جست‌وجوی استاد و پژوهشگر

Weibo Liuمشاهده پروفایل

مدرس

• Big Data Analysis
• Evolutionary Computation
• Particle Swarm Optimization
• +۷ مورد دیگر

Dr. Weibo Liu is a Lecturer in Computer Science at Brunel University London, affiliated with the College of Engineering, Design and Physical Sciences. His research focuses on big data analysis, evolutionary computation, machine learning, and deep learning techniques, with applications in healthcare data analysis, manufacturing, and image processing. He serves as an Associate Editor for the Journal of Ambient Intelligence and Humanized Computing and the Journal of Cognitive Computation . Weibo Liu earned a B.S. in Electrical Engineering from the University of Liverpool (UK) in 2015 and a Ph.D. in Artificial Intelligence from Brunel University London in 2020. He has contributed to over 54 publications, emphasizing domain adaptation, fault diagnosis, and optimization algorithms. His recent publications highlight advancements in machine learning and deep learning , particularly in domain adaptation , object detection , and industrial applications like additive manufacturing and battery health estimation. His work integrates evolutionary computation (e.g., particle swarm optimization) with neural networks for solving real-world problems in healthcare, robotics, and energy systems. Scientific Awards: Associate Fellow of the Higher Education Academy (AFHEA) He actively supervises PhD projects on Deep Learning-Based Defect Detection for Metal Additive Manufacturing and has participated in program committees, including the 2017 International Conference on Automation and Computing (ICAC). His co-authors include prominent researchers like Prof. Xiaohui Liu and Prof. Zidong Wang.

Laura Burattiniمشاهده پروفایل

استاد

• Bioengineering
• Biomedical Signal Processing
• Electrocardiography
• +۵ مورد دیگر

Laura Burattini is a Professor of Bioengineering at the Department of Information Engineering, Faculty of Engineering, Università Politecnica delle Marche (UNIVPM) in Italy. Her academic work focuses on biomedical signal processing with particular emphasis on electrocardiography, wearable sensor technologies, and machine learning applications in healthcare. She maintains an active research program with numerous recent publications spanning cardiology, diabetes monitoring, gait analysis, and medical diagnostics. Prof. Burattini's research interests center around biomedical signal processing, particularly in the analysis of electrocardiographic signals for cardiac risk assessment. Her work extends to wearable sensor technologies for continuous health monitoring, with specific applications in diabetes management through continuous glucose monitoring metrics and skin temperature variability. She also investigates biomechanical aspects of human movement through gait analysis and electromyography, developing novel algorithms for gesture recognition and motion phase detection. Her research bridges engineering principles with clinical applications, creating practical tools for medical diagnostics and patient monitoring. Analysis of Prof. Burattini's recent publications (2022-2025) reveals a strong focus on applying machine learning and signal processing techniques to solve clinical problems. Her work demonstrates expertise in cardiac electrophysiology (particularly ECG analysis), diabetes monitoring technologies, and biomechanical analysis of human movement. A notable trend is her development of interpretable AI models for medical applications, emphasizing clinical utility alongside technical innovation. She frequently works with multimodal sensor data, integrating information from ECG, EMG, inertial sensors, and other physiological measurements to create comprehensive health assessment tools. Prof. Burattini serves as a full professor with regular office hours (Fridays 14:30-16:30) at UNIVPM's Engineering Faculty. While specific details about her research grants and student advising aren't provided in the available information, her extensive publication record suggests active research supervision and collaboration with clinical partners. Her work appears to bridge multiple disciplines, connecting engineering methodologies with practical healthcare applications.

• Ambient Intelligence
• Ambient Assisted Living
• Intelligent Systems
• +۳ مورد دیگر

Ângelo Costa is an Associate Professor at the Department of Computer Science and Artificial Intelligence within the Higher Polytechnic School II at the University of Alicante. He is affiliated with the IU Computer Research Institute and the Mobile Vision Research Laboratory (MVRLab). Education PhD in Biomedical Engineering (2013), Universidade do Minho Master in Computer Science (2009), Universidade do Minho Bachelor's Degree in Computer Engineering (2007), University of Minho His research focuses on Ambient Intelligence (AmI) and Ambient Assisted Living (AAL), developing Intelligent Systems for cooperative and adversarial environments through Multi-Agent Learning. He contributes to Human-Computer Interaction (HCI) and Robotic Assistants, co-founding the Cognitive Assistants research line. His work spans 25 total publications, including 20 JCR-indexed journals, with 10 in Q1 and 40 in peer-reviewed conferences. Scientific Awards 6 awards from institutions like IBM He has co-supervised 5 Master's theses and currently supervises 2 thesis projects. His academic involvement includes 34 program committees, organizing 9 conferences, and delivering 11 invited talks. Media coverage highlights include international newspaper, radio, and TV exposure. Labs & Institutes Mobile Vision Research Laboratory (MVRLab) Institute of Computer Research (IU Computer Research)

• Artificial Intelligence
• Machine Learning
• Digital Health
• +۴ مورد دیگر

Diogo Martinho is an Adjunct Professor at the Instituto Superior de Engenharia do Porto, part of Instituto Politécnico do Porto, where he teaches in the BSc in Informatics Engineering, MSc in Artificial Intelligence Engineering, and MSc in Biomedic Engineering programs. He is an integrated member of the Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development (GECAD). He obtained his PhD in Informatics Engineering (2023) from Universidad de Salamanca, MSc in Informatics Engineering (2015), and BSc in Informatics Engineering (2013) from Instituto Politécnico do Porto. His research focuses on Artificial Intelligence applications in healthcare and industry , with emphasis on personalized elderly care, chronic disease management, and collaborative decision systems. Core domains include: Multi-agent systems for health coaching Gamified behavioral interventions Ubiquitous decision support frameworks Machine learning for clinical classification His publications demonstrate strong emphasis on hybrid AI approaches combining cognitive agents, argumentation systems, and behavioral modeling. Recent work prioritizes practical implementations in diabetes management, respiratory health, and elderly wellbeing. Awards and honors include: Two PAPRE2024 grants for high-impact publications Best Paper Award (2022) Scientific Excellence Award (2015) Academic Merit Scholarship (2014) He has supervised/co-supervised 1 PhD thesis, 8 MSc dissertations, and 13 BSc projects. As Principal Investigator for EXPAI and ELFMo projects, and researcher in 11 international initiatives (e.g., FoodFriend, AIRDOC, PHE), he secured funding from ITEA, EU Horizon 2020, and Erasmus+. He coordinates GECAD's healthcare AI research and chairs the AItHeC conference session.

• Artificial Intelligence
• Machine Learning
• Human-Computer Interaction
• +۴ مورد دیگر

Victor Crista is a researcher at the Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development (GECAD) at the Polytechnic Institute of Porto. He holds a Master's degree in Artificial Intelligence Engineering and a Bachelor's degree in Informatics Engineering from the Porto School of Engineering (ISEP). Doctoral Program in Artificial Intelligence and Intelligent Systems Engineering (In Progress, 2025-2029) Master's Degree in Artificial Intelligence Engineering (Completed 2025) Bachelor's Degree in Informatics Engineering (Completed 2022) His research focuses on artificial intelligence, machine learning, human-computer interaction systems for the elderly, gamification, natural language processing, and large language models. He specializes in developing intelligent systems for elderly care and health promotion. The most recent articles highlight his work in generative AI, multi-agent systems for wellness, and proactive health interventions targeting the elderly population. His publications span journals, book chapters, and conference proceedings, emphasizing applications of AI in healthcare and behavioral support. 2024: Best Paper Second Award (University of Salamanca) 2022: Best Paper Award (Università degli Studi dell'Aquila) Victor has contributed to several international and national projects, including FoodFriend, MedGPT, and ATT. His work involves adapting tourist routes for physical conditions, AI for food intake monitoring, and ethical healthcare solutions. He is affiliated with the GECAD research group and actively collaborates with institutions like the University of Salamanca and Università degli Studi dell'Aquila.

• Mobile Computing
• Distributed Systems
• File Systems
• +۳ مورد دیگر

Dan Cojocar is a Lecturer in the Department of Computer Science at Babeș-Bolyai University, Cluj-Napoca, Romania. He serves as Lab Instructor for the Mobile Applications course (2024-2025) teaching third-year English-speaking students, and instructs multiple undergraduate courses including Operating Systems laboratories, Web Services and Middleware Technologies, IoT & Android Things, and Tutoriat sessions. His academic responsibilities span course development, laboratory instruction, and bachelor thesis supervision across both semesters of the academic year. Cojocar's research centers on distributed systems with emphasis on the BBUFs (Babeș-Bolyai University File System) framework, mobile computing architectures, and formal verification methods. His scholarly work explores replication strategies, synchronization mechanisms, IPv6-based lookup systems, and aspect-oriented programming for monitoring. The research demonstrates strong integration between theoretical computer science (π-Calculus modeling) and practical system implementation, particularly in Unix-based distributed environments and mobile network routing. Analysis of Cojocar's publication timeline (2006-2015) reveals progressive specialization from foundational web application development toward advanced distributed systems. Early work focused on model-driven approaches (2006) and session management (2007), evolving into BBUFs architecture (2008-2009) and sophisticated replication strategies (2011). The research trajectory shows increasing sophistication in formal methods application while maintaining practical relevance to file system design and mobile networking challenges, with later publications integrating mobile ambient concepts into network routing schemes (2015). Through his GitHub repository (dancojocar/ma), Cojocar maintains comprehensive Mobile Applications course materials used since 2016, featuring multi-language support (Kotlin 40.1%, Java 34.4%) and contemporary mobile development practices. His educational contributions include developing laboratory frameworks for Android, Flutter, and Firebase integration, with course infrastructure utilizing Microsoft Teams and GitHub for student collaboration. The repository's academic adoption (21 stars, 38 forks) demonstrates recognition of his pedagogical approach to mobile computing education.

Shuai ZHANGمشاهده پروفایل

پژوهشگر ارشد

• Swarm robots
• Robotics and autonomous systems
• Multi-robot/agent systems
• +۱۰ مورد دیگر

Shuai ZHANG is a Research Fellow at Nanyang Technological University (NTU), Singapore, working under the supervision of Prof. Chen Lv. He previously served as a Postdoctoral Fellow at the University of Hong Kong (HKU) with Prof. Jia Pan and completed his Ph.D. and Master's in Marine Science and Technology at Northwestern Polytechnical University under Prof. Mingyong Liu and Prof. Xingguang Peng. He was also a Joint Ph.D. student at the Intelligent Computational Engineering Laboratory (ICE LAB) at the University of Strathclyde, UK, supervised by Dr. Edmondo Minisci. Ph.D., Marine Science and Technology, Northwestern Polytechnical University Master, Marine Science and Technology, Northwestern Polytechnical University His research focuses on Swarm robots/drones , Robotics and autonomous systems , Swarm intelligence , and Bio-inspired optimization , with applications in Multi-robot/agent systems , Differential privacy , and Distributed control . He investigates collective behaviors in robotic systems using Game theory and Evolutionary dynamics , while integrating Smooth particle hydrodynamics and Agent-based modeling . Recent publications demonstrate expertise in EEG emotion recognition , BCI-assisted neurorehabilitation , and non-invasive brain-computer interfaces , with a trend toward geometric modeling in neural networks and adaptive signal processing. His work bridges theoretical models (e.g., transformers, co-adaptive networks) with practical implementations in embedded systems and wearable technologies. Associate Editor, 2023 IEEE International Conference on Robotics and Biomimetics (ROBIO 2023) He actively contributes to academic services as a reviewer for journals including IEEE Transactions on Robotics (T-RO), IEEE Robotics and Automation Letters (RA-L), and Complex & Intelligent Systems , reflecting his impact in robotics and computational neuroscience communities.

David Z. Durantمشاهده پروفایل

استاد

• Composition
• Music Theory
• Electroacoustic Music
• +۳ مورد دیگر

David Z. Durant is a Professor of Music at the University of South Alabama, serving as Director of the Music Theory and Technology Program since 2003. A graduate of the University of Florida (BM, MM) and the University of Alabama (DMA), his work bridges classical composition with electroacoustic technologies. Bachelor of Music in Composition, University of Florida Master of Music in Composition and Theory, University of Florida Doctor of Musical Arts in Composition, University of Alabama As both composer and performer, Durant specializes in: Electroacoustic music integration Advanced music theory pedagogy Recording and sequencing technologies Contemporary composition for diverse instruments Multimedia sound design Academic music education leadership His recent compositions have been performed across international festivals including: International Computer Music Conference Sonorities Festival Society for Electroacoustic Music in the US Featured collaborations include: Esther Lamneck (Tarogato performances) Peter Wood (Trumpet recordings) Thomas Rowell & Doreen Lee (Vocal premiere) Technologically, Durant's work explores: 40-channel speaker array capabilities Digital soundfile integration Audio spatialization techniques Multimedia performance systems

• Sensor Networks
• Urban Environment
• Citizen Science
• +۵ مورد دیگر

Ester Vidaña Vila is a Lecturer at the La Salle Digital Engineering School under the Universitat Ramon Llull , specializing in the Engineering Department . Her research focuses on Sensor Networks , Urban Environment , Citizen Science , and Acoustic Event Detection , with a strong emphasis on Environmental Monitoring and Ambient Assisted Living . Her recent work involves deploying Wireless Acoustic Sensor Networks for acoustic comfort prediction and environmental noise analysis . She integrates deep learning techniques and IoT technologies to address challenges in packaging waste classification , smart cities , and healthcare applications such as early dementia diagnosis. Key projects include: EngageMate (2024–2025): Advancing classroom interaction with IoT assistants. Promoting STEAM vocations (2023–2025): Robotics and AI for children’s education. ULTRAPACK (2022–2024): Ultrasonic technology for waste classification. Sons dels Monestirs (2024): Analyzing soundscapes of sacred sites in Catalonia. Her research is supported by grants from Aristos Campus Mundus and the Departament de Recerca i Universitats , with collaborations spanning interdisciplinary teams in engineering, environmental science, and healthcare.

Joe Gauthierمشاهده پروفایل

استادیار

• Electrochemistry
• Heterogeneous Catalysis
• Materials Science
• +۳ مورد دیگر

Joe Gauthier is an Assistant Professor in the Department of Chemical Engineering at Texas Tech University, directing the Computational Catalysis Research Laboratory. His work bridges theoretical and applied research in sustainable energy technologies. His academic background includes: Ph.D. in Chemical Engineering, Stanford University (2020) B.S. in Chemical Engineering, The Ohio State University (2015) Dr. Gauthier's research focuses on structure-property relationships for catalyst design in renewable energy systems. His multidisciplinary approach integrates electrochemistry , heterogeneous catalysis , materials science , and data science to develop in-silico methods for understanding catalyst limitations and engineering novel materials. Key applications include ammonia synthesis, CO2 reduction, and nitrate electroreduction for energy storage and environmental remediation. Analysis of his 15 most recent publications (2025-2022) reveals dominant themes in computational electrocatalysis: electric double layer modeling, reaction selectivity optimization (particularly for urea and ammonia), and energy-efficient pathway design. His work consistently emphasizes high-current-density operation and scalability for industrial decarbonization. Dr. Gauthier actively mentors five doctoral researchers and has guided multiple undergraduates through research projects, reflecting his commitment to developing next-generation scientists. His laboratory maintains strong collaborations with experimental groups to validate computational predictions. The Computational Catalysis Research Laboratory operates as a multidisciplinary hub where quantum mechanical simulations meet practical energy challenges, driving innovation in sustainable chemical production.

• Music and Audio Technology
• Sonic Art
• Human-Computer Interaction
• +۵ مورد دیگر

Tom Davis is an Associate Professor in Music and Audio Technology at The Media School, Bournemouth University , where he teaches on the BA Music and Sound Production degree. He is a practicing artist specializing in sound installation and live performance , with exhibitions across Europe and the United States. His research focuses on the interface between music and technology , including instrument building, technologically mediated improvisation, and enaction. Education: PhD in Sonic Art (Queen's University Belfast, 2008) PGCert in Education Practice (Bournemouth University, 2015) MA in Communication Media: Creative Sound Production (University of the West of England, 2004) BSc (Hons) in Physics with Music (University of Edinburgh, 2001) Research Interests span interdisciplinary domains such as Music Technology , Human-Computer Interaction , and Sonic Art , with a focus on enactive and postphenomenological frameworks. His work explores networked performance ecosystems , actuated instruments , and AI-mediated creativity . Publications and Research Trends reflect his expertise in digital music interfaces , human-AI collaboration , and cultural heritage digitization . Key themes include improvisational agency , assistive technology , and generative sound systems . Grants and Leadership: Davis leads projects like Shared Post-Human Imagination: Human-AI Collaboration in Media Creation (AHRC, 2024) and Improving Educational Outcomes for SEN Students (HEIF, 2017). He serves as an external examiner for institutions like London College of Communication (UAL) and contributes to peer review for journals and funding bodies. Labs and Collaborations: As an affiliate member of CIPPM (Centre for Intellectual Property Policy & Management) , he engages in cross-disciplinary research on emerging technologies and global IP policy .

Armando Diego Bedoyaمشاهده پروفایل

دانشیار

• Biomedical Informatics
• Machine Learning
• Artificial Intelligence in Medicine
• +۳ مورد دیگر

Armando Diego Bedoya is an Associate Professor of Medicine and Biostatistics & Bioinformatics at Duke University School of Medicine, specializing in translational biomedical informatics. He holds appointments in the Department of Biostatistics & Bioinformatics and Division of Translational Biomedical Informatics, with a focus on machine learning and artificial intelligence in clinical settings. Current Positions: Associate Professor of Medicine, Associate Professor of Biostatistics & Bioinformatics Past Appointments: Assistant Professor of Medicine, Medical Instructor in the Department of Medicine His research bridges clinical medicine and data science, with recent work on ambient digital scribing tools, unified health large language models, and ethical considerations in AI-drafted patient communication. He actively explores machine learning applications in clinical decision support systems and critical care workflows. Notable publications include: Framework for evaluating AI-powered clinical scribing tools Health language model assessments for message replies Ethical challenges in patient preferences for AI communication AI implementation in critical care settings Scientific contributions include NIH-funded grants for machine learning-enabled clinical decision support systems (2022-2025). His clinical training spans Internal Medicine and Pulmonary/Critical Care at Duke University School of Medicine, with leadership roles such as Chief Resident at Duke Regional Hospital.

Antonio Piccinnoمشاهده پروفایل

دانشیار

• Human-Computer Interaction
• Human-Centered Design
• End-User Development
• +۷ مورد دیگر

Antonio Piccinno is Associate Professor of Human-Computer Interaction (HCI) at the Department of Computer Science, University of Bari Aldo Moro (UNIBA). He is a founding member of the IVU (Interaction, Visualization, Usability & UX) Laboratory where he coordinates research on the interplay between Human-Computer Interaction and Software Engineering through End-User Development techniques. His research interests focus on Human-Centered Design (HCD), End-User Development (EUD), Adaptive Interfaces, Adaptive Multimedia and Multimodal Interaction, and more recently, Secure software analysis and design. He has extensively explored applications in smart home environments, cultural heritage, medical applications, and cybersecurity. Analysis of his recent publications (2022-2025) reveals a strong trend toward applying Human-Computer Interaction principles to emerging technologies. His work increasingly focuses on symbiotic AI systems, particularly in healthcare contexts, and cybersecurity applications where user behavior and interface design significantly impact security outcomes. He has also maintained a consistent research thread in End-User Development for IoT systems and smart environments. Prof. Piccinno has held significant organizational roles including Full Papers Co-Chair for INTERACT 2023 and 2021, and has served on program committees for numerous international conferences including INTERACT, AVI, and IS-EUD. He currently teaches Software Engineering for undergraduate Computer Science students and Cloud Computing for graduate students at UNIBA. Throughout his career, he has supervised approximately 70 bachelor's and master's theses and one PhD student, while also serving on numerous PhD evaluation committees. Prof. Piccinno is an Expert Member, WG Coordinator, and Websites Coordinator of the IFIP TC13 (International Federation for Information Processing Technical Committee on Human-Computer Interaction). He is also a member of ACM, IEEE, ACM SIGCHI, and SIGCHI Italy, demonstrating his active engagement with the international HCI community.

• Wireless Networks
• Edge Computing
• Artificial Intelligence
• +۳ مورد دیگر

Ying Liu is a Doctoral Researcher in the Department of Information and Communications Engineering at Aalto University . Ying is affiliated with the Ambient Intelligence research group, focusing on advanced wireless network optimization and edge computing systems. Position: Doctoral Researcher Institution: Aalto University Email: ying.2.liu@aalto.fi Research Interests span wireless network optimization, unmanned aerial vehicle (UAV) systems, edge computing, and deep reinforcement learning applications. Ying’s work addresses dynamic resource allocation challenges in multi-UAV environments and task offloading strategies for IoT systems. Publications highlight contributions to UAV deployment and latency reduction in edge computing. Key journals include the IEEE Internet of Things Journal .

• Urban Planning
• Transportation Engineering
• Smart Cities
• +۴ مورد دیگر

Jenni Partanen is an Assistant Professor at Aalto University, specializing in Built Environment research. Her work focuses on urban planning and computational social science, with particular emphasis on transportation systems, smart city technologies, and sustainable urban development. She is affiliated with the Planning and Transportation research group. Her research explores innovative approaches to urban challenges through computational modeling and data-driven analysis. Key areas include pedestrian safety optimization, wind comfort in public spaces, 15-minute city concepts, and urban vitality enhancement using big data. Recent publications highlight her contributions to computational urban planning, environmental design, and spatial analysis. Her methodological approach combines agent-based modeling, cellular automata simulations, and integration of socio-economic metrics with traditional urban data.