جست‌وجوی استاد و پژوهشگر

Michael Thielمشاهده پروفایل

پژوهشگر

• Remote Sensing
• Climate Change
• Agricultural Land Use
• +۴ مورد دیگر

Dr. Michael Thiel is a Senior Scientist at the Chair of Remote Sensing at Julius-Maximilians-Universität Würzburg, affiliated with the Philosophische Fakultät and the Department of Remote Sensing within the Institute of Geography and Geology. His academic career includes leadership roles in projects like WASCAL, TelePAtH, and AgriSens DEMMIN 4.0, focusing on climate change impacts in West Africa, remote sensing applications for agriculture, and urban development analysis. He holds a PhD in Remote Sensing from the University of Trier (2013), specializing in SAR data texture analysis for urban area characterization. His research integrates satellite data with geospatial tools to study land use dynamics, climate adaptation strategies, and environmental conservation across Africa and Central Asia. Key research areas include: Climate change impacts on agriculture and urban systems Remote sensing of land cover/land use changes Satellite-based monitoring of soil sealing and impervious surfaces GIS applications for sustainable resource management Decision support systems for climate-resilient agriculture His 2025 publications highlight advancements in spatial decision support systems for West African agriculture, climate adaptation strategies in urban areas, and the use of Earth observations to assess maize cropping systems' vulnerability to climate variability. Recent work also addresses rural industrialization effects on migration patterns and biodiversity conservation. Dr. Thiel is affiliated with organizations like the African Studies Association Germany and serves on the advisory board of the AWARD - One Planet Fellowship. He contributes to international collaborations such as the Climate Change and Land Use Graduate School at Kwame Nkrumah University of Science and Technology (Ghana). His research outputs include over 50 peer-reviewed articles since 2007, focusing on remote sensing techniques for environmental monitoring, urban dynamics analysis, and agricultural sustainability in developing regions.

Wlodek Kuleszaمشاهده پروفایل

استاد

• Systems Engineering
• Measurement and Instrumentation
• Sensor Networks
• +۳ مورد دیگر

Wlodek Kulesza is a Senior Professor in the Department of Mathematics and Natural Sciences at the Blekinge Institute of Technology in Karlskrona, Sweden. He has held academic positions since 2001, including a Professorship in Multi-sensor Systems since 2007. Research: Multisensory systems for health and security applications Teaching: Research Methodology, Philosophy of Science, and Sensors Signals and Systems Expertise: Systems engineering, sensor fusion, IoT, and measurement data handling Research Focus : His work in systems engineering emphasizes multisensor integration for applications spanning healthcare, security, wind energy safety, and subsea cable monitoring. He has pioneered approaches to stereovision calibration, localization algorithms, and real-time safety systems. Awards : Andy Chi Best Paper Award (2009, IEEE Transactions in Measurement and Instrumentation) Collaborations : Visiting Professor at Chinese and Polish universities, with extensive cross-border educational workshops and remote lab federations (e.g., PILAR/VISIR projects).

Visa Koivunenمشاهده پروفایل

استاد

• Statistical Signal Processing
• Wireless Communications
• Multisensor Systems
• +۴ مورد دیگر

Visa Koivunen is a Distinguished Professor of Signal Processing at Aalto University (since 1999), with positions as Academy Professor (2010) and Aalto Distinguished Professor (2020). He holds an honorary D.Sc. (Tech.) from the University of Oulu and has held visiting roles at Princeton University, the University of Pennsylvania, and EPFL. His research focuses on statistical signal processing, wireless communications, radar systems, and integrated sensing and communications (ISAC). He has published over 490 papers, including award-winning works, and advised 31 doctoral theses. Key roles include leadership in conferences (e.g., Asilomar 2018 General Chair) and technical committees (IEEE SPS). Recognitions include the EURASIP Technical Achievement Award (2015), IEEE Signal Processing Society Best Paper Awards (2007, 2017), and EURASIP Fellow status (2020). He co-chairs NATO panels on cognitive radars and ISAC. His research interests span signal processing fundamentals and applications in radar, communications, and machine learning. Recent work emphasizes ISAC, reinforcement learning for resource allocation, and causal inference in federated systems. He has pioneered waveform design techniques using GANs and Bayesian methods for spatial signal analysis. Educations: D.Sc. (Tech.) with honors from the University of Oulu (1994), Primus Doctor Award (1989-1994). Awards: IEEE Fellow, EURASIP Fellow, Member of Academia Europaea. Service: Associate Editor for IEEE Transactions, Chair of IEEE SPAWC and Asilomar conferences. His work bridges theory and practice, addressing challenges in radar-communication coexistence, energy-efficient edge computing, and secure distributed inference. He has delivered over 50 invited talks globally and actively contributes to NATO initiatives on cognitive radar systems.

Miina Rautiainenمشاهده پروفایل

استاد

• Remote Sensing
• Forest Sciences
• Peatland Ecology
• +۵ مورد دیگر

Miina Rautiainen is a Full Professor in Remote Sensing at Aalto University, leading the Remote Sensing Research Team in the Department of Built Environment, School of Engineering. She holds dual professorships in Geoinformatics and the Department of Built Environment. Her research focuses on remote sensing and spectroscopy of forests and peatlands, with emphasis on albedo dynamics, vegetation structure, and climate change impacts. She has led major projects including the ERC Consolidator Grant (2018-2024) and multiple Research Council of Finland grants. Education: Doctoral degree in Forest Sciences from the University of Helsinki (2005). Completed university pedagogy studies in the Faculty of Behavioural Sciences, University of Helsinki. Research interests span remote sensing methodologies, forest ecology, peatland monitoring, and spectral analysis. Key projects include PEATSPEC (spectral characterization of boreal peatlands), ARTISDIG (digital twins for forest biodiversity), and BOREALITY (albedo-climate linkages). Awards include ERC funding and leadership in Finnish Society for Forest Sciences (2017-2020). Publications emphasize spectral modeling, LiDAR applications, and climate-relevant vegetation dynamics. Supervised 8 doctoral theses including work on LiDAR-based biomass estimation, peatland rehabilitation, and wolverine habitat analysis. Team members include researchers like Aarne Hovi, Jussi Juola, and Iuliia Burdun. Labs/Teams: Remote Sensing Research Team at Aalto, collaborating with VTT, Natural Resources Institute Finland, and international partners. Instrumentation includes spectral measurement devices, terrestrial LiDAR, and lab setups for leaf analysis.

Claas Nendelمشاهده پروفایل

استاد

• Agroecosystem Modelling
• Climate Change Impact Assessment
• Crop Simulation
• +۳ مورد دیگر

Prof. Claas Nendel is a Professor at the Leibniz Centre for Agricultural Landscape Research (ZALF), leading the Ecosystem Modelling and Landscape Modelling groups within Research Area 4 'Simulation and Data Science'. His work focuses on agroecosystem dynamics, climate change impacts, and crop modelling integration with remote sensing data. Research interests include: Simulation of crop-water-nutrient interactions Climate adaptation strategies for European agriculture Remote sensing applications in agricultural monitoring He has pioneered the MONICA model for agroecosystem simulation and contributed to AgMIP global crop modelling initiatives. Recent studies emphasize soybean and wheat system resilience under climate change, irrigation mapping via satellite fusion, and drought risk assessments. Awards include his role as Past ESA President (European Society for Agronomy). Key projects involve: Intercropping systems optimization Grassland mowing detection via Sentinel time series Soil organic matter dynamics under no-till practices His work bridges field experimentation with large-scale modelling to address agricultural sustainability challenges.

• Sensor Technologies
• Innovation Management
• Entrepreneurship Ecosystems
• +۳ مورد دیگر

Tamara Papić is an Assistant Professor at Singidunum University in Belgrade, specializing in Innovation Management and Entrepreneurship. She holds a Ph.D. in Sensor Technologies from Jožef Stefan International Postgraduate School (Slovenia) and a Master's in Quality Management from Fakultet organizacionih nauka. Her research focuses on sensor technologies, dyslexia detection through eye-tracking, and the application of AI in education and marketing. Key academic contributions include developing sensor-based systems for analyzing reading patterns in children with dyslexia, leveraging machine learning models like VGG16 and autoencoders. She co-founded BabyFM, a startup creating smart thermoregulation devices for infants using sensors and mobile apps. Her work has been supported by grants from Innovation Forum Cambridge, Star Tech, and Serbia’s Innovation Fund. Professionally, she produced RTV Serbia’s entrepreneurial series 'My Hero' and 'Golden Idea,' and organized national startup competitions. She chairs strategic conferences like Smart City SEE and Belgrade Strategic Dialogue, promoting innovation ecosystems. Her cross-disciplinary projects bridge engineering, education, and business strategy.

• Optical Metrology
• Coherent Metrology
• Holography
• +۷ مورد دیگر

Dr. Vivi Tornari is a Research Fellow and head of the Holography laboratory at IESL/FORTH, specializing in optical metrology and cultural heritage preservation. She has held this position since 1996 and has coordinated major EU projects such as E-RIHS and CHARISMA . Her work focuses on developing holographic interferometry techniques for structural diagnosis of artworks, fraud detection, and environmental impact assessment. She holds a PhD in Applied Science from the University of Sunderland and has authored over 70 scientific publications. Education: Postdoctoral Fellow in Optical Holography, Royal College of Art (RCA), London (1990) PhD in Applied Science, University of Sunderland, UK (2009) MSc in Chemical Engineering/Material Science, National Technical University of Athens (1996) Research interests include laser-based structural analysis, speckle interferometry, and the integration of optical methods for heritage preservation. She has pioneered non-invasive diagnostic tools such as the Applied Holography Metrology Laboratory and has advised on EC projects as an evaluator. Funding highlights include: Leadership in EU projects totaling over €20M Coordinator of SYDDARTA (FP7) and CLIMATE FOR CULTURE (FP7) PI for HOLOAUTHENTIC (FP5) and LASERACT (FP6) Her publications emphasize interdisciplinary collaboration, combining optical engineering with conservation science. Key innovations include: Development of DHSPI (Digital Holographic Speckle Pattern Interferometry) Integration of thermography with interferometry for defect analysis Laser ablation studies on polymer substrates Labs/Teams: Lead the Holography Lab at IESL, collaborating with international institutions like the V&A Museum and Imperial College London. Current projects focus on European research infrastructures (E-RIHS) and climate change impacts on heritage materials.

Yuri Rzhanovمشاهده پروفایل

استاد پژوهشی

• 3D Modeling
• Visualization
• Artificial Intelligence
• +۷ مورد دیگر

Yuri Rzhanov is a Research Professor at the Center for Coastal and Ocean Mapping at the University of New Hampshire , where he focuses on numerical modeling and image processing for marine applications. His work bridges semiconductor physics foundations with modern underwater 3D scene reconstruction and habitat classification. Education : Ph.D. in Semiconductor Physics, Academy of Science of Russia M.S. in Semiconductor Physics, Novosibirsk State University Research Interests center on 3D modeling/visualization , underwater image processing , refractive effect compensation , and benthic habitat classification using conventional/multispectral imagery. His career evolved from semiconductor quantum effects to solid-state nonlinear phenomena, then to marine signal/image processing. Key Collaborators : Co-investigators: Larry Mayer, Brian Calder, Jennifer Dijkstra, May-Win Thein Co-authors: John Hughes Clarke, Kim Lowell, Thomas Butkiewicz Grants include projects funded by the US Geological Survey , NOAA , and US Navy (2004–2024) related to seafloor mosaicing, unmanned underwater vehicle coordination, and marine acoustic/image data processing.

DAVID LOPEZ VILARIÑOمشاهده پروفایل

استاد

• Computer Architecture
• Computer Vision
• FPGA Acceleration
• +۳ مورد دیگر

David Lopez Vilariño is a **Professor** at the **University of Santiago de Compostela**, affiliated with the **Department of Electronics and Computing** within the **Faculty of Physics**. He earned his PhD in 2001 with a thesis titled *"Active contours at the pixel level: design and implementation on cellular network architectures,"* advised by Dr. Diego Cabello Ferrer. His research focuses on **Computer Architecture**, **FPGA Acceleration**, **LiDAR Data Analysis**, and **Embedded Systems**, with notable contributions to LiDAR-based applications in urban planning, infrastructure monitoring, and medical imaging. He is part of the **ARQCOMP (Computer Architecture)** and **Artificial Vision** research groups. His work spans topics such as high-performance computing, parallel processing, and hardware optimization for vision-capable systems. Key projects include developing FPGA-based solutions for real-time video surveillance, retinal vessel analysis, and autonomous navigation systems. Publications emphasize **LiDAR data processing**, including algorithms for road detection, power line characterization, and 3D point cloud analysis. He also pioneered tools like the *Open Lidar Visualizer and Analyser* for 3D stereoscopic visualization. His expertise bridges hardware design and software development, particularly in leveraging FPGAs for embedded vision systems. No scientific awards or grants are explicitly listed, but his prolific publication record highlights sustained innovation in computer vision and geospatial technologies. His research team collaborates on projects involving manycore systems, GPU acceleration, and reconfigurable computing architectures.

Yu Liangمشاهده پروفایل

مدرس

• Computer Vision
• Machine Learning
• Image Processing
• +۴ مورد دیگر

Dr. Yu Liang is a Lecturer at the Department of Information Technology and Electrical Engineering at ETH Zürich. His research focuses on advancing computer vision and machine learning techniques, particularly in video generation, image restoration, and event-based systems. He specializes in developing innovative frameworks for tasks like motion-aware video synthesis, low-light image enhancement, and diffusion models applied to multimedia processing. Key research interests include hierarchical information flow architectures, transformer-based networks, and scalable solutions for real-world imaging challenges. His work emphasizes practical applications of generative models and cross-modal fusion techniques to achieve high-quality visual outputs. Dr. Liang has contributed extensively to the field through publications on topics such as Fractal-IR for image restoration, Uni3C for 3D-enhanced video generation, and event-based frame interpolation. His research often bridges theoretical advancements with practical implementations, addressing issues like temporal coherence, motion deblurring, and adaptive illumination estimation. Although no specific academic awards are listed, his prolific publication record (over 20+ papers since 2019) highlights his active role in the academic community. His work has led to impactful datasets like Lsdir and frameworks like SwinIR, demonstrating strong contributions to both methodology and infrastructure in computer vision.

• Wind energy and wildlife interactions
• Bat ecology and behavior
• Offshore wind energy
• +۲ مورد دیگر

Cris Hein serves as a Researcher in Environmental Science at the National Renewable Energy Laboratory (NREL), where he leads the environmental portfolio within the National Wind Technology Center. He coordinates the Bats and Wind Energy Cooperative and acts as operating agent for the International Energy Agency Wind Technology Collaborative Program's Task 34. His educational background includes: Bachelor of Science in Geology from Texas A&M University Master of Science in Biology from Texas State University PhD in Forestry and Natural Resources from the University of Georgia For over two decades, Hein has specialized in bat ecology and behavior, with more than ten years focused on wind energy environmental interactions. His research develops evidence-based strategies to minimize wildlife impacts from wind turbines, particularly through advanced monitoring systems and operational mitigation techniques. Current work emphasizes offshore wind environmental effects and bat fatality reduction protocols across North American wind facilities. Analysis of his 2024-2025 publications reveals three dominant research trajectories: 1) Gulf of Mexico offshore wind environmental assessments, 2) marine mammal monitoring during offshore construction, and 3) validation of curtailment as the most effective bat fatality mitigation strategy. His work consistently bridges ecological research with practical wind industry applications, showing particular expertise in translating field data into operational guidelines. As program coordinator for the Bats and Wind Energy Cooperative, Hein manages multi-stakeholder collaborations between government agencies, industry partners, and conservation organizations. His leadership in IEA Task 34 facilitates international knowledge exchange on wind energy environmental effects, directing research funding toward high-impact conservation solutions. Hein's laboratory operations center on NREL's National Wind Technology Center environmental research group, which conducts field studies at operational wind facilities nationwide. The team specializes in developing monitoring technologies and analyzing wildlife-turbine interaction data to inform industry best practices and regulatory frameworks.

Abhilash Chandelمشاهده پروفایل

استادیار

• Precision Agriculture
• Remote Sensing
• Machine Learning in Agriculture
• +۴ مورد دیگر

Abhilash Chandel serves as an Assistant Professor of Precision Agriculture Technologies and Data Management in the Department of Biological Systems Engineering at Virginia Tech, holding a 50% research and 50% extension appointment since December 2021. His work bridges advanced data analytics with practical agricultural solutions, focusing on optimizing crop production through technological innovation. Dr. Chandel's academic foundation includes: Ph.D. in Biological and Agricultural Engineering from Washington State University (2021) M.Tech. in Farm Machinery and Power Engineering from IIT Kharagpur (2015) B.Tech. in Agricultural and Food Engineering from IIT Kharagpur (2015) His research program centers on precision agriculture technologies, specializing in aerial and satellite remote sensing, machine learning applications for crop monitoring, and data-driven water stress detection. Key innovations include AI-enabled mobile tools for real-time field diagnostics, multispectral imagery analysis for disease identification, and evapotranspiration mapping systems for irrigation optimization. His work addresses critical challenges in water management, yield prediction, and sustainable crop production across diverse agricultural systems. Analysis of Dr. Chandel's publication record reveals consistent advancement in UAS-based crop monitoring, with increasing emphasis on AI integration for real-time decision support. His research spans multiple cropping systems including soybeans, peanuts, wheat, and specialty crops, demonstrating particular expertise in thermal-RGB fusion techniques for physiological stress assessment and machine learning frameworks for yield prediction. Recent work shows expanding applications in disease detection (anthracnose, nematodes) and precision nutrient management. Dr. Chandel's contributions have been recognized through multiple awards including: Graduate Student Leadership Award (WSU, 2021) Walter and Vinnie Hinz Outstanding Graduate Student Award (2020) Winner of Microsoft-WSU Digital Ag-Athon (2020) Multiple travel awards and departmental recognitions during graduate studies Through his extension appointment, Dr. Chandel develops practical resources for Virginia farmers including VCE publications on drone-based nematode assessment, peanut maturity mapping, and multispectral disease diagnosis. His work demonstrates strong collaboration with agricultural stakeholders to translate research into field applications, though specific details of graduate student mentoring or major grant funding were not documented in available sources.

• Forest Inventory
• Forestry
• Biometrics
• +۹ مورد دیگر

Dr. Tim Ritter is a Senior Scientist at the Institute for Forest Growth, University of Natural Resources and Life Sciences Vienna (BOKU), with expertise in biometrics, forest inventory, and laser scanning applications. He earned his Dr. forest. ("summa cum laude") in 2014 from Georg-August-Universität Göttingen, following M.Sc. and B.Sc. degrees in Forest Ecosystem Analysis and Forestry. Research Focus: Terrestrial/Personal Laser Scanning (TLS/PLS) for forest mapping Stochastic corrections for tree non-detection Spatial statistics and 3D forest modeling Deadwood inventory and carbon storage analysis Forest road monitoring and harvesting damage detection Publications Trends: Recent work emphasizes LiDAR integration in forest inventory, automated point cloud analysis, and digital twin development for forest ecosystems. Key methods include machine learning, spatial regression, and multi-sensor data fusion for timber volume estimation and biodiversity assessment. Scientific Awards: 2014: Finding talent: Researcher Career Grant Professional Activities: Editorial Board Member for Frontiers in Forests and Global Change (2023), Topical Advisory Panel for Sustainability (2020), and active reviewer for 15+ journals including Remote Sensing and Forests . Presented 55+ lectures across 5 countries, including keynote speeches at international conferences.

• Robotic Vehicles
• Computational Intelligence
• Cooperative Control and Optimization
• +۳ مورد دیگر

Lefteris Doitsidis is an Associate Professor at the School of Production Engineering and Management, Technical University of Crete. He holds a PhD in Production and Management Engineering from the same institution (2008), with prior academic positions at the Department of Electronics, Hellenic Mediterranean University. His professional journey includes visiting scholar roles at the University of South Florida, USA. Research focuses on robotic systems, including autonomous navigation of UAVs/AUVs, multirobot teams, computational intelligence, and educational robotics. He leads the Intelligent Systems and Robotics Laboratory, developing tools like HYDRA for STEM education and frameworks for industry 4.0 applications such as bin-picking and precision agriculture. His work integrates control systems optimization, energy efficiency in manufacturing, and digital twin technologies. Over 65 publications span journals, conferences, and books, emphasizing practical implementations like ROS-based autonomous vehicle testbeds and energy management systems for electric vehicles. Key contributions include UAV path planning algorithms, swarm robotics coordination, and sensor fusion techniques. Current research trends emphasize sustainability in manufacturing, educational robotics platforms, and autonomous systems validation through advanced algorithms like Deep Deterministic Policy Gradient.

• Robotics
• Smart Manufacturing
• Advanced Materials Processing
• +۹ مورد دیگر

Xiaoqi Chen is an Adjunct Professor in the Department of Mechanical Engineering & Product Design Engineering at Swinburne University of Technology, School of Engineering. He previously served as Deputy Director of the Manufacturing Futures Research Institute and Professor in the same department. Prior to Swinburne, he was Professor and Director of Mechatronics Engineering at the University of Canterbury (2006–2019), and held senior research roles in Singapore and the UK. Education: B.Eng. in Mechanical Engineering, South China University of Technology M.Sc. in Materials Technology, Brunel University, UK PhD in Electrical Engineering and Electronics, University of Liverpool, UK Prof. Chen’s research spans robotics, smart manufacturing, advanced materials processing, additive manufacturing, and autonomous systems . He is a strong advocate for translating research into commercial applications, evidenced by spin-offs like Invert Robotics Ltd. His work integrates intelligent systems with industrial processes to improve efficiency and sustainability. He is deeply involved in the ARC Training Centre for Collaborative Robotics in Advanced Manufacturing, co-leading the Biomimic Cobots program. His recent publications highlight advancements in robotic grinding, fault diagnosis using deep learning, composite materials, and additive manufacturing of superalloys . These works reflect a trend toward intelligent, data-driven, and sustainable manufacturing systems with applications in aerospace, energy, and healthcare. Scientific Awards and Recognitions: Fellow of the Royal Society of New Zealand Fellow of Engineering New Zealand (F.EngNZ) Fellow of Society of Manufacturing Engineers (F.SME) Fellow of American Society of Mechanical Engineers (F.ASME) New Zealand Hi-Tech Start-Up Excellence Award (2012) New Zealand Forest Owners Association Award (2015) Singapore National Technology Award Mechanical Engineering Research Award, University of Canterbury Advising and Grants: Prof. Chen supervises multiple PhD students in areas such as compliant mechanisms, soft robotics, and intelligent fault diagnosis. He is a Chief Investigator on industry-linked grants, including a project on rapidly-deployable soft robotic assistive devices funded by KNW DESIGN PTY LTD. His editorial roles include serving as Associate Editor for IEEE Transactions on Industrial Electronics and IEEE Transactions on Automation Science and Engineering. Labs and Teams: He leads research teams in robotics and advanced manufacturing at Swinburne and is a key figure in the ARC Training Centre for Collaborative Robotics in Advanced Manufacturing. His work bridges academia and industry, focusing on real-world deployment of robotic and intelligent systems.