جست‌وجوی استاد و پژوهشگر

• Machine Learning
• Artificial Intelligence for 5G and IoT
• Optical Wireless Communications
• +۱۱ مورد دیگر

Dr. Dehao Wu is a Senior Lecturer in the Department of Computer Science at Bournemouth University, Faculty of Science and Technology. He has previously held research positions at the University of Sussex as a Senior Research Fellow and Sussex Research Fellow, and completed postdoctoral work at Nanyang Technological University, Singapore, and the University of Manchester. Education: Bachelor's in Optical and Information Engineering (2007) M.Sc. in Microelectronics and Telecommunication Engineering (2009) Ph.D. in Optical Wireless Communications, Northumbria University, UK (2013) His research focuses on machine learning and artificial intelligence for 5G and beyond-5G systems , including intelligent network management, optical wireless communications, visible light communications, free space optics, RF communications, indoor high-accuracy positioning, underwater communications, and information-centric networking. He has published over 45 peer-reviewed papers, two book chapters, and holds two patents in indoor positioning technology. His recent publications (2021–2024) span topics such as 6G beamforming using metasurfaces, deep learning for interference mitigation, information resilience in caching networks, and security frameworks in flying ad-hoc networks. These works reflect a strong interdisciplinary trend combining AI, communication theory, and network security. Professional Service: Executive Committee Member, IET RF and Microwave Technical and Professional Networks (TPN) Technical Committee Member, IEEE Conferences Dr. Wu advises no students listed in the profile but is actively involved in collaborative research and professional academic service. He has not received any explicitly mentioned scientific awards. His work is supported through research grants and institutional affiliations, contributing to next-generation communication systems and secure network architectures. Laboratories and Research Groups: While not explicitly named, his research aligns with intelligent communication systems, AI-driven networking, and optical wireless technologies, likely contributing to Bournemouth University’s broader digital and communication research initiatives.

• Internet Security
• Operating Systems
• Programming
• +۱۲ مورد دیگر

Dr. Xiaochun Cheng is a Senior Lecturer in the Department of Computer Science at Middlesex University, School of Science and Technology. Their research spans Internet Security, Operating Systems, and Programming, with a strong focus on cybersecurity, artificial intelligence, and IoT applications. They are actively contributing to both academic and applied research in secure systems and intelligent computing. Research Interests: Dr. Cheng's work is centered on cybersecurity, deep learning, and intelligent systems. Key areas include intrusion detection in IoT, secure communication in autonomous vehicles, medical image analysis using neural networks, and privacy-preserving data sharing in healthcare systems. Their interdisciplinary approach bridges computer science with biomedical and social applications. The recent publications reflect a strong trend toward applying deep learning and hybrid AI models to critical domains such as healthcare (e.g., diabetic retinopathy, melanoma detection), cybersecurity (e.g., malware classification, threat detection), and smart infrastructure (e.g., smart buildings, UAVs). These works often combine advanced neural architectures with real-world constraints like resource limitations and data privacy. Scientific Contributions: Dr. Cheng has contributed significantly to journals such as IEEE Transactions on Intelligent Transportation Systems, Computers & Security, PLoS ONE, and Applied Sciences. Their collaborative research spans multiple continents and disciplines, including computer science, public health, and bioinformatics. Grants and Advising: While specific grants and students are not mentioned in the provided text, Dr. Cheng's extensive publication record suggests active research supervision and project leadership. They likely mentor students in AI, cybersecurity, and software engineering, and may be involved in funded projects related to secure IoT and intelligent transportation systems. Laboratories and Teams: Dr. Cheng appears to be part of a multidisciplinary research group at Middlesex University focused on intelligent systems and cybersecurity. Their collaborations with researchers in blockchain, cloud computing, and medical AI suggest involvement in a dynamic, cross-functional research environment.

• Air Transport
• Aviation Management
• Airline Business Models
• +۱۲ مورد دیگر

Professor Zheng Lei is a Professor of Aviation at Swinburne University of Technology, School of Engineering, where he serves as Chair of the Department of Aviation within the Faculty of Science, Engineering and Technology. He holds a PhD in Air Transport and Tourism Management from the University of Surrey and has previously held academic roles at the University of Surrey and Cranfield University. He also serves as a Visiting Professor at the Civil Aviation University of China and is the founder and President of the Institute for Aviation Research, a think tank focusing on aviation in China. His research expertise lies in airline business models, air transport market analysis, regulation and policy, and aviation’s role in regional competitiveness. His work emphasizes real-world impact, advising airlines, airports, regulators, and aviation authorities globally. His fields of research include transportation, logistics, supply chains, and urban and regional planning. The 15 most recent publications reflect a consistent focus on aviation economics, policy, and digital transformation. Key themes include aviation resilience during the pandemic, market liberalization, airline competition, digital technologies like AI and blockchain, service quality assessment via NLP, and sustainable connectivity. His work employs advanced econometric, modeling, and data analytics methods to inform policy and industry practice. Professor Lei has secured significant external research funding from government and industry, including grants from the Department of Foreign Affairs and Trade, Department of Infrastructure, and Civil Aviation Safety Authority, focusing on hydrogen in aviation, alternative fuels, and advanced air mobility. He actively supervises PhD and Master’s students on topics such as hydrogen adoption, autopilot liability, advanced air mobility, airport security, and pilot success prediction, demonstrating a strong commitment to training the next generation of aviation professionals. He has led or contributed to numerous research projects and contracts, including 'Hydrogen to the Skies' and 'Regional AAM Surrogate Trial,' working with partners such as Textron Systems and government agencies. His leadership in both academic and applied research underscores his role as a key figure in contemporary aviation studies.

• Hydrology
• Alpine Hydrology
• Snow Hydrology
• +۵ مورد دیگر

Matthias Bernhardt is an Associate Professor at the University of Natural Resources and Life Sciences, Vienna (BOKU), affiliated with the Department of Water-Atmosphere-Environment and the Institute of Hydrology and Water Management. His research focuses on alpine hydrology, snowpack modeling, and remote sensing applications in mountainous regions. Academic Rank: Associate Professor Institution: University of Natural Resources and Life Sciences, Vienna (BOKU) Department: Institute of Hydrology and Water Management Email: matthias.bernhardt@boku.ac.at ORCID: 0000-0001-5503-7925 His research interests center on hydrological processes in alpine environments, particularly snow dynamics, snow cover heterogeneity, and meltwater generation. He employs physically based models such as Alpine3D, SNOWPACK, and Crocus, and integrates remote sensing technologies including GNSS and UAS for monitoring snow properties and energy fluxes. His work contributes to improving snow management in ski resorts and understanding climate change impacts on water resources. The recent publications highlight a strong trend in using advanced modeling and remote sensing techniques to study snow hydrology. Key themes include physically based snowpack simulation, GNSS-based snow monitoring, spatially distributed heat flux estimation, and the application of satellite and terrestrial imaging for snow cover mapping. These efforts are often applied in high-alpine terrains and support climate adaptation strategies in mountain regions. Scientific recognition includes: Complementary EGU member for the calendar year 2012 in appreciation of activities in respect to the EGU Dr. Bernhardt has been actively involved in advising and presenting research, with numerous conference presentations at EGU and AGU. His work often involves collaboration with international research teams and participation in projects like PROSNOW, which aims to optimize snow management in Alpine ski resorts. He has contributed to studies on evapotranspiration trends and turbulent heat flux modeling using UAV-based thermal data, demonstrating a broad expertise in environmental monitoring and modeling. He leads research using cutting-edge technologies such as GNSS remote sensing and unmanned aerial systems (UAS) for environmental observation. His team applies these tools in high-alpine stations to monitor snow water equivalent, liquid water content, and land surface temperature, supporting both scientific understanding and practical applications in water resource management.

Diana Kingمشاهده پروفایل

پژوهشگر ارشد

• Antarctic ecology
• Remote sensing
• Conservation biology
• +۵ مورد دیگر

Dr Diana King is a research-focused Antarctic ecologist and Deputy Program Manager of the ARC Special Research Initiative Securing Antarctica's Environmental Future (SAEF) at the University of Wollongong (UOW), Australia. She is based within the School of Earth, Atmospheric and Life Sciences (SEALS) and contributes to both research and large-scale program leadership in Antarctic science. Education & Training: BEnvSc (Hons) in Life Sciences, University of Wollongong (2004–2010) PhD in Ecology, University of Wollongong, School of Biological Sciences (2010–2018) Thesis: Monitoring Antarctic bryophyte communities in a time of change Research Interests: Dr King’s research integrates remote sensing , unmanned aerial systems (UAS) , and machine learning to monitor and understand Antarctic terrestrial ecosystems. Her work spans: Development of automated methods to identify Antarctic plants from field photographs. Use of multispectral and thermal sensors on drones to assess moss and lichen health. Landscape-scale mapping of vegetation responses to rapid climate change and extreme events such as Antarctic heatwaves. Design of biodiversity monitoring protocols for the Antarctic Near-shore and Terrestrial Observing System (ANTOS). Scientific Service & Leadership: Deputy Program Manager, ARC Special Research Initiative Securing Antarctica's Environmental Future (SAEF) (2021–present) EDI Champion for SAEF; member of the SCAR EDI Action Group Peer reviewer for Austral Ecology , International Journal of Geo-Information , and Remote Sensing Grants & Funding: ECO-ANTARCTICA – Antarctic-wide observing system for near-shore and terrestrial ecosystems (UOW Global Challenges, 2018) Drones @UOW – Strategic seed funding for UAV-based research (UOW, 2017) Labs & Teams: Dr King works within the SAEF consortium, a multi-institutional partnership that unites over 30 Australian and international organisations to forecast environmental change and secure Antarctica’s future as a natural reserve devoted to peace and science. Her activities are tightly integrated with UOW’s Centre for Sustainable Ecosystem Solutions and the SEALS remote-sensing and ecology groups.

Hannah Williamsمشاهده پروفایل

پژوهشگر

• Movement Ecology
• Bio-logging
• Animal Behavior
• +۵ مورد دیگر

Dr. Hannah Williams is a Movement Ecologist and Affiliated Scientist at the Max Planck Institute of Animal Behavior , where she investigates soaring bird behavior using bio-logging, UAVs, and simulation modeling. She is affiliated with the University of Konstanz and leads research within the Research Group Safi under the Department of Migration . Current Focus: Social eavesdropping in soaring birds, mapping airflow landscapes through conspecific behavior Previous Institutions: Swansea University (postdoc), University of Exeter (MSc), University of St Andrews (BSc) Research Interests center on movement ecology, animal behavior, and bio-logging. Her work explores how soaring birds use social and environmental cues for navigation, combining field data with computational modeling to decode dynamic movement strategies. Publications (2015-2019) demonstrate expertise in bio-logging technology, flight energetics, and social information theory. Key themes include thermal soaring mechanics, movement pattern recognition, and ecological data visualization tools.

• Cybersecurity
• Wireless Sensor Networks
• Smart Grid Security
• +۷ مورد دیگر

Dr. Yee Wei Law is a Senior Lecturer at the University of South Australia's (UniSA STEM) Mawson Lakes Campus. His research expertise spans cybersecurity, machine learning, and wireless sensor networks, with a focus on secure communication systems and autonomous vehicle localization. He serves as a Research Degree Supervisor and actively contributes to publications in IoT security, space systems, and privacy-preserving technologies. Research Trends : Recent work emphasizes domain adaptation for predictive maintenance, adversarial attack analysis in computer vision, and quantum key distribution for satellite-IoT networks. Key themes include security in smart grids, UAV-based gesture recognition, and collaborative privacy-preserving algorithms. Publications highlight interdisciplinary applications of machine learning in fault diagnostics, cloud detection via satellite, and secure networking protocols. His work bridges theoretical advancements with real-world implementations in hypersonic tracking and RFID security.

• Strategic Management
• Organizational Behavior
• Stress Management
• +۱۱ مورد دیگر

Associate Professor Semih Soran is affiliated with Özyeğin University's Faculty of Aviation and Aeronautical Sciences, where he chairs the Department of Professional Flight. He earned his bachelor's degree in Industrial Engineering from the Turkish Military Academy in 1998, followed by master's degrees in Management and Organization from İnönü University (2004) and International Relations from Selçuk University (2006), and a Ph.D. in Management and Organization from İnönü University in 2011. Bachelor's: Industrial Engineering, Turkish Military Academy (1998) Master's: Management and Organization, İnönü University (2004); International Relations, Selçuk University (2006) Doctorate: Management and Organization, İnönü University (2011) His research focuses on strategic management, stress and emotion dynamics in organizational performance, pilot training, crew resource management, and aviation-related technological innovations. He also provides consultancy on mobile mapping, UAV-based mapping, and web-based GIS platforms. With a background as a flight instructor in the Turkish Army Aviation Academy from 1999 to 2011, he accumulated 3,000 flight hours. His work bridges aviation practices with organizational and strategic management theories.

• Structural Geology
• Geodynamics
• Seismotectonics
• +۷ مورد دیگر

Carmelo Giovanni Monaco is a Full Professor of Structural Geology and Geodynamics at the Department of Biological, Geological, Environmental Sciences, University of Catania. Born in Catania on January 15, 1963, he has established himself as a leading expert in structural geology, seismotectonics, and active tectonics with over 180 scientific publications. His research spans from field-based structural analysis to advanced geophysical and remote sensing techniques, focusing on the Mediterranean region, particularly Sicily, Calabria, and Crete. Degree in Geological Sciences with honors from University of Catania (1981-1986) PhD in Tectonics and Structural Geology at University of Camerino (1988-1992) Researcher of Geology at Catania University (1992) Associate Professor (1998) Full Professor (2002) Monaco's research initially focused on structural geology and regional tectonics of collisional systems with thrusts and folds, evolving toward morphotectonics and active tectonics. His work examines Quaternary structures, Pleistocene marine terraces, and paleo-shorelines to understand uplift rates and active fault contributions to regional deformation. Recent research extends to geo-archaeology of Mediterranean sites and geological risk assessment along coastal areas related to sea-level rise and tsunamis. He has led extensive geological mapping projects including the Italian Geological Map at 1:50,000 scale for multiple regions. His publication record shows consistent output with significant recent contributions in active fault analysis, seismic hazard assessment, and tectonic modeling. The most recent articles demonstrate interdisciplinary approaches combining field geology, geophysics, remote sensing, and archaeological evidence to understand active deformation processes in the Mediterranean. Key themes include the Calabrian Arc subduction system, Ionian slab dynamics, and the relationship between active faults and historical seismicity. Scopus H-index: 42 Google Scholar H-index: 50 Coordinator of multiple PhD programs (2003-2014) Head of Department (2014-2019) Board member of Italian Geological Society (2012-2019) Monaco has supervised numerous PhD students as coordinator of multiple doctoral programs and has been principal investigator for significant research projects including CARG geological mapping initiatives and PRIN research programs on active fault systems. His leadership extends to institutional roles including Department Head and academic senator at University of Catania, as well as participation in national seismic hazard assessment programs. He maintains active research collaborations through CRUST (Inter-University Center for Three-Dimensional Seismic-Tectonic Analysis) and INGV (National Institute of Geophysics and Volcanology), focusing on integrated approaches to understanding active tectonics and seismic hazards in the Mediterranean region.

• Swarm Robotics
• Artificial Intelligence
• Computer Vision
• +۵ مورد دیگر

María del Mar Pujol López is a University Professor at the Department of Computer Science and Artificial Intelligence, University of Alicante, affiliated with the Higher Polytechnic School and the Institute of Computer Research. She has earned 6 teaching quinquenios and 4 research sexenios, demonstrating her dual excellence in teaching and research. Her research focuses on swarm robotics, artificial intelligence, and computer vision. She has directed 4 doctoral theses on topics including artificial swarms, object segmentation, sensor fusion, and morphological primitives. Her recent work explores emergent behaviors in swarm robotics using deep reinforcement learning, UAV deployment strategies, and applications of AI in Industry 5.0 and Smart City contexts. Her publications from the last five years show a consistent research trajectory in swarm intelligence with increasing applications in real-world scenarios. She has published in journals like IEEE Access, Advanced Robotics, and Scientific Reports, demonstrating interdisciplinary impact across computer science, robotics, and smart city applications. Professor Pujol López has coordinated multiple research projects including 'Comportamientos Inteligentes Multitarea de Enjambres Adaptativos' (2019-2021) and 'Adaptación y Autoensamblado Morfológico en Sistemas de Enjambre Inteligentes' (2010-2013). She has also participated in educational innovation projects like the Erasmus+ Eurobotique initiative. She teaches various courses including Statistics, Data Processing for Information Systems, and Computer Manufacturing Models across multiple computer engineering degrees. Her teaching methodology incorporates flipped classroom approaches and continuous assessment with online quizzes, reflecting her commitment to educational innovation within the European Higher Education Area framework.

• Computer Networks
• Wireless Communication
• Unmanned Aerial Vehicles (UAVs)
• +۳ مورد دیگر

Talip Tolga Sarı is a Research Assistant at the Department of Computer Engineering , Istanbul Technical University , where he has been affiliated since 2019. He holds a PhD in Computer Engineering (2021), a Master's in Computer Engineering (2018), and dual Bachelor's degrees in Computer Engineering and Electronics & Communication Engineering (2015). Education PhD in Computer Engineering, Istanbul Technical University (2021) Master's in Computer Engineering (2018) Bachelor's in Computer Engineering (2015) Bachelor's in Electronics & Communication Engineering (2015) Research interests span Computer Networks , Wireless Communication , and Unmanned Aerial Vehicles (UAVs) , with a focus on semantic communication , UWB localization , and topology control for resilient networks. His recent publications address UAV swarm coordination , smart campus frameworks , and assisted localization systems , reflecting interdisciplinary applications of computer science in real-world problems. Key trends in his 15 most recent articles include decentralized UAV networks, semantic communication architectures, and UWB-based indoor positioning. His work combines machine learning, cross-layer routing, and software-defined networking paradigms, with citations spanning Computer Science , Robotics , and Network Security . Awards : Highest Performance Award, Istanbul Technical University (2025)

• Information Systems
• Modeling and Simulation
• Artificial Intelligence
• +۳ مورد دیگر

Dr. Erke Arıbaş is a Lecturer at Istanbul Technical University's Faculty of Computer and Informatics , specializing in the Department of Computer Engineering . His research spans interdisciplinary domains including artificial intelligence, simulation modeling, and biophysics applications. Education: PhD in Computational Science and Engineering (2001-2013), Istanbul Technical University MA in Information Systems Design and Management (2001), Istanbul Technical University (Evening Education) BS in Physics (1992-1996), Istanbul Technical University BS in Physics (1996-2000), University of Missouri-Rolla His research focuses on generative AI applications , autonomous systems , and multi-phase flow simulations with thermal modeling. He has contributed to fields ranging from smart city cybersecurity to biomechanical modeling of blood flow. Article trends show expertise in AI-personality modeling integration , unmanned aerial vehicle design , and biofluid dynamics with specialized focus on red blood cell aggregation and arterial hemodynamics.

Philippe Giguèreمشاهده پروفایل

دانشیار

• Mobile Robotics
• Deep Learning
• Computer Vision
• +۴ مورد دیگر

Philippe Giguère is an Associate Professor at the Department of Computer Science and Software Engineering, Faculty of Science and Engineering, Laval University. His research focuses on mobile robotics , sensor fusion , and deep learning for autonomous systems in challenging environments (forests, underwater, harsh weather). He leads projects in 3D localization, terrain identification, and robotic perception. Labs : Norlab, DAMAS Affiliations : Centre de recherche en robotique, vision et intelligence machine (CerVIM), Institut Intelligence et Données (IID), CRDM (Big Data Center) His teaching includes courses on deep learning and mobile robotics . Publications cover SLAM , sensor calibration , and autonomous navigation . He works with MATLAB, Python, and ROS frameworks.

• Photogrammetry
• Remote Sensing
• 3D Modeling
• +۵ مورد دیگر

Heikki Kauhanen is a researcher at Aalto University's Department of Built Environment. His work focuses on photogrammetry, remote sensing, and 3D modeling applications in urban environments. Collaborates on projects involving UAV photogrammetry and LiDAR Develops 3D visualization tools for environmental analysis Specializes in integrating geospatial datasets for urban vegetation monitoring Recent projects include biomass estimation for urban trees in Helsinki, multitemporal change detection in built environments, and cost-efficient survey drone development. His research bridges computational methods with practical urban planning challenges.

• Data-Driven Decision-Making
• Industrial Statistics
• Reliability Engineering
• +۳ مورد دیگر

Qiuzhuang Sun is a Lecturer in the School of Mathematics and Statistics at the University of Sydney. His research focuses on data-driven decision-making, industrial statistics, and reliability engineering, with applications in healthcare, transportation, and sustainable urban systems. Alma Mater: Joint B.Eng. in Industrial Engineering and Computer Science from Shanghai Jiao Tong University; Ph.D. in Industrial Systems Engineering from National University of Singapore His research interests include: Data-Driven Decision-Making for healthcare, emergency response, and preventive maintenance Applied data science and machine learning for transportation data, clinical data, and megacity sustainability Reliability engineering with emphasis on anomaly detection, degradation modeling, and prognostic health management Recent publications highlight advancements in degradation modeling, robust optimization, and healthcare system design, reflecting interdisciplinary collaborations in industrial engineering, statistics, and biomedical research. His work aligns with the Faculty of Science's research strengths in Data and Decisions, Precision Health, and Sustainable Systems. Scientific accolades include: Finalist, IISE Data Analytics & Information Systems Case Study Competition (2024) First Place, INFORMS Blue Summit Supplies Data Mining Challenge (2023) Best Student Paper Award, INFORMS Society on Location Analysis (2023) Best Paper Award, INFORMS Conference on Quality, Statistics, and Reliability (2023) Winner, INFORMS QSR Industrial Data Challenge Competition (2022) ISE Magazine Featured Article (2020) Excellent Paper Award, Operations Research Society of China Reliability Chapter (2019) He supervises students in projects related to reliability engineering and data-driven decision-making. His work integrates statistical modeling, machine learning, and industrial systems optimization.