جست‌وجوی استاد و پژوهشگر

• 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.

Hametner, Bernhardمشاهده پروفایل

مدرس

• Biomedical Engineering
• Arterial Pressure Modeling
• Cardiovascular Physiology
• +۳ مورد دیگر

Prof. Dr.techn. Bernhard Hametner is a Lecturer at the Institute of Biomedical Engineering (E363) within Technische Universität Wien (TU Wien) . His research focuses on arterial pressure dynamics, cardiovascular physiology, and biomedical signal analysis with applications in clinical diagnostics and space medicine. He leads projects involving wearable medical devices, multisensor monitoring systems, and computational models of vascular systems. Key affiliations: TU Wien's Network Lab and collaborative EU projects like VascAgeNet Expertise in pulse wave analysis, vascular aging, and translational biomedical engineering Research Interests: His work spans arterial stiffness quantification, non-invasive cardiac output estimation, and developing methods to detect early cardiovascular dysfunction through waveform analysis. He has pioneered approaches using difference equations for modeling arterial wave reflections and contributed to understanding microgravity's impact on cardiovascular systems. Publications Highlight Trends: Recent work emphasizes clinical applications of wearable devices (2023), AI-driven medical recommendation systems (2022), and space physiology studies (2020-2022). Earlier research focused on computational modeling of vascular dynamics and validation of novel diagnostic methods. Advising & Education: Supervised 8 thesis students (2016-2021) in topics like biomedical signal analysis, machine learning in healthcare, and cardiovascular modeling. Active in training the next generation of biomedical engineers through TU Wien's graduate programs. Labs/Teams: Part of TU Wien's Network Lab, collaborating with international teams on projects like the EU's VascAgeNet initiative. Engaged in multidisciplinary teams combining engineering, medicine, and data science.

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.

• Human Factors Engineering
• Automated Driving
• Driver State Modeling
• +۲ مورد دیگر

Jonas Radlmayr is a Researcher at the Department of Ergonomics, Technical University of Munich, where he has been actively contributing since 2014 under Prof. Klaus Bengler's Chair. His work focuses on human factors in automated driving systems, with emphasis on driver-state modeling and transition-of-control mechanisms. Education: Diplom-Ingenieur (Master's equivalent) in Mechanical Engineering, Technical University of Munich (2013), specializing in Control Engineering and Ergonomics Radlmayr's research investigates critical human-automation interaction challenges in conditionally automated driving (Level 3). His work examines how driver drowsiness, non-driving tasks, and system reliability impact take-over performance during transitions of vehicle control. He has pioneered methodological frameworks including the Take-Over Performance Score (TOPS) for quantifying driver readiness and developed integrative models for drowsiness progression in automated contexts. His experimental designs address real-world challenges in human-machine interface validation and driver monitoring system development. Analysis of his 15 most recent publications reveals consistent focus on driver availability metrics, human factors in cut-in scenarios, and mental model formation regarding automation levels. The research demonstrates strong interdisciplinary connections between cognitive psychology, transportation engineering, and physiological monitoring, with recurring themes in usability evaluation frameworks and safety-critical transition protocols. As an integral member of TUM's Ergonomics Chair, Radlmayr utilizes advanced research infrastructure including the Dynamical Mock-Up, Modular Ergonomic Mockup, and Static Driving Simulator. His collaborative work with industry partners addresses practical implementation challenges in automated vehicle design while advancing theoretical understanding of human-automation teaming in transportation systems.

• 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.

Mohamed Alyمشاهده پروفایل

استاد

• Geospatial Technologies
• Remote Sensing
• Geohazard Assessment
• +۳ مورد دیگر

Mohamed Aly is a Professor at the University of Arkansas, affiliated with the Department of Geosciences, Center for Advanced Spatial Technologies (CAST), Arkansas Center for Space & Planetary Sciences, and Environmental Dynamics (ENDY) Program. His research integrates Synthetic Aperture Radar Interferometry (InSAR), GIS, GNSS, and machine learning for geohazard assessment and environmental monitoring. Education: PhD in Geology (Radar Interferometry), Texas A&M University MS in Geology (Remote Sensing & GIS), Zagazig University Research focuses on InSAR for crustal deformation, machine learning in geospatial analysis, wildfire and landslide susceptibility modeling, and geothermal process monitoring. Recent publications emphasize multisensor data fusion and Google Earth Engine applications. Scientific awards include NASA EPSCoR Early Career Investigator, Fulbright College Teaching Commendation, and Academic Excellence from Texas A&M. He mentors students in geohazard research and geospatial technologies.

• Remote Sensing
• Photogrammetry
• Civil Engineering
• +۹ مورد دیگر

Dr. Maria-Valasia Peppa is a researcher at Newcastle University's School of Civil Engineering and Geosciences . Her work focuses on remote sensing, photogrammetry, and geospatial technologies, with applications in hydrodynamic modeling, landslide monitoring, and urban infrastructure analysis. Key Research Areas: UAV-based photogrammetry, glacial lake dynamics, digital elevation models (DEMs), and environmental data uncertainty. Recent Trends: Integration of deep learning with CCTV for traffic analysis, calibration of multisensor UAV systems, and real-time flood nowcasting frameworks. Collaborations: Active partnerships with Professors Jon Mills, Claire Walsh, and international institutions in Africa and Nepal. Applications: Cultural heritage mapping, water security strategies, and urban air quality modeling.

Sudhagar Nagarajanمشاهده پروفایل

دانشیار

• LiDAR Scanning
• Infrastructure Monitoring
• Drone Mapping
• +۲ مورد دیگر

Dr. Sudhagar Nagarajan is an Associate Professor and Associate Chair in the Department of Civil, Environmental and Geomatics Engineering at Florida Atlantic University. He directs the Advanced Geomatics Engineering Lab, focusing on non-contact infrastructure monitoring using LiDAR, drones, and multisensor systems. His research includes shoreline erosion analysis, 3D building modeling, and underwater infrastructure assessment. Projects funded by NASA, DOT, and TRB address resilience in coastal communities. He received the ASPRS Roger Hoffer Award (2018) and ESRI Best Paper Award. Articles emphasize geospatial AI, coastal change detection, and sustainable infrastructure management.

Dionisio Rodríguez-Esparragónمشاهده پروفایل

استاد

• Remote Sensing
• Image Processing
• Data Analysis
• +۵ مورد دیگر

Dionisio Rodríguez-Esparragón is a Professor at the University of Las Palmas of Gran Canaria (ULPGC), affiliated with the Institute of Oceanography and Global Change (IOCAG). He holds B.S., M.S., and Ph.D. degrees from ULPGC and the University of Granada. His research focuses on remote sensing applications for environmental monitoring, image processing, and oceanography. Notable collaborations include work with the Image Analysis Group at the University Politécnica de Madrid and a 2022–2024 requalification stay at the University of Pavia. Education: B.S. in Engineering (1990) – ULPGC M.S. in Physics (2010) – University of Granada Ph.D. in Remote Sensing (2016) – ULPGC Research interests include multispectral satellite image analysis, ecosystem monitoring, and climate change impacts. His work bridges environmental science with technological advancements like LiDAR and UAV-based imaging. Recent projects address volcanic activity tracking, wildfire damage assessment, and African development challenges via remote sensing. Grants and funding have supported initiatives like fusion of multisensor data for coastal ecosystems and analysis of atmospheric-oceanic parameters. His contributions extend to academic collaboration and peer review in global institutions. Labs/Teams: Active in the Medical Data Analytics group at the Center for Biomedical Research (UPM) and leads the IOCAG's remote sensing operational products research.

Zervakis Michalisمشاهده پروفایل

استاد

• Digital Image Processing
• Signal Processing
• Biomedical Engineering
• +۳ مورد دیگر

Zervakis Michalis is a full Professor at the Technical University of Crete (TUC), serving as Rector and Director of the Digital Image and Signal Processing Laboratory (DISPLAY). He holds a Ph.D. in Electrical Engineering from the University of Toronto (1990) and has been a faculty member at TUC since 1995. His expertise spans Digital Image/Signal Processing, biomedical applications, and neural network implementations in automation. Education: Ph.D., Electrical Engineering, University of Toronto (1990) M.Sc., Electrical Engineering, University of Toronto (1985) B.Sc., Electrical Engineering, Aristotle University of Thessaloniki (1983) Research Interests: Signal/image processing for biomedical applications Machine learning for healthcare diagnostics EEG/ECG analysis and seizure detection Neural network architectures for automation Multi-sensor systems and aerial surveillance His research emphasizes clinical applications like epilepsy monitoring and cardiovascular diagnostics, leveraging deep learning and multimodal data fusion. He has led over 20 international projects and published >90 papers in image/signal processing. Current work focuses on AI-driven medical systems and UAV-based infrastructure monitoring. Labs/Teams: Director of the DISPLAY Lab, collaborating on projects like the BorderUAS semiautonomous surveillance platform and the Pulsense cardiovascular monitoring system. Grants/Contributions: Extensive involvement in EU-funded initiatives and industry partnerships, advancing smart farming, power line inspection, and emergency response systems.

Mallika Noccoمشاهده پروفایل

استادیار

• Agrohydrology
• Soil-plant-water relations
• Irrigation management
• +۷ مورد دیگر

Mallika Nocco is an Assistant Professor and Extension Specialist in Agrohydrology at the University of Wisconsin-Madison's Department of Biological Systems Engineering (College of Agricultural and Life Sciences). Her work bridges agricultural engineering, hydrology, and environmental science to advance sustainable water management practices. Education: B.A. in Cultural Studies & Comparative Literature/Philosophy (2004), University of Minnesota M.S. in Soil Science (2012), University of Wisconsin-Madison Ph.D. in Environment and Resources (2017), University of Wisconsin-Madison Research Interests: Dr. Nocco focuses on agrohydrology, soil-plant-water relations, and irrigation management. Her lab develops precision agriculture tools using remote sensing and integrates science communication through the Water Talk podcast. Key areas include: Climate resilience strategies for crops Managed aquifer recharge techniques Evapotranspiration modeling for water efficiency Soil health and carbon sequestration Publications Trends: Recent work emphasizes interdisciplinary approaches, with studies on almond orchard water management, cover crop impacts, and CO2 sequestration via enhanced weathering. Remote sensing innovations dominate technical outputs, while extension-focused projects address grower education and policy. Awards: 2024 Science Communication Fellowship 2023 Soil and Water Conservation Innovation Award 2017 David H. Smith Postdoctoral Fellowship Advising & Grants: Supervises graduate students in soil science and remote sensing applications. Leads projects funded by USDA, NSF, and industry partnerships, focusing on precision irrigation and environmental justice in agriculture. Labs/Teams: Director of the Conservation Irrigation Lab, collaborating with growers, policymakers, and engineers to translate research into actionable strategies. Active in the Tree-crop Remote Sensing (T-REX) initiative for climate-resilient agroecosystems.

• Gait Analysis
• Parkinson's Disease
• Wearable Technology
• +۳ مورد دیگر

Dr. Lisa Alcock is a Researcher at Newcastle University, specializing in gait analysis, wearable technology, and neurodegenerative disorders, particularly Parkinson’s disease. Her work focuses on developing and validating algorithms for mobility assessment, leveraging digital health technologies. She collaborates extensively with interdisciplinary teams, including the Mobilise-D consortium, to advance real-world gait monitoring and clinical outcomes. Recent projects include studies on environmental discrimination using machine learning, patient-centric visualization of mobility data, and drug efficacy analysis through wearable sensors. Her research interests span biomechanics, motor function assessment, and the integration of wearable devices into clinical practice. She has contributed to over 50 peer-reviewed publications, emphasizing methodological advancements in gait detection, turning algorithms, and sensor validation. Collaborations with institutions worldwide highlight her commitment to bridging technological innovation with clinical needs. Key contributions include the development of energy-based composite indices for Parkinson’s disease and novel imaging techniques for gait neuroanatomy. Her work often addresses challenges in real-world applicability, ensuring technologies are validated in diverse settings. Current efforts focus on enhancing patient collaboration in outcome visualization and improving accessibility through context-aware systems.

• Surface Metrology
• Additive Manufacturing
• Precision Engineering
• +۴ مورد دیگر

Professor Jane Jiang is a distinguished academic at the University of Huddersfield , affiliated with the School of Computing and Engineering and the Department of Engineering . She specializes in surface metrology, precision engineering, and advanced manufacturing technologies. Her work focuses on optimizing measurement techniques for additive manufacturing, X-ray computed tomography, and optical systems. Research Interests Her research spans surface texture analysis , 3D vision systems , and metrology for smart manufacturing . She develops novel methods for characterizing complex surfaces using techniques like phase measuring deflectometry and chromatic confocal sensors. Her contributions bridge engineering and materials science, emphasizing practical applications in aerospace, biomedical, and industrial sectors. Recent Contributions Her 2025 work includes advancements in freeform optics design, vibration-resistant microscopy, and neural network-based surface characterization. Her studies on XCT measurement for additive manufacturing parts address critical challenges in precision and data analysis. Affiliations & Projects She leads the Centre for Precision Technologies and actively collaborates on EU-funded projects. She organized the 1st International Conference on Metrology and Standard (2024) and contributes to interdisciplinary initiatives in bio-engineering and advanced materials. Grants & Teams Her team includes researchers like Shan Lou and Paul Scott , focusing on metrology for medical implants and aerospace components. She supervises PhD students exploring AI-driven surface specification and manufacturing process optimization.