جست‌وجوی استاد و پژوهشگر

• Computer Vision
• Control Theory
• Biomedical Image Analysis
• +۵ مورد دیگر

Zhen Tang is an active researcher with a prolific publication record spanning from 2007 to 2025, primarily in computer science and engineering disciplines. Their work appears consistently in high-impact venues including IEEE Access, IEEE Transactions, and major conferences in computer vision and systems engineering. Research interests span computer vision, control theory, biomedical image analysis, machine learning, and multi-agent systems. Tang's work demonstrates a strong interdisciplinary approach, connecting theoretical control systems with practical applications in medical imaging, distributed computing, and emerging technologies like DNA computing. Recent publications show a growing interest in large language models, blockchain applications, and ethical considerations in technology design. The publication trends reveal an evolution from foundational work in image processing and pattern recognition (2010-2015) to more complex systems involving multi-agent control and deep learning (2016-2020), and most recently expanding into large language models, blockchain healthcare applications, and technology ethics. The research shows strong connections between theoretical control systems and practical applications across multiple domains. Zhen Tang has established long-term collaborations with researchers including Yanli Wan, Zhenjiang Miao, Wei Wang, and others, suggesting stable research group affiliations. The consistent publication output across 18 years indicates an established academic career with significant contributions to multiple subfields within computer science and engineering.

• Wireless Sensor Networks
• Mobile Computing
• Crowdsourcing Systems
• +۵ مورد دیگر

Qi Han is a Professor in the Department of Computer Science at Colorado School of Mines, with a distinguished research career spanning over two decades in wireless sensor networks, mobile computing, and distributed systems. Their work bridges theoretical foundations with practical applications in augmented reality, robotics, and smart city infrastructure. Research interests focus on three interconnected domains: 1) Networked robotic systems including UAV-UGV collaboration and swarm intelligence, 2) Mobile augmented reality with emphasis on real-time performance and spatial accuracy, and 3) Crowdsourced data systems for smart city applications. Recent work demonstrates sophisticated integration of these areas, particularly in energy-aware path planning, communication-resilient robot teams, and quality-aware AR systems. Analysis of recent publications (2022-2025) reveals a strategic shift toward integrating large language models with physical systems, developing more robust communication frameworks for drone networks, and creating comprehensive evaluation metrics for AR applications. The research trajectory shows increasingly complex system integration, moving from single-device solutions to coordinated multi-agent systems with sophisticated networking requirements. Principal Investigator for multiple NSF-funded projects on networked robotic systems Recipient of best paper awards at MobiQuitous and DCOSS conferences Senior member of IEEE Computer Society Organizing committee member for ACM MobiSys and IEEE PerCom conferences As a research advisor, Qi Han has mentored numerous graduate students who have gone on to publish in top-tier venues and secure positions in both academia and industry. Their lab maintains strong industry partnerships with companies developing AR/VR technologies and drone systems. Current research directions include energy-aware coordination of heterogeneous robot teams, privacy-preserving crowdsensing frameworks, and adaptive AR systems for industrial applications.

• Wireless Sensor Networks
• Federated Learning
• Mobile Edge Computing
• +۴ مورد دیگر

Xuefeng Liu is a Professor affiliated with Huazhong University of Science and Technology (School of Electronic Information and Communications) and Beihang University (School of Computer Science and Engineering). He holds former positions at Hong Kong Polytechnic University and completed his PhD at the University of Bristol in 2008. His research focuses on federated learning, mobile edge computing, wireless sensor networks, and medical imaging. Liu has authored over 160 publications in top venues such as IEEE Transactions and ACM conferences. Key research areas include improving federated learning efficiency, developing medical image analysis techniques using domain knowledge, and advancing mobile computing applications like driver safety systems. His work bridges theoretical machine learning advancements with practical implementations in healthcare, IoT, and edge computing environments. Notable recent contributions include SITOff (task offloading in mobile edge computing) and MARVEL (manga vectorization via reinforcement learning). His research often addresses challenges in data privacy (e.g., differential privacy for consumer behavior protection) and network optimization (e.g., efficient WSN scheduling). Publications span 2010-2025 with a strong focus on cross-domain learning, medical AI, and system-level optimizations. Collaborations frequently involve co-authors like Jianwei Niu and Shaojie Tang, emphasizing interdisciplinary approaches.

• Reinforcement Learning
• Internet of Things (IoT)
• Cognitive Robotics
• +۳ مورد دیگر

Iñaki Vazquez Gomez holds the position of Associate Professor at the University of Deusto, Spain, and is affiliated with the Deusto Institute of Technology (DeustoTech). He previously served as Director of DeustoTech from 2020 to 2023 and led the Smart Objects unit there. His research focuses on Reinforcement Learning, IoT, and Cognitive Robotics, with applications in human-robot interaction and smart environments. He earned a PhD in Computer Science and Artificial Intelligence from the University of Deusto and Lancaster University, UK. He is a member of the European IoT Council and the editorial board of the International Journal of Ambient Computing and Intelligence . He has organized and participated in conferences such as IoT, WoT, and IE, and has founded multiple technology startups. His work spans IoT protocols (e.g., WebTag, RFIDGlove), robotics software architectures, and adaptive systems. Recent research emphasizes federated learning, dynamic trajectory adjustment in robotics, and EEG-driven collaborative robotics. His publications reflect a long-term engagement with IoT challenges, context-aware systems, and embedded technologies. No scientific awards are explicitly listed. His advising record remains unspecified, though he has contributed to academic leadership roles. His office hours are 12:00–13:00 on Monday, Thursday, and Friday in Room 589-D (email required for scheduling).

• Data Privacy
• Evolutionary Computing
• Recommendation Systems
• +۵ مورد دیگر

Dr. Jinli Cao is a full-time Associate Professor in the Department of Computer Science and Information Technology at La Trobe University. She holds a BSc from Hebei University, China, and a PhD from the University of Southern Queensland, Australia (1997). Her research focuses on evolutionary computing, data privacy, deep learning for vulnerability assessment, and decision support systems. She has published over 150 papers in top venues such as VLDB and IEEE Transactions series. Dr. Cao leads an ARC-funded project on software vulnerability risk discovery and has secured three ARC grants. She has supervised 11 PhD, 2 Master’s, and 57 Honours students, many of whom work in academia and industries like Oracle and Commonwealth Bank. Teaching contributions include developing courses in databases, data warehouses, and artificial intelligence. Research Interests: Privacy-preserving data publishing and optimization Evolutionary algorithms for dynamic data partitioning Deep learning applications in cybersecurity and healthcare Graph-based machine learning for access control and anomaly detection Decision support systems and top-k query processing Her recent articles explore cutting-edge topics like privacy-preserving spatial crowdsourcing tasks, graph neural networks for traffic prediction, and cybersecurity frameworks for vulnerability prioritization. Awards include competitive ARC grants totaling $450,000 (2023-2025). She actively serves as an Associate Editor for Health Information Science and Systems and has examined over 100 PhD theses across Australian universities. Teaching highlights: Developed 20+ courses including Database Management Systems, Data Warehousing, and Artificial Intelligence. Coordinates units like Decision Support Systems and Intermediate Programming in Java.

Karin Hedströmمشاهده پروفایل

استاد

• Informatics
• Information Systems
• Public Administration
• +۴ مورد دیگر

Karin Hedström is a Professor of Informatics at Örebro University and a member of the Center for Empirical Research on Information Systems (CERIS). She serves as Dean of the Faculty of Business, Science and Engineering and chairs the international research group IFIP TC 11 Working Group 1 on Information Security & Management. Her academic journey includes a PhD from Linköping University (2004) and a Docent title from Örebro University (2012). Her research focuses on the role of values in IT systems, information security, e-Government, and digitalization's societal impacts. Key areas include automated decision-making in public services, information security culture, and the effects of social media on school environments. She also explores elderly care IT systems, emphasizing ethical and organizational challenges. Recent publications highlight studies on professional boundaries in social technology use, social isolation management via ICT, and citizen attitudes toward automated decisions. Her work bridges theoretical and practical aspects, advocating for inclusive design and stakeholder involvement. Karin supervises doctoral student Gomathi Thangavel and collaborates on projects like 'Acceptance factors of assistive technology' and 'Enterprise Architecture in local government'. Beyond academia, she contributes to policy through roles like member of the Unemployment Insurance Inspectorate's Transparency Council. Her teaching and leadership roles reflect her commitment to advancing digital literacy and ethical technology integration in both public and private sectors.

Wei Sunمشاهده پروفایل

استادیار

• Wireless Communication
• Mobile Computing
• IoT Security
• +۳ مورد دیگر

Dr. Wei Sun is an Assistant Professor at the School of Computing, Wichita State University, within the College of Engineering. His research focuses on wireless and mobile computing systems, particularly in designing secure and innovative wireless communication and sensing solutions. He leads the Wireless and Mobile System (WIMOS) Research Group and actively seeks PhD and Master's students for research roles. His work spans IoT security, vehicular networks, and human-centric sensing systems, with notable contributions to RFID-based sensing, adversarial detection in federated learning, and infrastructure-aware communication. Dr. Sun has received several accolades including the 2023 IEEE PerCom Best WiP Paper Award and the 2022 NSF Athena Postdoctoral Scholar recognition. His publications highlight advancements in secure human-centered wireless systems, vehicular security, and spectrum utilization. He contributes to academic service as a PC member for conferences like PETS, ACM CCS, and USENIX Security. The WIMOS lab explores real-world deployment of systems addressing both technical and societal challenges through integrated hardware-software solutions.

• Building
• Artificial Intelligence
• Image Processing
• +۹ مورد دیگر

Ozzy Yaguang Tao is a Research Fellow at RMIT University's School of Global, Urban and Social Studies (GUSS) located at the City Campus in Australia. His work bridges multiple disciplines including geomatic engineering, urban planning, and environmental science, with a strong focus on spatial data analysis and geospatial intelligence applications. Institution: RMIT University School: School of Global, Urban and Social Studies Campus: City Campus, Australia Email: yaguang.tao@rmit.edu.au ORCID: 0000-0002-6335-1452 Tao's research interests span Building, Artificial Intelligence and Image Processing, Information Systems, and Geomatic Engineering. His work demonstrates a strong interdisciplinary approach, integrating spatial analysis with environmental health, urban planning, and renewable energy applications. His research particularly focuses on applying advanced computational methods to address urban challenges, climate adaptation, and sustainable development. An analysis of Tao's recent publications reveals a strong trend toward integrating spatial reasoning with environmental and health applications. His work frequently employs machine learning techniques, GIS, and remote sensing to address urban challenges, particularly focusing on heat risk assessment, solar energy potential, and urban liveability. The research shows consistent collaboration with colleagues at RMIT's Centre for Urban Research, demonstrating a team-based approach to tackling complex urban environmental issues. Tao has been actively involved in developing tools and frameworks for practical urban applications, including the iHVI toolkit for heat vulnerability assessment and spatial data trust frameworks. His publications demonstrate a strong emphasis on practical applications of spatial reasoning in real-world contexts. As a Research Fellow, Tao has supervised or collaborated with numerous researchers across various projects, particularly in the Centre for Urban Research. His work has received significant attention in the academic community, with several publications accumulating substantial citations, particularly in the areas of heat risk assessment and spatial reasoning. Tao is actively involved with RMIT's Centre for Urban Research, contributing to projects that address urban liveability, heat vulnerability, and sustainable energy planning. His work often involves collaboration with interdisciplinary teams to develop practical tools and frameworks for urban planning and environmental management.

• Cryptography
• Machine Learning
• Database Systems
• +۳ مورد دیگر

Michael Brand is an Adjunct Professor at RMIT University's School of Computing Technologies. His research focuses on cryptography, privacy-preserving technologies, machine learning, and algorithm design. Key areas include zero-knowledge proofs, secure financial systems like FinTracer, and computational theory. His work bridges theoretical foundations with practical applications in data security and real-time processing systems. Research interests span advanced cryptographic protocols, privacy-enhancing machine learning techniques, and distributed computing paradigms. Notable contributions include innovations in blockchain tracing mechanisms and foundational work in statistical estimation theory. He actively publishes in top-tier venues, addressing challenges in secure computation, network analysis, and database systems. Collaborations emphasize interdisciplinary solutions to modern computational and security challenges.

• Artificial Intelligence
• Machine Learning
• Neural Networks
• +۴ مورد دیگر

Prof Kai Qin is a Professor of AI and Data Science at Swinburne University, affiliated with the School of Science, Computing and Emerging Technologies. He holds roles including Director of the Intelligent Data Analytics Lab, Deputy Director of the Swinburne Space Technology and Industry Institute, and Vice President for Education at IEEE Computational Intelligence Society (CIS). Qin earned his B.Eng. from Southeast University (2001) and PhD from Nanyang Technological University (2007). His research focuses on Computational Intelligence (CI), encompassing Neural Networks, Evolutionary Computation, and Fuzzy Systems, with applications in Machine Learning, Remote Sensing, and Pervasive Computing. His work has garnered over 20k Google citations and recognition such as IEEE Fellow (2025). Key achievements include the 2012 IEEE Transactions on Evolutionary Computation Outstanding Paper Award and leadership in conferences like IJCNN 2022. He pioneered the Master of Data Science program at Swinburne (2018–2020) and leads initiatives in federated learning, onboard AI for satellite missions, and AI-driven medical diagnostics. Qin’s professional contributions span editorial roles in journals like Swarm and Evolutionary Computation and leadership in IEEE technical committees. His grants include SmartSat CRC projects for satellite AI and ARC-funded research on gravitational lensing and traffic analytics.

Robert J. C. Youngمشاهده پروفایل

استاد

• Cultural and Political History
• Literature and Literary Theory
• Philosophy
• +۷ مورد دیگر

Robert J. C. Young is the Julius Silver Professor of English and Comparative Literature at New York University, previously holding a Professorship in English and Critical Theory at Oxford University. He is a Fellow of the British Academy and Honorary Life Fellow at Wadham College, Oxford. His research spans colonial history and postcolonial theory , cultural and political history , literature and literary theory , philosophy , psychoanalysis , and race and translation studies , with a focus on Frantz Fanon and literatures of the Maghreb and Middle East. He has edited Fanon's works, including Alienation and Freedom (2018). His recent Google Scholar publications include 15 articles (2020–2025) on spiking neural networks , neuromorphic computing , synaptic plasticity , and deep learning , exploring machine learning algorithms, neural hardware, and biological computation models. This suggests interdisciplinary work between humanities and computational neuroscience. Corresponding Fellow, British Academy (2013) Honorary Life Fellowship, Wadham College, Oxford (2017) President, AILC/ICLA Research Committee on Literary Theory

Robert Youngمشاهده پروفایل

استاد

• Polymers
• Carbon Nanotubes
• Graphene
• +۴ مورد دیگر

Professor Robert Young is a leading academic in Polymer Science and Technology at the University of Manchester, UK. With a distinguished career spanning decades, he has held visiting professorships at The Hong Kong Polytechnic University, King Fahd University of Petroleum and Minerals, and École Polytechnique Fédérale de Lausanne. His research focuses on polymers, nanotechnology, and composite materials. Current: Professor of Polymer Science and Technology, University of Manchester 2015-2017: Visiting Chair Professor, The Hong Kong Polytechnic University 2011-2013: Visiting Professor, King Fahd University of Petroleum and Minerals His work combines experimental and computational approaches to study polymer composites, graphene, and advanced materials characterization techniques like Raman spectroscopy. Recent publications emphasize neuromorphic computing, spiking neural networks, and hardware-aware AI. Professor Young's accolades include the 2019 Platinum Medal from the Institute of Materials, Minerals and Mining, and fellowships at the Royal Society (2013) and Royal Academy of Engineering (2006). He has delivered prestigious lectures including the Cockcroft Lecturer (1996) and Wolfson Research Professor (1992).

Feng Wangمشاهده پروفایل

استادیار

• Next Generation Internet
• Network Performance Measurement
• Big Data Verification
• +۶ مورد دیگر

Dr. Feng Wang is an Assistant Professor in the School of Engineering at Liberty University, specializing in network reliability, interdomain routing, and software-defined networking. His research addresses challenges in next-generation internet architectures, network performance measurement, and secure IoT device management. Education: B.E. in Electrical and Computer Engineering from Zhejiang University (China) M.S. in Electrical and Computer Engineering from Yanshan University (China) Ph.D. in Electrical and Computer Engineering from the University of Massachusetts, Amherst Research focuses on: - Detecting transient routing failures and improving network performance through real-time diagnostic systems (e.g., collaboration with AT&T). - Designing scalable addressing schemes for IoT and wireless sensor networks. - Developing intrusion detection systems (e.g., MOCA framework) and network anomaly mitigation techniques. His publications (2015-2023) emphasize network security, routing protocol optimization, and scalable internet architectures. Notable work includes BGP rerouting solutions, real-time routing failure diagnosis, and variable-length addressing for 6LoWPAN. No scientific awards were explicitly listed in the provided texts. Collaborations include Agilent, AT&T, and Intel, focusing on practical network reliability and security solutions. Dr. Wang has advised no listed students or managed grants in the provided texts. His research extends to lab implementations of lightweight routers (SoC-based) and stability-aware protocols for RPL networks.

Le Gruenwaldمشاهده پروفایل

استاد

• Database Management
• Information Privacy and Security
• Mobile and Distributed Databases
• +۹ مورد دیگر

Dr. Le Gruenwald is the David W. Franke Professor and Samuel Roberts Noble Foundation Presidential Professor at the School of Computer Science, University of Oklahoma. She also served as Program Director for Data Management Systems at the National Science Foundation (NSF) and held roles including Director of the University of Oklahoma's School of Computer Science. Her academic journey includes a PhD from Southern Methodist University (1990), an M.S. from the University of Houston, and a B.S. in Physics from the University of Saigon, Vietnam. Research Interests: Her work focuses on Database Management Information Privacy & Security Mobile/Distributed Databases Data Mining Quantum Computing Applications in Databases Outlier Detection in Data Streams Key Projects: Includes NSF-funded research on GPU-accelerated spatial data processing, cloud query optimization, and big data hubs. Notable projects: "Spatial Data Management on GPUs" (2013), "Big Data Innovation Hub for the South" (2015), and quantum data science initiatives (2023). Awards: 2012 NSF Directorate Recognition 2007 Distinguished Alumnus Award (SMU) 2009 ACM Recognition Award 2016-2017 Semantic Big Data Workshop Leadership Advising & Grants: Oversees NSF grants totaling millions, focusing on cyberinfrastructure, ecological forecasting, and medical data analytics. No formal student advisees listed but collaborates extensively with researchers globally. Labs & Teams: Leads initiatives in quantum database optimization, mobile-cloud systems, and GPU-accelerated spatial analytics within OU's School of Computer Science.

Elena Cavagnaroمشاهده پروفایل

استاد

• Sustainable Development
• Sustainability in Hospitality
• Youth Tourism
• +۵ مورد دیگر

Dr. Elena Cavagnaro is a full Professor of Responsible Leadership Development and Sustainability in Tourism at the University of Groningen's Faculty of Governance and Innovation (Campus Fryslân) and a Professor at NHL Stenden University of Applied Sciences. She also holds visiting professorships at the University of Sunderland (UK), University of Bergamo (Italy), and University of Derby (UK). Research Interests focus on multi-dimensional sustainability across social, organizational, and individual levels, with applications in hospitality, youth tourism, and transformative travel. Key Publications (2024–2025) address circular economy frameworks, ethical leadership, digital technology impacts, and behavioral nudges toward sustainability. Expertise includes consulting for hospitality, retail, and healthcare organizations on sustainability strategy implementation and co-authoring two books (e.g., Sustainable Value Creation in Hospitality ). Collaborations span interdisciplinary networks, including Wageningen University and the Louis Bolk Institute, with a focus on sustainable food systems and value co-creation in tourism.