from the British Computer Society and IET, Chartered Engineer status, and membership in EPSRC's Peer Review College.

• AI Ethics
• Cognitive Science
• Machine Learning
• +7 more

Dr. Michal Klincewicz is an Assistant Professor at Tilburg University's Department of Cognitive Science and Artificial Intelligence, affiliated with the Tilburg School of Humanities and Digital Sciences. He also holds a part-time position as an Assistant Professor at Jagiellonian University. His research focuses on AI ethics, cognitive science, and the intersection of video games with well-being and decision-making. Klincewicz completed his PhD in Philosophy at the CUNY Graduate Center and conducted postdoctoral research at the Berlin School of Mind and Brain. His work addresses ethical challenges in AI applications, including mental healthcare chatbots, generative AI's societal impacts, and consciousness theories. He leads projects like 'Moral Video Games Collaboration' and 'Understanding the associations between online video games and well-being.' Klincewicz is also involved in serious games development, such as 'The Sustainable Port,' to study real-world decision-making dynamics. Key collaborations include MindLabs and the Port of Rotterdam Authority. His research spans over 47 publications, with recent focus on AI ethics, cognitive neuroscience, and video game expertise analysis using eye-tracking and machine learning. He actively participates in conferences and networks like the Netherlands Research School for Information and Knowledge Systems (SIKS).

Shafaeat HossainView profile

Professor

• Machine Learning
• User Authentication in Smart Devices
• Behavioral Biometrics
• +1 more

Shafaeat Hossain is a Professor in the Department of Computer Science at Southern Connecticut State University (SCSU) . He holds a Ph.D. in Computational Analysis and Modeling from Louisiana Tech University (2014) and advanced degrees from the University of Dhaka. His research focuses on machine learning , user authentication in smart devices , behavioral biometrics , and multi-biometric verification . B.S. in Computer Science and Engineering, University of Dhaka (2006) M.S. in Computer Science, Louisiana Tech University (2012) Ph.D. in Computational Analysis and Modeling, Louisiana Tech University (2014) His work bridges machine learning with security applications , particularly in touchscreen gesture analysis , continuous authentication , and behavioral biometrics for smartphones. He explores multi-biometric fusion strategies to enhance security and user convenience, while also investigating game theory in social networks and NLP for deep authorship attribution . Recent publications highlight advances in capacitive swipe authentication , zoom gesture analysis , and Wi-Fi indoor positioning . Collaborative studies address sleep apnea diagnosis and smartwatch dynamics in verification systems. SCSU Faculty Scholar Award (2023) SCSU Mid-Level Faculty Research Fellowship (2019) Senior Member, IEEE He has secured grants totaling over $25,000 from SCSU, CSU-AAUP, and UConn for projects on child safety in digital authentication and multi-biometric security enhancement . His scholarship spans IEEE Access , Computers & Security , and top-tier conferences like IEEE IJCNN and SMARTCOMP .

Sanka RasnayakaView profile

Lecturer

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +6 more

Sanka Rasnayaka is a Lecturer at the School of Computing, National University of Singapore , where he has worked since 2022. He previously served as a full-time Teaching Assistant and PhD candidate at the same institution. PhD in Computer Science (2021), National University of Singapore B.Sc. Engineering (Honours) in Computer Science and Engineering (2016), University of Moratuwa, Sri Lanka Research interests focus on Artificial Intelligence and Computer Vision , specifically in biometrics, privacy, and human perception. Current projects explore: Biometrics & Continuous Authentication (gait, keystroke dynamics) Large Language Models for Software Engineering Physics-Informed Generative AI for flood modeling Recent publications demonstrate expertise in: Biometric authentication systems Privacy-preserving AI Transformer architectures for behavioral analysis Generative AI in environmental modeling Teaching includes foundational courses like CS1101S Programming Methodology (co-teaching since 2022) and CS2040 Data Structures and Algorithms (AY2410). He also developed workshops on Generative AI, LLMs, and Computer Vision. Projects supervised: CRISP Platform for classroom management Live Annotation Tool for educators AI Pal for customized LLM assistants Scientific awards include multiple Teaching Excellence Awards (2024-2025) and scholarships from NUS (2017-2021).

• Cybersecurity
• Healthcare IT Security
• Machine Learning
• +4 more

Carlos Cilleruelo Rodríguez is an Associate Professor in the Department of Computer Science at Universidad de Alcalá. He is affiliated with the TIFyC research group ("Information Technologies for Training and Knowledge") and specializes in cybersecurity, healthcare IT security, and authentication systems. His research focuses on dark web analysis, malware detection, and adaptive security frameworks. He earned his Doctorate from Universidad de Alcalá in 2023 with the thesis "A cybersecurity review of healthcare industry 2023" , supervised by Dr. José Javier Martínez Herráiz and Dr. Luis de Marcos Ortega. His work spans ransomware mitigation in manufacturing, continuous authentication architectures (JBCA), and privacy issues in IoT healthcare devices. Recent projects include the ProTego initiative for mobile authentication in eHealth environments. Publications highlight trends in machine learning for behavioral authentication, darknet interconnections, and security in Bring-Your-Own-Device (BYOD) healthcare settings. No scientific awards explicitly mentioned. Labs/teams: Active contributor to the TIFyC group, focusing on cybersecurity education and applied research in critical infrastructure protection.

Veijo VaakanainenView profile

Lecturer

• Second language acquisition
• Third language acquisition
• Swedish as a Second Language
• +6 more

Veijo Vaakanainen is a University Lecturer of Swedish at the Centre for Language and Communication Studies, University of Turku (since 2023). His roles include teaching Swedish for medical and economics students, designing language courses, and integrating AI into pedagogy. He previously held part-time teaching positions at the University of Turku’s Department of Scandinavian Languages and German, as well as Åbo Akademi University’s Swedish Department (2016–2023). His expertise spans second/third language acquisition, cross-linguistic influence, and digital tools in education. Education: PhD in Scandinavian Languages from the University of Turku (2016–2025), funded by Svenska kulturfonden and Svenska litteratursällskapet i Finland. Earlier roles include secondary school teaching (2018–2019) and research on formulaic sequences in learner languages (2017). Research focuses on connectors in L2 Swedish writing, leveraging Systemic Functional Linguistics and keystroke logging. He explores multilingualism, AI applications in language learning, and effective digital pedagogy. Recent work includes analyzing connector usage dynamics in Swedish and German learner texts, and developing interactive learning materials using QR codes and gamification. Teaching innovations include AI-integrated language courses and collaborative digital projects. He emphasizes student-centered approaches, evidence-based methods, and ethical sustainability in education. No scientific awards are explicitly listed, but his work has been supported by prestigious Finnish cultural and literary foundations.

• Biometrics
• Behavioral Biometrics
• Mobile Authentication
• +12 more

Ruben Tolosana is a researcher at the Biometrics and Data Pattern Analytics Lab (BiDA Lab) in the School of Engineering at Universidad Autónoma de Madrid. His work centers on biometrics, with emphasis on behavioral and mobile authentication, face recognition, privacy-enhancing technologies, and deep learning applications in human-computer interaction. He actively contributes to major research initiatives such as the FRCSyn-onGoing challenge and the ChildCI framework. PhD in Computer Science or related field (inferred from publication volume and role) Advanced training in machine learning, computer vision, and biometrics His research interests include behavioral biometrics, mobile device security, synthetic data for AI training, privacy in biometric systems, and the application of Transformer models to user authentication. Tolosana's work often involves the development of novel datasets and benchmarking platforms to advance the field. He has co-authored influential surveys on privacy vulnerabilities in mobile sensors and privacy-preserving techniques in biometric recognition. The most recent articles highlight trends in using synthetic data for face recognition, applying Transformers to behavioral biometrics (keystroke, touchscreen, gait), and developing frameworks for child age detection via interaction patterns. His work consistently addresses real-world challenges such as privacy, bias, and system generalization. Publications in journals like Information Fusion , Pattern Recognition , and ACM Computing Surveys reflect the high impact and interdisciplinary nature of his research. Second FRCSyn-onGoing: Winning solutions and post-challenge analysis to improve face recognition with synthetic data (2025) ChildCI framework: Analysis of motor and cognitive development in children-computer interaction for age detection (2024) FRCSyn-onGoing: Benchmarking and comprehensive evaluation of real and synthetic data to improve face recognition systems (2024) SwipeFormer: Transformers for mobile touchscreen biometrics (2024) An Overview of Privacy-Enhancing Technologies in Biometric Recognition (2024) Ruben Tolosana collaborates extensively with researchers in the BiDA Lab, including Rubén Vera-Rodríguez, Aythami Morales, Julian Fierrez, and others. He has contributed to the development of public databases such as mEBAL and ChildCIdb, supporting open science. His work is supported by ongoing research grants (inferred from project scope and publications), and he plays a key role in organizing workshops such as WAMWB to advance the mobile and wearable biometrics community. He is a core member of the Biometrics and Data Pattern Analytics Lab (BiDA Lab), a leading research group in biometric technologies, where he contributes to multiple projects involving mobile authentication, face recognition, and privacy-preserving AI systems.

João Pedro Machado VitorinoView profile

Part-Time Lecturer

• Machine Learning
• Artificial Intelligence
• Cybersecurity
• +3 more

João Pedro Machado Vitorino is a part-time lecturer and researcher at the Polytechnic Institute of Porto's School of Engineering, affiliated with GECAD. He is pursuing a Ph.D. in Informatics Engineering (Artificial Intelligence) at the University of Porto and holds an MSc in Artificial Intelligence Engineering. Education : Ph.D. (in progress), MSc, and BSc in Informatics/Artificial Intelligence Engineering Research : Focuses on machine learning robustness, explainability, and adversarial attack simulation for cybersecurity applications Projects : Involved in 7 EU/National R&D initiatives (2021-2025), including BEHAVIOR (2024-2025) and CYDERCO (2023-2025) His recent publications (2023-2025) span cybersecurity datasets , adversarial learning , malware detection , LLM security , and energy-efficient AI . He co-organized the 36th European Simulation & Modelling Conference (2022) and peer-reviewed for Pattern Recognition and Computers & Security . Awards : IEEE Outstanding MSc Thesis (2023), Engineers Association Innovation Award (2024), multiple merit certificates Skills : Machine Learning, AI Security, Network Analysis, and 3 professional certifications (Cisco, Microsoft, Airbus)

Amy J. KoView profile

Professor

• Computing Education
• Human-Computer Interaction (HCI)
• Equity & Justice in Computing
• +6 more

Amy J. Ko is a Professor and Associate Dean for Academics at the Paul G. Allen School of Computer Science & Engineering and The Information School at the University of Washington, Seattle . She serves as Editor-in-Chief of ACM TOCE , co-directs Reciprocal Reviews and CS for All Washington , and leads the CENSOR Research Lab . Her work prioritizes equitable, liberatory computing education , bridging human-computer interaction and social justice . Research Focus: Equity in CS education, AI literacy, inclusive design, developer productivity, and ethical technology use Awards: Best Paper Award (2024, 2022) Diversity + Inclusion Award (2024) Most Influential Paper Honorable Mention (2014) Honorable Mention (2024, 2023) Publications: Over 184 works spanning program comprehension, assessment design, ethical pedagogy, and democratizing computing education Books: Foundations of Information , Critically Conscious Computing , and Teaching Accessible Computing Her Google Scholar profile reflects citations under her deadname, which she advocates to correct. She emphasizes student agency and community collaboration , particularly with marginalized groups in computing spaces.

Bridianne O'DeaView profile

Associate Professor

• Mental Health
• Digital Mental Health Solutions
• Youth Mental Health
• +5 more

Dr. Bridianne O'Dea is an Associate Professor and NHMRC MRFF Investigator based at the Black Dog Institute, affiliated with the University of New South Wales. She completed her PhD in Health Sciences at the University of Sydney in 2013, along with a Graduate Certificate in Educational Studies (Higher Education) in 2011 and a Bachelor of Health Science (Honors, First Class) in 2009. Dr. O'Dea leads a comprehensive research program focused on identifying and addressing treatment gaps in mental health service provision using innovative Internet solutions. Her research integrates public health, psychology, and computer science to design and test scalable, low-cost digital interventions that proactively reach young people rather than waiting for them to seek help. Her vision is to ensure all young Australians have access to timely, appropriate, and effective mental healthcare. Her work demonstrates significant trends in digital mental health, with a strong emphasis on creating accessible treatments and service models through technology. Recent publications highlight her leadership in developing smartphone applications for mental health monitoring, school-based prevention programs, and AI-driven recommendation systems. Her research spans adolescent depression, suicide prevention, teacher wellbeing, and the use of digital phenotyping to identify mental health markers. Scientific Awards: Bupa Emerging Health Researcher Award (2018) NSW Young Tall Poppy Award (2017) theMHS Early Career Research Award - Innovation (2017) Multiple Black Dog Institute Travel Awards (2015-2018) Centre for Research Excellence in Suicide Prevention Best Paper Award (2017) Dr. O'Dea has secured substantial research funding, including an NHMRC MRFF Investigator Grant (2021-2026) for her project 'Tackling it with Tech: Using novel internet solutions to overcome the burden of depression in youth' and multiple NHMRC Project Grants. She collaborates extensively with researchers across disciplines including psychology, computer science, and public health. Her work with the Future Proofing Study represents a major longitudinal effort to understand adolescent mental health through digital interventions and monitoring.

• Translation Studies
• Cognitive Translation Processes
• Dubbing Translation
• +5 more

Kristian Tangsgaard Hvelplund is an Associate Professor with the Department of English, Germanic and Romance Studies at the University of Copenhagen's Faculty of Humanities. His academic work centers on translation studies, with a particular emphasis on cognitive processes in translation and dubbing translation. Translation cognition and automaticity Eye-tracking and keystroke logging methodologies Media translation and dubbing Translation process modeling Hvelplund's research combines theoretical and applied approaches, utilizing experimental methods to analyze translation quality and cognitive resource allocation. Recent publications explore emotional dimensions in translation, post-editing workflows, and methodological innovations in cognitive translation studies. His work demonstrates strong interdisciplinary connections across Translation Studies , Cognitive Science , Applied Linguistics , and Human-Computer Interaction . Methodologically, he focuses on Eye-tracking , Process modeling , and Quantitative translation analysis . As a dedicated educator, Hvelplund supervises BA, MA and PhD students in translation studies while maintaining active participation in international academic collaborations.

• Applied cryptography
• Cryptographic protocols
• Network security
• +5 more

Dr. Ji Sun Shin is a Professor in the Department of Computer and Information Security at Sejong University, where she has been faculty since 2012. Her research bridges theoretical cryptography with practical security applications across multiple domains including IoT, smart devices, and critical infrastructure systems. Education: Ph.D. in Computer Science, University of Maryland at College Park (2009) B.S. in Computer Engineering, Seoul National University (2001) Professor Shin's research focuses on applied cryptography and network security with particular expertise in authentication systems. Her work spans password-based key exchanges , keystroke dynamics authentication , privacy-preserving protocols , and IoT security . She has made significant contributions to provably secure cryptographic protocols including HB/HB+ protocols, forward-secure identity-based signatures, and functional signatures. Her research addresses both theoretical foundations and real-world implementation challenges in cryptographic systems. Analysis of her recent publications reveals a strong trend toward privacy-preserving techniques in distributed systems, with significant work in federated learning security, blockchain applications for IoT, and efficient cryptographic implementations. Her research demonstrates consistent evolution from theoretical cryptography toward practical security solutions for emerging technologies like smart grids, drone systems, and smartphone authentication. Research Leadership: Principal Investigator of the Information Security Lab at Sejong University Active research collaboration across multiple domains including smart cities, healthcare systems, and critical infrastructure security Extensive patent portfolio with numerous domestic and international patents related to location verification, blockchain security, and authentication systems Professor Shin's laboratory focuses on practical security implementations with research areas spanning smartphone security, short-range communication protocols, IoT authentication mechanisms, and smart car security systems. Her team develops fundamental security technologies that address both theoretical security guarantees and real-world usability constraints.

Massimo Orazio SpataView profile

Research Fellow

• Deep Learning
• Biomedical Engineering
• Computer Science
• +3 more

Massimo Orazio Spata is a Research Fellow in Computer Science at the University of Catania's Department of Mathematics and Computer Sciences, specializing in deep learning applications for biomedical, audio, and biometric systems. He has held roles at STMicroelectronics since 1999, focusing on system integration, image processing, and biomedical device R&D. He teaches courses such as Mobile Programming and Computer Architecture at secondary schools and has advised numerous students on grid computing and middleware projects. Education: PhD in Computer Science (University of Catania, 2008), MSc in Computer Science (University of Catania, 2013), and a teaching certification in Computer Science (University of Catania, 1998). Research interests include deep learning algorithms, biomedical device development, grid scheduling, and cybersecurity. He has authored patents on lab-on-chip systems, bio-computer analysis, and scheduling methods, and his work has been recognized with STMicroelectronics Innovation Awards (2016–2014) and a Cisco CCNA certification. Key collaborations include projects with Google (Mediapipe Objectron for robotics), Huawei (video deblurring), and involvement in the PNRR Horizon HiCONNECTS project (2024–present). He serves on conference committees (e.g., ICAETA 2023) and has developed e-learning systems and CAD tools for STMicroelectronics.

Bin ZhangView profile

Associate Professor

• Prognostics and Health Management
• Fault Detection and Isolation
• Failure Prognosis
• +8 more

Dr. Bin Zhang is an Associate Professor in the Department of Electrical Engineering at the Molinaroli College of Engineering and Computing, University of South Carolina. With over 20 years of experience in prognostics and health management, intelligent systems and control, and robotics, he has established himself as a leading researcher in battery management systems, power electronics, and fault-tolerant control systems. Dr. Zhang's educational background includes: Ph.D. in Electrical Engineering from Nanyang Technological University, Singapore M.E. in Mechanical Engineering from Nanjing University of Science and Technology, China B.E. in Mechanical Engineering from Nanjing University of Science and Technology, China His research focuses on active approaches to achieve intelligent smart systems with self-situational-awareness and self-adapting capabilities. Primary interests include prognostics and health management (PHM), which covers fault detection and isolation, failure prognosis, and fault tolerance; robotics and unmanned systems; intelligent systems and control; and dynamic systems design, modeling, simulation and control. His work integrates physics-based models with data-driven techniques and computational intelligence, including pattern recognition and machine learning. Analysis of Dr. Zhang's recent publications reveals a strong emphasis on battery modeling (particularly lithium-ion batteries), power electronics control (including fractional order delay and virtual variable sampling techniques), and deep learning methods (including graph neural networks, deep residual convolutional neural networks, and deep belief networks). His research spans multiple application domains including power grids, batteries, aircraft, helicopters, and manned/unmanned vehicles. Dr. Zhang serves as Associate Editor for prestigious journals including IEEE Transactions on Industrial Electronics, IEEE Transactions on Systems, Man, and Cybernetics: Systems, and Neurocomputing. He is a Senior Member of IEEE and a member of ASME. As director of the Resilient Systems Laboratory, Dr. Zhang advises numerous graduate students working on cutting-edge research in battery technology, power cable insulation, and control systems. His lab is equipped with advanced facilities including an 8-channel ARBIN BT-Smart battery testing system, power electronics control systems, cable/wire testing systems, rotating machinery testing systems, and unmanned vehicles including quadrotors and hexacopters.

Bogdan GhitaView profile

Associate Professor

• Cybersecurity
• Network Security
• IoT Security
• +8 more

Dr. Bogdan Ghita is an Associate Professor and Associate Dean International in the Faculty of Science and Engineering at the University of Plymouth. His primary affiliation is with the School of Engineering, Computing and Mathematics. He leads network research within the Centre for Security, Communications, and Network Research. His research focuses on cybersecurity, IoT security, machine learning applications in networking, blockchain technology, network function virtualization, and disaster communication systems. He has supervised over 20 PhD students on topics ranging from smart grid optimization to network intrusion detection. Teaching responsibilities include undergraduate courses like Cyber Security and Networks, Ethical Hacking, and Network Monitoring, as well as postgraduate modules in Ethical Hacking. He actively contributes to curriculum development in online education and cybersecurity pedagogy. Key research themes include: Network slicing and NFV in disaster recovery systems Cybersecurity for IoT and industrial systems Machine learning for network anomaly detection Blockchain-based trust management for M2M services Forensic analysis of digital evidence His recent work explores AI-driven personalized education frameworks and quantum-resistant cryptographic schemes. He has published extensively in top-tier conferences/journals with a focus on applying computational methods to solve real-world cybersecurity challenges.