جست‌وجوی استاد و پژوهشگر

• Additive Manufacturing
• Process Monitoring
• Control Systems
• +۶ مورد دیگر

Tegoeh Tjahjowidodo is a Senior Lecturer at the Faculty of Industrial Engineering Sciences , KU Leuven , affiliated with the Department of Mechanical Engineering and the Manufacturing Processes and Systems (MaPS) unit at Campus De Nayer. He serves as Head of Education for Electromechanics programs and leads Subdivision 17 at the campus. Research Areas: Additive Manufacturing (Wire-Arc Additive Manufacturing), Process Monitoring, Control Systems, Laser Micromanufacturing, Wear Analysis, Robotics, and Condition Monitoring. Publication Trends: Focus on in-situ monitoring of laser micromanufacturing, machine learning for abrasive belt grinding, WAAM parameter optimization , and multi-sensor fusion for process control. Scientific Contributions: Co-promotor for MultiTRIBO (tribology), Promotor for WAAM structural integrity and pedicle screw surgical simulators . Active in international collaborations (e.g., 25th International Symposium on Laser Precision Microfabrication, Spain 2024).

Roger Michaelidesمشاهده پروفایل

استادیار

• Radar Remote Sensing
• Geospatial Science
• Arctic Permafrost Dynamics
• +۵ مورد دیگر

Roger Michaelides is an Assistant Professor of Earth, Environmental, and Planetary Sciences and Environmental Studies at Washington University in St. Louis. He leads the Radar Interferometry and Geospatial Science Laboratory (Radar Lab), focusing on radar remote sensing, geospatial techniques, and Arctic permafrost dynamics. His work integrates InSAR, radar altimetry, and multi-sensor fusion to study environmental processes like wildfire-permafrost interactions, coastal erosion, and climate change impacts. Michaelides earned a PhD in Geophysics from Stanford University (2020) and held postdoctoral positions at the Colorado School of Mines (2020–2022). He joined Washington University in 2022. His research emphasizes developing novel remote sensing methods for cryospheric and terrestrial systems, including NASA-funded studies tracking permafrost thaw and wildfire effects in the Arctic. Recent awards include a NASA Early Career Investigator Program Fellowship (ECIP-ES), supporting his $300,000 project on Arctic permafrost monitoring. He actively mentors graduate and undergraduate students, offering funded PhD opportunities in InSAR applications and climate science. His lab collaborates with agencies like NASA and the Indian Space Research Organization, leveraging satellite data from missions like NISAR. Key interests include radar signal processing, environmental modeling, and interdisciplinary approaches to Earth observation. Michaelides’ work bridges geophysics, ecology, and climate science, with applications to global environmental challenges such as permafrost degradation and wildfire prediction.

• Precision Agriculture
• Remote Sensing
• Soil Science
• +۳ مورد دیگر

Dr. Patrick Filippi is a Lecturer in Precision Crop Management at the School of Life and Environmental Sciences, University of Sydney. He is affiliated with the Precision Agriculture Laboratory and the Sydney Institute of Agriculture. His work focuses on integrating remote sensing, machine learning, and geostatistics to address challenges in precision agriculture, particularly in crop yield modeling, soil mapping, and environmental monitoring. Research interests include precision agriculture technologies, soil science applications, data-driven crop management, and the use of satellite and proximal sensing for agricultural decision-making. He has contributed to projects funded by the Grains Research and Development Corporation (GRDC) and the University of Sydney, focusing on spatial variability in crop production, soil constraints, and machine learning interpretability. Key achievements include developing the LimeSoDa dataset for soil mapping and winning the 2016 CSIRO AgData Challenge Hackathon. His grants span topics like nitrogen fixation mapping in legumes and frost/heat management analytics. Filippi collaborates closely with industry to translate research into practical tools for farmers. Awards: 2nd Place CSIRO AgData Challenge Hackathon (2016) Labs: Precision Agriculture Laboratory (https://precision-agriculture.sydney.edu.au/) Grants: Includes Strategic Partnership Seeding Grants (2024), GRDC-funded projects (2022–2024), and Start-Up Research Funding (2024).

• Earth Observation
• Synthetic Aperture Radar (SAR)
• Remote Sensing
• +۶ مورد دیگر

Dr. Armando Marino is a Senior Lecturer in Earth Observation at the University of Stirling’s Department of Biological and Environmental Sciences since 2018. He holds an MSc in Telecommunication Engineering (2006, Universita’ di Napoli) and a PhD in Polarimetric SAR Interferometry (2011, University of Edinburgh). His research focuses on synthetic aperture radar (SAR) for environmental monitoring, including maritime pollution, forest degradation, agricultural productivity, and coastal erosion. Education: MSc Telecommunication Engineering, Universita’ di Napoli ‘Federico II’ (2006) PhD in Remote Sensing, University of Edinburgh (2011) Marino develops machine learning algorithms for SAR data analysis and conducts fieldwork with custom-built radar systems. He collaborates with institutions like ESA, JAXA, and NASA, leading projects such as PlasticSurf (microplastic detection) and MoLaDy (ALOS-4 land monitoring). His work integrates optical and SAR satellite data for flood mapping and vegetation analysis. He has received accolades including the RSPSoc Best PhD Thesis (2011) and University of Stirling’s Outstanding Collaborator award (2022). Current projects involve £180,000+ in funding for radar-based environmental solutions. Scientific Awards: Best PhD Thesis 2011 (RSPSoc) Outstanding PhD Thesis (Springer Verlag) Outstanding Collaborator 2022 (University of Stirling) Marino’s methodologies combine SAR polarimetry, computer vision, and environmental field measurements. He actively mentors interdisciplinary teams and contributes to global initiatives on climate hazard mitigation.

• Remote Sensing
• Geographic Information Systems (GIS)
• Environmental Monitoring
• +۷ مورد دیگر

Giorgos Mountrakis is a Professor in the Department of Environmental Resources Engineering at SUNY College of Environmental Science and Forestry (ESF). His research focuses on environmental monitoring using remote sensing, environmental modeling through geographic methods, and decision support systems for ecological and urban challenges. He holds a Dipl. Eng. from the National Technical University of Athens (1998), an M.S. (2000), and Ph.D. (2004) from the University of Maine. His work integrates advanced technologies like satellite imagery, LiDAR, and machine learning to address land cover dynamics, climate impacts, and wildlife conservation. Current advisees include Atef Amriche (PhD candidate in Geospatial Information Science), Babak Haji Seyed asadollah (PhD in Environmental Resources Engineering), Ahmadreza Safaeinia (PhD in Environmental Resources Engineering), and Zhixin Wang (PhD in Geospatial Information Science). Key research themes include: land use/cover classification using deep neural networks, climate change impacts on forests and rangelands, and optimizing spatial-temporal models for large-scale environmental analysis. His projects span global datasets (e.g., Landsat, MODIS) and regional case studies in the US, Mongolia, and Algeria. Publications emphasize methodological advancements in remote sensing, such as fusion of multisensor data, accuracy assessment frameworks, and applications in biodiversity conservation. His work bridges technical innovation with practical environmental decision-making, addressing issues like urban growth prediction and wildlife-vehicle collision mitigation.

Natalia Efremovaمشاهده پروفایل

مدرس ارشد

• Machine Learning
• Deep Learning
• Computer Vision
• +۴ مورد دیگر

Dr. Natalia Efremova is a Senior Lecturer in Digital Economy at Queen Mary University of London (QMUL), School of Business and Management. She joined QMUL in November 2021 and is a member of the Centre for Globalisation Research (CGR) and a fellow of the Digital Environment Research Institute (DERI). Her research focuses on applying machine learning and deep neural networks to address sustainability challenges such as climate change, sustainable agriculture, and environmental monitoring. She holds a Ph.D. in Computer Science (Neural Networks for Computer Vision) from Kyoto University and an MBA from the University of Oxford, where she also worked as a Teradata Research Fellow at the Said Business School. Education: Ph.D. in Computer Science, Kyoto University, Japan (2012) MBA, University of Oxford, Said Business School (2021) Previous Roles: Associate Professor, Plekhanov University of Economics, Russia (2012–2016) Teradata Research Fellow, University of Oxford (2016–2021) Research Interests: Dr. Efremova’s work emphasizes developing transparent ML models for sustainable land-use and climate-related applications, as well as ethical AI frameworks for sustainable development goals. Her projects involve satellite data analysis (e.g., Sentinel imagery) for precision agriculture, soil moisture estimation, and crop monitoring. Teaching & Supervision: She teaches courses in Business Analytics (e.g., Group Projects in Business Analytics) and supervises PhD students in AI applications for sustainability. She is currently co-director of the MSc in Environmental Analytics program (2023). Key Themes in Publications: Her articles focus on AI-driven solutions for environmental challenges, including crop mapping, soil carbon estimation, and regenerative grazing monitoring. Methodologies include deep learning (e.g., Transformers, GANs) and remote sensing data fusion. Affiliations: Member of CGR and fellow of DERI, contributing to interdisciplinary research on globalization and environmental AI.

Aoife Gowenمشاهده پروفایل

استاد

• Hyperspectral Imaging
• Sustainable Transport Policy
• Critical Thinking in Education
• +۴ مورد دیگر

Professor Aoife Gowen is a leading academic at the UCD School of Biosystems & Food Engineering , specializing in hyperspectral imaging and its applications across medicine, food safety, and engineering. Her research, supported by prestigious European Research Council (ERC) funding, investigates water molecule interactions with surfaces to improve bone graft materials and develop innovative diagnostic tools for prostate cancer. She also leads Science Foundation Ireland (SFI)-funded projects on hyperspectral monitoring of bacterial growth for food safety. Beyond technical research, Professor Gowen has developed computational tools now integrated into commercial chemical analysis software. Her work spans interdisciplinary domains, including sustainable transport policy, critical thinking education, and promoting gender diversity in engineering. As a key figure in the Women on Walls initiative, she has enhanced visibility for women in STEM fields. Her recent publications focus on spectral technologies for food quality, microplastics characterization, and medical diagnostics, reflecting her commitment to addressing global challenges in health and sustainability. Scientific Awards: ERC Grant for water-surface interaction research Professor Gowen actively collaborates with European networks and industry partners, driving advancements in hyperspectral imaging applications. Her lab’s efforts to bridge computational science with real-world chemical analysis have positioned her as a pioneer in invisible chemistry visualization, impacting medicine, food, and environmental engineering.

• Hyperspectral Imaging
• Machine Learning
• Image Processing
• +۵ مورد دیگر

Suhad Al-Khafaji is a Research Fellow in Hyperspectral Spectroscopy at Griffith University's School of Environment and Science (Chemistry and Forensic Science). Their research focuses on hyperspectral imaging, machine learning, and computer vision applications in agriculture, environmental monitoring, and material analysis. Al-Khafaji is affiliated with the Australian Rivers Institute and previously the Institute for Integrated and Intelligent Systems (2015-2020). They hold an ORCID identifier (0000-0002-7986-4308) and are located at N44 1.26, Nathan Campus. Research Interests: Hyperspectral imaging for agricultural quality assessment (e.g., macadamia moisture analysis) Spectral-spatial boundary detection algorithms in multispectral datasets Machine learning integration with computer vision techniques Nanotechnology applications in imaging systems Cognitive psychology aspects of pattern recognition Recent Work Trends: Recent articles emphasize hyperspectral image processing innovations, particularly boundary detection and feature extraction for agricultural and environmental applications. Their 2024 work applies machine vision to macadamia quality prediction, while earlier contributions (e.g., 2022) refine spectral-spatial analysis methodologies. Labs/Teams: Active member of Griffith's Australian Rivers Institute and former affiliate of the Institute for Integrated and Intelligent Systems.

Flora Salimمشاهده پروفایل

استاد

• Machine Learning
• Time-series Analysis
• Spatio-temporal Data Mining
• +۵ مورد دیگر

Flora Salim is a Professor in the School of Computing Technologies at RMIT University. She serves as co-Deputy Director of the RMIT Centre for Information Discovery and Data Analytics (CIDDA) and an Associate Investigator of the ARC Centre of Excellence in Automated Decision Making and Society. Her research focuses on human behavior modeling, machine learning with time-series and spatio-temporal data, and edge AI applications in IoT and wearables. Flora has secured over $10M in research funding from ARC, industry partners, and government bodies. Notable awards include the 2021 PACM IMWUT Distinguished Paper Award, 2019 Humboldt-Bayer Fellowship, and RMIT's 2018 Research Impact Award. She leads the CRUISE research group and has held visiting professorships at the University of Kassel and University of Cambridge. Editorial roles: Associate Editor of PACM on IMWUT, Area Editor of Pervasive and Mobile Computing Steering Committee member of ACM UbiComp Her work bridges ubiquitous computing and machine learning, with applications in urban analytics, mobility, and health monitoring. Recent projects include self-supervised learning for multimodal data and forecasting with heterogeneous time-series. Supervision areas: Deep learning for sensor data, explainable AI, and wearable-based emotion sensing Teaching programs: Master of Artificial Intelligence and Master of Data Science

• Earth Physics
• Climate Science
• Remote Sensing
• +۳ مورد دیگر

Francisco J. Tapiador is a Professor at the Universidad de Castilla-La Mancha , affiliated with the Department of Environmental Sciences. His research spans Earth Physics, Climate Science, and Remote Sensing, with a focus on precipitation modeling, climate classification systems, and data fusion techniques. He leads the Earth Physics research group at UCLM and collaborates extensively with international institutions. Key Research Areas : Earth Physics Climate Modeling Satellite Meteorology Data Fusion Algorithms Environmental Uncertainty Quantification Publication Trends : Dr. Tapiador's recent work emphasizes high-resolution precipitation merging via radar corrections, machine learning for storm detection, and uncertainty quantification in climate models. His articles integrate Remote Sensing , Machine Learning , and Climate Informatics to address extreme weather and hydrometeorological hazards. Peer Review Leadership : Atmospheric Research Chaos, Solitons and Fractals Chemosphere Heliyon Journal of Computational Science Meteorology and Atmospheric Physics Water Resources Research Collaborative Networks : Andrés Navarro Eduardo García-Ortega Gyuwon Lee Kyo-Sun Sunny Lim Ziad S. Haddad Technological Impact : His work bridges fluid dynamics , entropy-based algorithms , and neural networks to advance satellite precipitation estimation and climate model validation. Current projects include multi-satellite data correction and climate-human system couplings.

Vasit Saganمشاهده پروفایل

استاد

• Geospatial Science
• Remote Sensing
• Photogrammetry
• +۴ مورد دیگر

Vasit Sagan is a Professor of Geospatial Science and Computer Science at Saint Louis University's School of Science and Engineering . He directs the Remote Sensing Lab , serves as Deputy Director of the Taylor Geospatial Institute , and holds the role of Associate Vice President for Geospatial Science in the Office of the Vice President for Research and Partnership. Education: Ph.D. from Peking University (2006) Leadership: Director of Remote Sensing Lab; Deputy Director, Taylor Geospatial Institute Research Interests center on geospatial computer vision , integrating remote sensing, photogrammetry, machine learning/AI, and imagery analysis. His work addresses critical challenges in food and water security , ecosystem monitoring , and social instability at scales ranging from local to global. He has secured over $50M in grants as PI/Co-PI and authored 150+ peer-reviewed publications. Recent Publications highlight his interdisciplinary approach, with studies on crop yield prediction via satellite/UAV imagery, disease detection in wheat, urban tree species classification, and deep learning applications for water quality monitoring. These works span agricultural technology , environmental science , and security informatics , emphasizing data fusion and AI-driven geospatial analysis. Scientific Awards include: 2021 Best Paper Award (Remote Sensing) Best Paper Award (International Archives of Photogrammetry) Advising and Grants : He has mentored numerous doctoral, master's, and postdoc researchers, and led major funded projects focused on geospatial AI and environmental sustainability. Labs and Facilities : Remote Sensing Lab at Saint Louis University and collaborative work with the Taylor Geospatial Institute.

• Geographic Information Science
• Remote Sensing
• Spatial Modeling
• +۵ مورد دیگر

Dr. George Raber is a Professor in the Department of Geography at the University of Southern Mississippi. His expertise spans Geographic Information Systems (GIS), remote sensing, spatial modeling, and unmanned aerial vehicles (UAVs). He holds a PhD from the University of South Carolina (2003), an MS from the same institution (2001), and a BS from Brigham Young University (1999). His research focuses on applying geospatial techniques to environmental challenges, particularly in coastal regions, with technical strengths in web mapping, spatial programming, and UAV-based remote sensing. Key research areas include coastal hazard exposure analysis, coral reef restoration, and the integration of machine learning with remote sensing data. His work emphasizes practical applications such as marine habitat mapping, risk assessment for coastal communities, and low-cost monitoring technologies like small unmanned surface vehicles (sUSVs). Dr. Raber's publications reflect a trend toward interdisciplinary solutions, combining geospatial technologies with environmental conservation and urban studies. Notable contributions include studies on UAV-LiDAR accuracy in marsh ecosystems and the socioeconomic impacts of environmental policies. He teaches courses ranging from foundational GIS and cartography to advanced topics like spatial programming and environmental remote sensing. His office is located in Walker Science Building 226.

• Cyber-Physical Systems
• Machine Learning
• Autonomous Systems
• +۵ مورد دیگر

Radu Grosu is a Professor at Technische Universität Wien (TU Wien), leading the Forschungsbereich Cyber-Physical Systems . His research focuses on Cyber-Physical Systems (CPS), Machine Learning, and autonomous robotics, with notable contributions to neural network architectures like Liquid Time-Constant Networks (LTC) and their applications in robotics and medical imaging. He is affiliated with the Network Lab and has supervised numerous PhD and Master's students, including Sebastian Michael Bittner, Daniel Scheuchenstuhl, and Sophie Neubauer. His work spans topics such as reinforcement learning, autonomous driving, and IoT ecosystems. Recent projects include developing robust AI systems for healthcare and robotics, such as tumor delineation using PET imaging and neuromorphic IoT architectures for smart villages. Grosu has published extensively on CPS, with over 146 contributions across peer-reviewed journals and conferences. His research emphasizes bridging theory and practice, addressing challenges in safety, scalability, and real-time control in autonomous systems. Key research interests include robotic perception, neural network robustness, and CPS/IoT integration. He has pioneered methods like DeepSTL for translating temporal logic requirements into neural network training objectives and developed frameworks like NimbleAI for neuromorphic sensing-processing systems. His team also explores distributed control algorithms for multi-agent systems, such as flocking drones and formation control using relative distance measurements. Recent work examines the generalization properties of deep filters in CNNs and quantum-classical reinforcement learning models for game AI. Grosu has advised over 20 students on topics ranging from deep learning in wafer defect analysis to bio-inspired neural circuits for auditable autonomy. His lab collaborates on interdisciplinary projects, such as applying AI to battery health estimation and prostate cancer diagnostics. He actively contributes to academic communities, editing special issues on AI in healthcare and CPS resilience, and has organized summer schools on CPS and IoT systems.

Justin Lipmanمشاهده پروفایل

استاد

• Cybersecurity
• Internet of Things (IoT)
• Wireless Communications
• +۶ مورد دیگر

Justin Lipman is a Professor in the School of Electrical and Data Engineering at the University of Technology Sydney (UTS). He serves as Director of the Cyber Digital Centre and previously led the RF and Communications Technologies Lab. With over 12 years of industry experience at Intel and Alcatel, his expertise spans cybersecurity, IoT, 5G/O-RAN, digital agriculture, and smart cities. Lipman holds a PhD in Telecommunications Engineering from the University of Wollongong. Research & Funding Secured $35M+ in research grants, including projects like UTS Vault ($8M) and the Nokia 5G Futures Lab. Focus areas: Cybersecurity, IoT infrastructure, wireless communications, and smart agriculture. 24 U.S. patents granted, including innovations in IoT security and metamaterials. Education PhD in Telecommunications Engineering (University of Wollongong, 2004) Industry experience: Chief Architect at Intel (2006–2016), Program Manager at Alcatel-Lucent (2005). Awards & Recognition IEEE Senior Member (2012) Leadership roles: Deputy Chief Scientist (Food Agility CRC), Board Director (Internet of Things Alliance Australia). Teaching & Labs Supervises HDR/PhD students in areas like SDN and IoT. Labs: RF and Communications Lab, BlueSky initiative.

• Remote Sensing
• Sensors
• Soil Carbon Sequestration
• +۷ مورد دیگر

Dr. Titia Mulder is an Associate Professor in Digital Soil Science at the Soil Geography and Landscape group, Wageningen University, The Netherlands. She specializes in spatial and temporal modeling of soil-landscape systems and soil sensing techniques for monitoring soil functions. Her work focuses on large-extent soil dynamics, ecosystem health, and sustainable land use practices. She chairs the IUSS Pedometrics Commission (2018–2022) and serves as an associate editor for European Journal of Soil Science and Frontiers in Soil Science . Her research integrates remote sensing, spatial statistics, and spectroscopy to address environmental challenges like climate change and biodiversity loss. She leads European and national projects on soil mapping and soil health monitoring. Key areas of expertise include soil-landscape relationships, sensor-based soil monitoring, and machine learning applications in environmental data analysis. Mulder teaches courses on spatial analysis for earth sciences ( GRS33306 ), environmental data collection ( YWU30806 ), and soil inventory techniques ( SGL30306 ). She supervises MSc internships and thesis projects in soil geography and landscape studies through modules like SGL70224 , SGL79224 , and SGL80436 . Her work emphasizes societal impact through sustainable practices, providing actionable insights for policy makers and stakeholders to combat environmental crises and ensure food security. She collaborates internationally on projects promoting soil carbon sequestration and ecosystem resilience.