جست‌وجوی استاد و پژوهشگر

Weidong Xiangمشاهده پروفایل

استاد

• Vehicular Networks
• Wireless Communication Systems
• RFID Technology
• +۷ مورد دیگر

Weidong Xiang is a Professor in the Department of Electrical and Computer Engineering at the University of Michigan-Dearborn's College of Engineering and Computer Science. His research focuses on wireless communication systems, vehicular networks, and cybersecurity innovations for automotive applications. Education: Ph.D. and M.S. in Electrical Engineering from Tsinghua University Research interests span vehicular communication protocols , MIMO/beamforming architectures , RFID security , and ultra-wideband (UWB) systems . He has pioneered work on nonlinear companding, depth-first ML decoding algorithms, and energy-harvesting wireless systems. Recent publications highlight trends in deep learning for wireless sensing , GPS error prediction using LSTMs , and DSRC channel modeling . His work integrates AI and cybersecurity into automotive communication infrastructures. Grant history includes projects funded by: NSA/DoD for cybersecurity-AI integration (2024-2027) Ford Motor Company for MIMO/DSRC systems (2019-2022) NSF grants for vehicular sensing (2015-2016, 2013-2014) DoE funding for smart grid SDR prototypes (2010-2011) He holds a patent for an Enhanced Carrier Frequency Estimator applicable in WiFi, WiMax, and WAVE systems.

Krystyna Michałowskaمشاهده پروفایل

استادیار

• Remote Sensing
• Geomatics
• Material Science
• +۳ مورد دیگر

Dr. Krystyna Michałowska is an Assistant Professor at Gdańsk University of Technology, specializing in remote sensing, geomatics, and material science. Her research spans environmental monitoring, coastal zone analysis, and technical fabric testing, demonstrating interdisciplinary expertise across engineering and environmental sciences. Her research interests focus on: Advanced remote sensing techniques for environmental monitoring Material strength testing using high-speed imaging Coastal zone dynamics and change analysis Soil science with emphasis on erosion processes Geospatial data processing and Web GIS applications Dr. Michałowska's publication record demonstrates consistent research output across multiple domains. Her recent work shows a progression from material science applications toward environmental monitoring, particularly focusing on the Baltic Sea region. She has developed expertise in multispectral imaging techniques and their application to water quality assessment and coastal zone management. Her interdisciplinary approach bridges engineering methodologies with environmental science applications. Her scientific contributions include: Development of fast camera techniques for fabric strength testing Long-term coastal monitoring of the Baltic Sea Analysis of wind erosion impacts on EU soils Advancements in water classification using multispectral imaging Comparative studies of Web GIS applications for 4D modeling

• Coastal Monitoring
• Drone/UAV Technology Applications
• Marine Ecology
• +۵ مورد دیگر

Dr. Blake Allan is a Research Fellow and Scientific Lead of the National Coastal Drone Program at Deakin University's School of Life and Environmental Sciences within the Faculty of Science Engineering and Built Environment. Based at the Warrnambool Campus in Victoria, Australia, he specializes in applying drone technology to coastal and marine environmental monitoring. His work bridges technological innovation with practical environmental management solutions. Dr. Allan's research focuses on coastal erosion monitoring, marine mammal studies, and the development of drone-based methodologies for environmental assessment. His work demonstrates how unmanned aerial vehicles can transform traditional approaches to coastal management, providing high-resolution data at unprecedented scales and frequencies. He has pioneered methods for using both professional and citizen science drone operations to monitor shoreline changes, beach erosion, and marine wildlife populations. His publication record shows a strong emphasis on practical applications of drone technology, with recent work developing erosion indicators, assessing marine mammal health, and creating multi-scale coastal monitoring systems. His research has established that even limited drone datasets can provide valuable insights into coastal dynamics, challenging previous assumptions about data requirements for effective monitoring. Dr. Allan has been instrumental in establishing the Victorian Coastal Monitoring Program, which has directly influenced coastal management practices including the realignment of walking paths for public safety and assessment of sand renourishment projects. His work on waterbird responses to drones has provided critical insights for minimizing disturbance during wildlife surveys. As Scientific Lead of the National Coastal Drone Program, he oversees drone operations across multiple sites in Victoria, Australia, coordinating data collection that spans from 1930s aerial imagery to contemporary drone surveys. His research has demonstrated how citizen science can enhance the scalability and cost-effectiveness of environmental monitoring programs, particularly during challenging circumstances like the COVID-19 pandemic lockdowns.

• Geospatial Information Systems
• Unmanned Aerial Systems Applications
• Laser Scanning Technology
• +۷ مورد دیگر

Prof. Dr. Ulf Kreuziger serves as a Professor in the Department of Geomatics and Geodesy within the Faculty of Electrical Engineering, Media and Computer Science at Ostbayerische Technische Hochschule (OTH) Amberg-Weiden. He holds multiple leadership roles including Lab Manager, Internship Coordinator, and Alumni Coordinator for the faculty. His work focuses on cutting-edge geospatial technologies and their practical implementations across various domains. Prof. Kreuziger's research spans numerous areas within geospatial science with primary interests in Geospatial Information Systems (GIS) , Unmanned Aerial Systems (UAS) applications , Laser Scanning and Point Cloud Processing , Augmented and Virtual Reality in geospatial contexts , and Geospatial Data Processing with Artificial Intelligence . His work bridges traditional geodesy with modern computational approaches, focusing on practical applications for rural development, smart city initiatives, and heritage preservation projects such as the digital reconstruction of the vanished Paulusbrunn village. Current research projects include the GeoDataObjektDetektor (GDOD) initiative evaluating geospatial data with AI methods, deformation monitoring of the Amberg city wall, and development of digital twins for educational institutions. His laboratory team comprises a lab engineer and several research staff members working on diverse geospatial technology applications from UAV-based land modeling to augmented reality implementations for rural development projects across Bavaria. Prof. Kreuziger maintains strong industry connections, collaborating with governmental agencies including Amt für Ländliche Entwicklung, Landratsamt, and engineering firms like fhs ingenieur gmbh on practical geospatial applications. He actively supervises numerous student theses covering topics from precision agriculture using multispectral sensors to AI-driven object recognition in point clouds, with emphasis on real-world problem solving in surveying, land management, and urban planning.

Serdar Çiftçiمشاهده پروفایل

استادیار

• Computer Vision
• Deep Learning
• Image Processing
• +۳ مورد دیگر

Serdar Çiftçi is an Assistant Professor at the Department of Computer Engineering within the Faculty of Engineering at Harran University in Şanlıurfa, Turkey. His academic journey includes a Ph.D. and M.Sc. from Middle East Technical University (METU) and a B.Sc. from Selçuk University. Ph.D. from Middle East Technical University (2017) M.Sc. from Middle East Technical University (2011) B.Sc. from Selçuk University (2007) Visiting Researcher at École Polytechnique Fédérale de Lausanne (2016) Visiting Researcher at Rochester Institute of Technology (2022) Çiftçi's research focuses on computer vision with deep learning approaches, specializing in HDR imaging, super-resolution, image restoration, and visual privacy protection. His HRU-Vision laboratory develops innovative solutions for challenging computer vision problems using state-of-the-art deep learning techniques. His work bridges theoretical advances with practical applications in image processing and analysis. His publication portfolio demonstrates strong trends in deep learning applications for image enhancement and analysis, with particular emphasis on attention mechanisms, transformer architectures, and privacy-preserving techniques. Recent work shows increasing focus on specialized applications including medical imaging, remote sensing, and artistic analysis. Teknofest 2019 Second Best Prize in Health category Middle East Technical University Thesis of the Year Award (2017) MediaEval 2015 Most Distinctive Approach Paper Award Çiftçi has successfully secured multiple research grants including "Privacy Protection for HDR Images" and "Smart Home Project for Eliminating Physical Disabilities Using Eye Tracking" from Harran University HUBAK, and previously participated in TÜBİTAK-funded research. He has advised numerous MSc students through their thesis work, with several achieving recognition in national competitions. His professional service includes extensive journal and conference reviewing activities across major computer vision venues. The HRU-Vision laboratory, led by Çiftçi, specializes in computer vision problems using deep-learning-based approaches, with active projects in HDR imaging, super-resolution, image restoration, and visual privacy protection. The lab maintains strong connections with international research groups including METU and EPFL.

Danielle Griegoمشاهده پروفایل

مدرس

• Building Integrated Solar Photovoltaics
• Building Energy Efficiency
• Participant-Driven Behavior Change via Mobile Apps
• +۳ مورد دیگر

Dr. Danielle Griego is a Lecturer at ETH Zurich's Department of Civil, Environmental and Geomatic Engineering and Executive Director of Design++, an interdisciplinary initiative fostering collaboration across 6 departments and over 20 professors. She holds a Ph.D. from ETH Zurich (2020), focusing on building-integrated solar photovoltaics and energy efficiency through participant-driven mobile apps. Her work bridges architecture, engineering, and sustainability, with prior roles including leading Singapore’s EcoCampus program at NTU. Her research emphasizes energy-efficient building design, community solar policy, and smart urban technologies. Education: Ph.D. in Architecture and Building Systems (ETH Zurich, 2020) M.Sc. Civil Engineering (University of Colorado Boulder, 20XX) B.Sc. Architectural Engineering (University of Colorado Boulder, 20XX) Her research interests include sustainable urban energy systems, behavioral change via technology, and the integration of renewable energy into built environments. She leads Design++ to advance interdisciplinary projects with industry partners, addressing real-world challenges in energy efficiency and smart cities. Grants & Advising: No formal advisee list provided, but actively involved in supervising Design++ initiatives and teaching courses related to building energy systems and sustainable design. Labs/Teams: Design++ at ETH Zurich serves as a central hub for cross-disciplinary research and education in design innovation and sustainability.

Laura Schalbetterمشاهده پروفایل

پژوهشگر

• Virtual Reality Applications in Rehabilitation
• Landscape and Urban Systems Planning
• Peri-urban Landscape Design
• +۳ مورد دیگر

Laura Schalbetter is a researcher at the Chair of Planning of Landscape and Urban Systems (PLUS) within ETH Zürich's Department of Civil, Environmental and Geomatic Engineering (D-BAUG). Her work bridges landscape architecture with cutting-edge technology through projects like REGaitVR and GLOBESCAPE , focusing on restorative environments and place-making in transformed landscapes. Education: MSc in Geomatics (ETH Zürich), BSc in Geomatic Engineering and Planning (ETH Zürich) Research interests center on virtual reality applications for gait rehabilitation, eye-tracking analysis in outdoor environments, and geospatial data integration in urban systems. Her work combines high-fidelity 3D environments with motion tracking and GIS technologies. Key publications analyze VR's role in therapeutic spaces, gaze-based interaction with geospatial interfaces, and AI-enhanced eye-tracking in landscape analysis. Recent studies examine oxygen supplementation strategies' impact on microbial communities and spatial visualization frameworks for quantum computing. Professional affiliations include: Current PhD student at ETH Zürich (since 2023) Research Assistant at PLUS (2021-2022) Student Assistant at IKG (2020) and IGP (2018-2020)

• Machine Learning
• Computer Vision
• Computational Physics
• +۳ مورد دیگر

Jiawei Guo is a researcher at National Central University's Department of Electrical Engineering. His work spans multiple disciplines including machine learning, computer vision, and computational physics. Key affiliations: National Central University, Taoyuan, Taiwan Research focus: Neural network applications in energy systems, underwater depth estimation, and mobile app security His research integrates physics-informed neural networks for solving complex engineering problems and adversarial transformers for pattern detection in acoustic signals. Recent publications demonstrate expertise in 3D modeling , multimodal reasoning , and privacy-compliant software analysis . Article trends show strong emphasis on diffusion models for medical imaging, spatial-temporal analysis for Gaussian processes, and data pruning techniques for efficient computation. While no formal awards are listed, his collaborative work appears in top venues including ACL , ICML , and IEEE Access .

B.S. Manjunathمشاهده پروفایل

استاد

• Image/Video Analysis
• Multimedia Databases
• Steganography
• +۳ مورد دیگر

B.S. Manjunath is a Professor in the Department of Electrical and Computer Engineering at the University of California, Santa Barbara (UCSB). He serves as Director of the Center for Multimodal Big Data Science and Healthcare and the Center for Bio-image Informatics. His research focuses on image/video analysis, multimedia databases, steganography, and bio-informatics. Manjunath holds a Ph.D. from the University of Southern California (1991), M.E. from Indian Institute of Science (1987), and B.E. from Bangalore University (1985). He is an IEEE Fellow and ACM Fellow. Education: Ph.D. (1991), Signal & Image Processing Institute, EE-Systems, USC M.E. (1987), Systems Science and Automation, Indian Institute of Science B.E. (1985), Electronics Engineering, Bangalore University Research Interests: Image/video analysis (segmentation, registration, texture analysis) Multimedia databases and data mining Steganography and digital forensics Signal/image processing for bio-informatics His work includes developing the BisQue open-source platform for image informatics and leading NSF-funded initiatives in bio-image informatics and interactive multimedia. Key Contributions: Over 300 peer-reviewed publications 24 patented technologies Co-editor of the ISO/MPEG-7 multimedia standard Founder faculty of the Media Arts and Technology Program Awards and Affiliations: IEEE Fellow (2025) and ACM Fellow (2025) Affiliated with UCSB’s Computer Science Department and Dynamical Neuroscience Program Former Director of the NSF-sponsored Interactive Digital Multimedia IGERT program Labs and Platforms: Director of the Vision Research Lab Lead developer of the BisQue image informatics system Pioneering work in multimodal camera networks and healthcare analytics

• Precision/Digital Agriculture
• Remote Sensing
• Internet of Things (IoT)
• +۵ مورد دیگر

Dr. Dharmendra Saraswat is a Professor in the Department of Agricultural & Biological Engineering at Purdue University, College of Engineering. His research focuses on precision agriculture, remote sensing, and IoT applications for crop and natural resource management. He holds a Ph.D. from The Ohio State University and has held previous faculty positions at the University of Arkansas and Chandra Shekhar Azad University of Agriculture & Technology. His work bridges engineering and agriculture, emphasizing data science tools, decision support systems, and unmanned aerial systems (UAS). Education: Bachelor’s in Agricultural Engineering, University of Allahabad Master’s in Agricultural Engineering, Indian Agricultural Research Institute (IARI), New Delhi Ph.D. in Food, Agricultural & Biological Engineering, The Ohio State University Research Interests: Dr. Saraswat’s work integrates information technologies with agricultural challenges, including spatio-temporal modeling, machine learning for precision farming, and watershed management. He develops cloud-based tools and mobile applications to enhance agricultural decision-making. His expertise spans remote sensing, GIS, and UAS sensor data analysis. Awards: Fellow of Indian Society of Agricultural Engineers (2014) John W. White Outstanding Extension Award (2014) ASABE Educational Aids Blue Ribbon Award (2015/2013) Excellence in Remote Sensing (2013) Early Career & Innovation Awards (2011) Lab & Collaborations: His research leverages facilities like Purdue’s ADM Agricultural Innovation Center and Discovery Park. He collaborates on projects involving digital agriculture, environmental modeling, and agricultural robotics. Key contributions include disease detection algorithms, UAV-based systems, and climate impact assessments.

Djamila Aouadaمشاهده پروفایل

استادیار

• Computer Vision
• Signal Processing
• Image Processing
• +۳ مورد دیگر

Djamila Aouada is an Assistant Professor and Senior Research Scientist at the University of Luxembourg's Interdisciplinary Centre for Security, Reliability and Trust (SnT), where she heads the Computer Vision, Imaging, and Machine Intelligence (CVI2) research group. She earned her State Engineering degree from École Nationale Polytechnique, Algeria, and PhD from North Carolina State University. Her research spans computer vision, signal processing, pattern recognition, and data modeling. Dr. Aouada leads several national and European projects including FNR FAVE, 3D-Act, and H2020 STARR, focusing on AI-driven solutions for industrial and security applications. She has received four IEEE Best Paper Awards for her contributions. Dr. Aouada has supervised 5 completed PhD theses and currently mentors 5 PhD candidates, while maintaining collaborations with Los Alamos National Laboratory and Mitsubishi Electric Research Labs. She serves as Senior IEEE Member and previously chaired IEEE Benelux Women in Engineering.

• Computer Vision
• Machine Learning
• Remote Sensing
• +۴ مورد دیگر

Min Liu is a Professor at the Institute of Computing Technology, Chinese Academy of Sciences, where they lead research at the intersection of computer vision, machine learning, and remote sensing applications. With an extensive publication record spanning from 1998 to 2025, their work demonstrates significant contributions to multiple scientific domains. Professor Liu's research interests span computer vision, machine learning, remote sensing, image processing, artificial intelligence, and environmental monitoring. Their work uniquely bridges theoretical computer science with practical applications in environmental science, particularly in analyzing climate change impacts, vegetation dynamics, and water resource management. Recent publications reveal a strong focus on applying deep learning techniques to solve complex problems in geospatial analysis and environmental monitoring, with particular attention to Chinese ecosystems and urban environments. Analysis of Professor Liu's recent publications (2023-2025) shows a clear trend toward interdisciplinary research that combines advanced computer vision techniques with environmental science applications. Their work frequently employs deep learning architectures like feature pyramid networks, graph convolutional networks, and self-attention mechanisms to address challenges in remote sensing image analysis, object detection, and environmental monitoring. A significant portion of their research focuses on China-specific environmental challenges, including urbanization impacts on vegetation, salt marsh carbon stock estimation in the Yangtze River estuary, and lake water body extraction from satellite imagery. Professor Liu has made significant contributions across multiple domains including: Environmental monitoring using remote sensing data Deep learning applications for geospatial analysis Computer vision algorithms for object detection and image segmentation Climate change impact assessment through data-driven approaches Ecosystem modeling and analysis Their research demonstrates strong methodological innovation while maintaining practical relevance to pressing environmental challenges, particularly those facing China's rapidly urbanizing landscape and changing ecosystems.

• Computer Science
• Artificial Intelligence
• Machine Learning
• +۸ مورد دیگر

Yong Cheng is a prolific researcher with significant contributions to computer science, artificial intelligence, and mathematical logic. His work spans biomedical image segmentation, federated learning, robotics, and formal logic, reflecting a multidisciplinary approach to solving complex technical challenges. Key Research Areas: Machine Learning, Natural Language Processing, Computer Vision, Remote Sensing, Robotics, Privacy-Preserving Techniques. Publication Trends show a focus on deep learning architectures (e.g., Transformer, U-Net), adversarial training, and applications in healthcare, autonomous systems, and geospatial analysis. His 2025 work on biomedical imaging and logic theorems highlights ongoing interests in theoretical and applied domains. Scientific Contributions include foundational work in Gödel's incompleteness theorems and practical innovations in edge computing and fusion robotics. While no formal honors are listed, his collaborations with institutions like IEEE and ACM suggest industry-wide recognition.

• Integrated Photonics
• Imaging Systems
• Medical Diagnostics
• +۷ مورد دیگر

George Giakos is a Professor and Chair of the Department of Electrical and Computer Engineering at Manhattan College, NY, and Director of the Graduate Program. Previously, he served as a Professor at the University of Akron for over 20 years, directing imaging technologies and surveillance laboratories. His research focuses on imaging systems, photonics, medical diagnostics, and defense applications. Giakos holds a PhD from Marquette University and has authored over 200 peer-reviewed articles, 16 patents, and received prestigious awards including the IEEE Fellow distinction and the 2014 IEEE-USA Professional Achievement Award. Education Ph.D., Electrical & Computer Engineering, Marquette University M.S., Nuclear Physics, Ohio University Postgraduate Diploma, Nuclear Instrumentation, University of Edinburgh Laurea, Applied Physics, University of Turin Research Interests Giakos pioneers advancements in imaging devices and systems, integrating photonics, nanotechnology, and bio-inspired techniques. His work spans medical diagnostics (e.g., cancer detection via polarimetric imaging), defense (space surveillance, autonomous systems), and semiconductor characterization. He emphasizes interdisciplinary innovation, bridging defense and bioscience through novel imaging paradigms. Articles Overview Recent work includes neuromorphic architectures for space IoT, adversarial machine learning in power grids, and interdisciplinary frameworks for systematic innovation. His research often combines AI with domain-specific applications, addressing challenges in healthcare site selection, cybersecurity, and quantum sensing. Awards IEEE Fellow (2014) ONR Distinguished Faculty Fellow (2005) AFRL Space Surveillance Fellowships (2007–2009) NASA Faculty Fellowships (2000, 2001, 2004) Advising & Grants Giakos has secured over $6M in grants as PI, collaborating with AFRL, NASA, and industry partners like Lockheed Martin. His leadership spans IEEE committees, including chairing the TC-19 Imaging Systems Technical Committee and organizing international conferences like IEEE International Conference on Imaging Systems and Techniques. Labs & Teams Directs Manhattan College’s imaging and surveillance laboratories, advancing technologies such as multifusion polarimetric detection and bio-inspired robotic vision systems. His team develops platforms like the AFRL Multifunctional Imaging Surveillance system for defense and medical applications.

Trevor Darrellمشاهده پروفایل

استاد

• Artificial Intelligence
• Computer Vision
• Machine Learning
• +۳ مورد دیگر

Professor Trevor Darrell is a faculty member in the Department of Electrical Engineering and Computer Sciences at UC Berkeley. He leads research in computer vision, machine learning, and robotics, focusing on algorithms for visual recognition and perception-based interfaces. His affiliations include the Berkeley Artificial Intelligence Research Lab (BAIR), Berkeley Center for Responsible, Decentralized Intelligence (RDI), and the International Computer Science Institute (ICSI). Education: PhD, MIT (1996) BSE in Computer Science, University of Pennsylvania (1988) Research Interests: Professor Darrell’s work spans Artificial Intelligence , Computer Vision , Robotics , and Multimodal Learning . His recent efforts emphasize vision-language models, embodied AI, and ethical AI frameworks for healthcare and robotics. Notable Contributions: His articles in 2025 highlight advancements in multimodal generation, humanoid control, and model alignment. Trends include leveraging vision-language integration for robotics tasks and addressing AI bias and hallucination. Awards: ICML Test of Time Award (2024) ACM SIGMM Test of Time Paper Award (2024) CVPR Longuet-Higgins Prize (2024) Labs & Collaborations: Leads BAIR and RDI, advancing responsible AI and geospatial analysis through initiatives like Berkeley Deep Drive and the CITRIS People and Robots (CPAR) program.