جست‌وجوی استاد و پژوهشگر

Mihaela Girtanمشاهده پروفایل

دانشیار

• Thin Films
• Solar Cells
• Optoelectronics
• +۳ مورد دیگر

Mihaela Girtan is an Associate Professor in the Faculty of Sciences at the University of Angers, heading the Thin Films for Photovoltaic Applications research group. Her work spans thin-film technologies, solar cells, and optoelectronic devices, with expertise in physical/chemical deposition methods and nanomaterials. Education: PhD in Physics, University of Stuttgart (1995) Her research investigates charge transport in oxides, organic/perovskite solar cells, transparent conducting films, plasmonics, and fluid dynamics in CVD reactors. She develops innovative materials for energy conversion, including oxide/metal/oxide electrodes and polymer-based photovoltaics. Recent publications focus on climate-agriculture interactions, including drought risk modeling, irrigation dynamics, and crop yield sustainability. Her work integrates remote sensing, machine learning, and climate modeling to address food security challenges. Scientific Awards: Consistently ranked in top 2% of researchers worldwide since 2020 She leads international collaborations and advises PhD students in materials science. Her group maintains advanced thin-film deposition and characterization facilities at Angers Photonics Laboratory.

Gyula Mate Kovácsمشاهده پروفایل

پژوهشگر ارشد

• Remote Sensing
• Wetlands
• Artificial Intelligence
• +۶ مورد دیگر

Gyula Mate Kovács is a Research Fellow (Postdoctoral Researcher) at the Department of Geosciences and Natural Resource Management, Faculty of Science, University of Copenhagen. His research is funded by the Novo Nordisk Foundation through the Global Wetland Center. Education Ph.D. in Remote Sensing of Wetlands, University of Copenhagen (2020–2024) M.Sc. in Geography and Geoinformatics, University of Copenhagen (2017–2019) B.Sc. in Environmental Management, Birkbeck University of London (2013–2017) Research Focus Dr. Kovács specializes in AI-driven remote sensing for wetland ecosystem analysis. His work integrates machine learning, deep learning, and satellite data fusion to quantify natural/anthropogenic impacts on wetlands at global scales. Key methodologies include time series analysis, cloud computing, and convolutional neural networks for applications like carbon mapping, water body detection, and land-use impact assessment. Publication Trends His 7 recent publications demonstrate a strong focus on wetland dynamics using satellite remote sensing, with themes spanning deep learning applications (CNN U-Net algorithms), greenhouse gas emissions in croplands, continental-scale wetland inventories, and ecosystem change detection. Research consistently employs advanced AI techniques to address environmental challenges in diverse regions like the Sahel and Europe. Funding & Affiliation Supported by the Novo Nordisk Foundation via the Global Wetland Center, his work advances wetland monitoring capabilities. He collaborates with international teams on projects involving satellite data processing and ecological modeling.

• Nonlinear Dynamics
• Quantum Chaos
• Complex Networks
• +۵ مورد دیگر

Ying-Cheng Lai is a Regents' Professor in the School of Electrical, Computer and Energy Engineering at Arizona State University (ASU), where he has been a full-time faculty member since 2005. He holds affiliations with the Center for Biodiversity Outcomes and the Center for Biological Physics. Previously, he served as the Sixth Century Chair in Electrical Engineering at the University of Aberdeen (2009–2017) and returned to ASU as the ISS Endowed Professor (2014–present). His academic journey includes a BS and MS in Optical Engineering from Zhejiang University (1982–1985), followed by MS and PhD in Physics from the University of Maryland, College Park (1989–1992). He completed a postdoctoral fellowship in Biomedical Engineering at Johns Hopkins University School of Medicine (1992–1994). His research focuses on Nonlinear Dynamics and Chaos , Machine Learning applied to complex systems, Relativistic Quantum Chaos , Complex Networks , Mathematical Biology , and Theoretical Ecology . He explores topics such as quantum scars in Dirac materials, synchronization control in networks, and early warning signals for ecological tipping points. His work integrates data analysis techniques with interdisciplinary applications in healthcare, climate science, and cybersecurity. His recent publications highlight advancements in machine learning-driven predictions for critical transitions, quantum transport modeling in graphene, and cybersecurity strategies for power grids. These trends reflect his commitment to bridging theoretical physics with applied engineering solutions. Awards: Regents Professor (ASU's highest faculty honor, 2021) Vannevar Bush Faculty Fellowship (DoD, 2016) Corresponding Fellow of the Royal Society of Edinburgh (2018) Foreign Member of Academia Europaea (2020) Fellow of AAAS (2020) Fellow of the American Physical Society (1999) Ying-Cheng Lai has advised 24 PhD and 20 MS students, supported 15 postdocs, and secured funding from agencies like DOD (AFOSR, ARO, Navy-ONR), NSF, and the National Academies. His grants include projects on quantum billiard systems, sensor applications, and network resilience in multilayer ecological frameworks. He runs a research group focused on advanced topics in electrical engineering and interdisciplinary physics.

Monika Kufferمشاهده پروفایل

استاد

• Urban Remote Sensing
• Urban Planning
• Deprived Areas
• +۶ مورد دیگر

Monika Kuffer is a Full Professor at the University of Twente's Faculty of Geo-Information Science and Earth Observation (ITC), holding additional roles as Associate Professor in the Department of Urban and Regional Planning and Geo-Information Management. She leads research in urban remote sensing, deprived area monitoring, and sustainable urban development. Her work integrates spatial statistics, machine learning, and citizen science to inform inclusive city planning. Education: PhD in Human Geography & GIS from the University of Twente MSc in Human Geography (TU Munich) MSc in Geographic Information Science (University of London) Research Interests: Urban Remote Sensing Slum and Deprivation Mapping Climate Adaptation Strategies Citizen Science for Urban Inequalities Earth Observation Policy Support Articles Trends: Recent work emphasizes multi-city climate adaptation analyses, thermal inequality assessments in African slums, and scalable deprivation modelling frameworks like IDEAMAPS. Projects like ONEKANA and NightWatch highlight fusion of EO data with community-driven methods. Awards: 2022 EO4all Prize for innovative Earth Observation applications Advising & Grants: Supervised 3 PhD/MSc projects. Active in global initiatives like the EU's Knowledge Centre on EO and the UN's SDG frameworks. Leads datasets on deprivation (e.g., IDeAMapSudan). Labs/Teams: Core member of ITC's Urban Remote Sensing and GeoAI teams. Collaborates with the Digital Society Institute for interdisciplinary urban research.

Chantel Chizenمشاهده پروفایل

استادیار

• Digital Pedology
• Remote Sensing
• Soil Carbon Dynamics
• +۳ مورد دیگر

Dr. Chantel Chizen is an Assistant Professor in the Department of Soil Science at the University of Saskatchewan. Her research focuses on advancing sustainable land management through digital pedology, remote sensing, and geospatial methods. She investigates soil carbon dynamics, prairie wetland management, soil salinity, and soil data management, collaborating with farmers and institutions to bridge scientific insights with practical agricultural needs. Education : Ph.D. (Soil Science), University of Saskatchewan (2024) M.Sc. (Soil Science), University of British Columbia (2020) B.Sc. (Applied Plant and Soil Science), University of British Columbia (2018) Research emphasizes interdisciplinary approaches to soil stewardship, including fieldwork and technologies like machine learning. Key themes include soil variability in agroecosystems, salinity impacts on Prairie wetlands, and carbon sequestration strategies. Recent work highlights soil-landscape modeling and climate resilience in agricultural systems. Key Awards : Carbon Sequestration Research Fellow (2024) Teacher-Scholar Doctoral Fellow (2023) FFAR Future Leaders in Food & Agriculture (2021) Her publications address soil carbon dynamics, greenhouse gas emissions in potato farming, and labile carbon fractions in grassland restoration. Ongoing projects aim to integrate farmer feedback into soil data frameworks and improve Prairie wetland management practices.

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.

• Water Resources Systems Management
• Groundwater and Surface Water Quality
• Saltwater Intrusion Control
• +۷ مورد دیگر

Bithin Datta is a Senior Lecturer in the Discipline of Civil Engineering at James Cook University (Australia), part of the College of Science and Engineering and the Division of Tropical Environments and Societies. He is affiliated with TropWATER (Centre for Tropical Waters and Aquatic Ecosystem Research), the Economic Geology Research Unit (EGRU) at JCU, and the CRC-for Contamination Assessment and Remediation of the Environment (CRC-CARE) at the University of Newcastle. Previously, he held Professor and Senior Professor positions at IIT Kanpur, India (1995-2009), and served as Head of the Civil Engineering Department and Head of the Postgraduate Environmental Engineering and Management Program. He has held Visiting Professorships at Dalhousie University (Canada), Denmark Technical University (Copenhagen), and the Asian Institute of Technology (Bangkok). Education: B.Tech (Hons) in Civil Engineering from IIT Kharagpur (India), Master’s degree in Civil Engineering (first rank in specialization), and a PhD in Civil Engineering from Purdue University (USA), specializing in Hydraulics and Systems Engineering. He is a Fellow of Engineers Australia (FIEAust). Research interests include water resources systems management, groundwater and surface water modeling, reservoir operation optimization, saltwater intrusion control, AI-driven environmental predictions, and ecological flow assessment. His work integrates simulation-optimization frameworks, machine learning (e.g., ANFIS, SVM), and hydraulic engineering principles to address contamination, climate change, and infrastructure challenges in tropical and coastal regions. His publications (178+ entries) focus on computational tools for groundwater contamination source identification, sustainable aquifer management, and reservoir environmental impacts. Notable projects include a $629,000 CRC-CARE-funded initiative for contamination monitoring networks and AI-based drought prediction models in tropical Queensland. Advising: Coordinated the Master of Engineering (Water Resources Management) at JCU and supervised over 30+ Master’s and 19 Ph.D. students across IIT Kanpur, JCU, and the University of South Australia. His research has been ranked #1 globally by ScholarGPS in Groundwater Pollution, Surrogate Models (AI/ML), and Saltwater Intrusion management. Labs/Teams: Core member of TropWATER, EGRU, and CRC-CARE, leading interdisciplinary projects on tropical water systems and geochemical contamination modeling in mine sites.

Chew Lock Yueمشاهده پروفایل

استاد

• Complex Systems
• Nonlinear Dynamics
• Quantum Physics
• +۵ مورد دیگر

Professor Chew Lock Yue is an Associate Dean (Students) in the College of Science and a Full Professor in the School of Physical & Mathematical Sciences at Nanyang Technological University (NTU). He holds a B.Eng (Hons) in Electrical Engineering from the National University of Singapore (1991), an M.Sc in Electrical Engineering from the University of Southern California (1997), and a Ph.D. in Theoretical Physics from NUS (2004). His research focuses on complex systems, nonlinear dynamics, quantum thermodynamics, and urban systems modeling. Current projects include thermodynamics of information processing, machine learning integration with complex systems, and statistical physics of sea-level rise. Professional roles span technical leadership at DSO National Laboratories (1992-2005), academic appointments since 2005 (Assistant Professor to Full Professor), and administrative roles including Cluster Deputy Director at NTU’s Data Science & Artificial Intelligence Research Centre (2018-2021). He has received multiple teaching awards, including the Nanyang Award for Excellence in Teaching (2007) and the Best Faculty Mentor Award (2013). Research interests also encompass social-ecological systems, quantum heat engines, and spatial agglomeration patterns in urban contexts. His work bridges physics with interdisciplinary challenges like climate modeling and machine learning, with over 150 publications in peer-reviewed journals. Active in education, he teaches courses on quantum mechanics, nonlinear dynamics, and statistical physics.

Alexander Kocianمشاهده پروفایل

استادیار

• Machine Learning
• Internet-of-Things (IoT)
• Agro Informatics
• +۳ مورد دیگر

Alexander Kocian is an Assistant Professor at the Department of Computer Science, University of Pisa. He holds a Ph.D. in Electrical and Electronic Engineering from Aalborg University (Denmark) and a Master's in Electrical Engineering from TU Vienna (Austria). His research focuses on Machine Learning, IoT, Agro Informatics, Health Informatics, and Real-time embedded systems. He has led major projects like AGRITECH (€40M funded by PNRR) and FuorisuoloSmart, advancing smart agriculture and healthcare technologies. Dr. Kocian serves as IEEE Senior Member (since 2024) and EAI Fellow (since 2022). He is Associate Editor of IEEE Access (2025–present), and Editorial Board member of Stats (2019–present) and Signals (2020–present). He has organized conferences like the EAI Int. Conf. on Intelligent Transport Systems (INTSYS) as General Chair (2024) and Steering Committee Member (2023). His work includes 50+ peer-reviewed publications, 4 patents, and contributions to telemedicine platforms like TESHEALTH (ESA-funded). Key projects span precision farming, IoT-based greenhouses, and AI-driven healthcare solutions. Current efforts emphasize data spaces for agritech and health informatics interoperability.

Bishnu Acharyaمشاهده پروفایل

دانشیار

• Bioprocess Engineering
• Biomaterials
• Nanocomposites
• +۷ مورد دیگر

Bishnu Acharya serves as an Associate Professor and Saskatchewan Ministry of Agriculture Chair in Bioprocess Engineering within the Department of Chemical and Biological Engineering at the University of Saskatchewan. His research program focuses on sustainable conversion of agricultural biomass into high-value products through advanced bioprocessing techniques, addressing critical environmental and energy challenges. His primary research domains include: Cellulose-based biomaterials and nanocomposites for biomedical and packaging applications Thermochemical conversion (pyrolysis, gasification) and biochemical processing of agricultural residues Engineered biochar systems for wastewater remediation and soil enhancement Integration of remote sensing and machine learning for precision agriculture optimization Development of biodegradable materials from flax, wheat straw, and camelina meal Analysis of his 2024-2025 publications reveals a strong interdisciplinary trajectory bridging chemical engineering, environmental science, and agricultural technology. Key thematic clusters involve circular economy implementation in biomass valorization, nanocellulose-based advanced material development, and sustainable wastewater treatment solutions. His work consistently emphasizes practical applications for Canadian agricultural systems, particularly in Saskatchewan and Prince Edward Island contexts. Professional Recognition: Saskatchewan Ministry of Agriculture Chair in Bioprocess Engineering While specific grant details are not publicly enumerated in available materials, Dr. Acharya's prolific output across high-impact journals indicates substantial research funding and active supervision of graduate students. His collaborations span environmental remediation, advanced materials development, and sustainable agricultural technologies, reflecting a systems-thinking approach to bioresource management. Laboratory infrastructure likely includes biomass processing units, nanomaterial characterization facilities, and bioreactor systems supporting his diverse research portfolio.

• Machine Learning
• Environmental Science
• Climate Science
• +۳ مورد دیگر

Professor Stephen Roberts holds the Royal Academy of Engineering / Man Group Chair in Machine Learning at the University of Oxford. He is affiliated with the Oxford-Man Institute and Somerville College. With a DPhil in machine learning and a physics background, his research spans environmental science, financial systems, and geophysics. He co-leads the Machine Learning Research Group and directs the EPSRC Centre for Doctoral Training in Autonomous, Intelligent Machines and Systems (AIMS). His academic journey includes prior faculty roles at Imperial College London before joining Oxford in 1999. Key research interests include tidal analysis using AI, climate modeling, geospatial data interpretation, and financial algorithm design. He has pioneered tools like RTide for coastal flooding prediction and developed machine learning frameworks for environmental and economic applications. Education: DPhil in Machine Learning, Physics undergraduate degree Affiliations: Oxford-Man Institute, Somerville College, EPSRC AIMS CDT Key Projects: SWOT mission data corrections, Antarctic bedrock mapping, carbon footprint reduction in ML His work bridges disciplines, applying ML to solve complex problems in climate science, finance, and geology. Awards include Fellowship of the Royal Academy of Engineering and IET. Current focus areas include improving climate model accuracy and fostering interdisciplinary training through the AIMS program.

Yeyin Shiمشاهده پروفایل

دانشیار

• Agricultural Remote Sensing
• Precision Agriculture
• High-throughput Phenotyping
• +۴ مورد دیگر

Yeyin Shi is an Associate Professor and Agricultural Intelligence Engineer at the University of Nebraska-Lincoln, Department of Biological Systems Engineering. His research focuses on applying artificial intelligence and remote sensing technologies to enhance agricultural productivity and sustainability. He teaches courses such as AGST 316: Technologies and Techniques for Digital Agriculture and AGEN/AGRO/AGST 431/892: Site-Specific Crop Management. He holds a Ph.D. in Biosystems and Agricultural Engineering from Oklahoma State University (2014), an M.S. (2010), and a B.S. in Mechanical Engineering from Nanjing Forestry University (2007). Research Interests: Agricultural data generation/analysis, remote sensing systems (satellite/UAV-based), crop stress sensing, precision crop management, and high-throughput phenotyping. His work bridges machine learning, robotics, and agronomy to address challenges in sustainable farming practices. Recent projects include maize tassel detection via deep learning, UAV-based weed detection, and nitrogen stress indices for maize using hyperspectral imagery. Awards: ASABE Outstanding Manuscript Reviewer (2015), 1st Place Postdoc Research Poster (2015), 2nd Place Student Robotic Competition (2012) Grants: Active collaborations on USDA-funded projects for precision agriculture and phenotyping Labs/Teams: Leads the Agricultural Intelligence Research Group at UNL, focusing on AI-driven agricultural solutions His research emphasizes scalable solutions through edge computing and cloud-based frameworks for irrigation scheduling and crop monitoring, aiming to optimize resource use in both row crops and livestock systems.

• Bayesian statistics
• Computational statistics
• Environmental statistics
• +۴ مورد دیگر

Roles & Affiliations: Distinguished Research Professor in Statistical Science at Queensland University of Technology (QUT), Director of QUT Centre for Data Science, and Associate Member of University of Oxford's Department of Statistics. Served as Deputy Director of ARC Centre of Excellence in Mathematical and Statistical Frontiers (2015–2021) and ARC Laureate Fellow (2015–2021). Education: BA (Hons) and PhD in Mathematical Statistics from University of New England, Australia. Completed post-doctoral roles at multiple Australian universities. Research Interests: Specializes in Bayesian statistical modelling, computational methods, and their applications in environmental science, genetics, healthcare, and industry. Leads projects on coral reef recovery, cancer epidemiology (Australian Cancer Atlas), and virtual citizen science platforms like Virtual Reef Diver. Her work emphasizes interdisciplinary collaboration, integrating complex data sources with advanced statistical techniques to address real-world challenges. Publications & Grants: Over 350 refereed journal publications and attracted >30 major grants. Recent focus areas include influenza epidemiology, spatial health disparities, and AI-driven early warning systems for climate-sensitive diseases. Active in developing methodologies for spatial statistics, small-area estimation, and federated learning. Awards & Recognition: 2024 Ruby Payne-Scott Medal (Australian Academy of Science), Pitman Medal (2016), first female recipient of this award in 35 years. Elected Fellow of Australian Academy of Science (2018), Academy of Social Sciences (2018), and Queensland Academy of Arts and Sciences (2018). Holds international roles including Vice-President of International Statistical Institute (2021–2025) and Scientific Council Member at Centre International de Rencontres Mathématiques (France). Supervision & Leadership: Supervised over 36 PhD students and leads teams in >50 collaborative projects. Current supervision includes 5 PhD and 4 Masters students at QUT. Founded the QUT Centre for Data Science and previously led the Collaborative Centre for Data Analysis, Modelling and Computation. Labs & Initiatives: Core contributor to the Australian Cancer Atlas 2.0, Virtual Reef Diver project, and Queensland's Learning Potential Fund. Active in global initiatives like the World of Statistics campaign and UN Big Data Task Teams.

• Invertebrate Zoology
• Evolutionary Ecology
• Molecular Ecology
• +۳ مورد دیگر

Timothy Rawlings is an Associate Professor in the Department of Biology at Cape Breton University. He holds a BSc (Honours) and MSc in Zoology from the University of British Columbia and a PhD from the University of Alberta. His research focuses on the evolutionary ecology and molecular ecology of freshwater and marine invertebrates, particularly examining factors influencing their evolution in response to environmental and anthropogenic pressures. Dr. Rawlings' expertise spans invertebrate zoology, marine ecology, and molecular analysis. His work often integrates morphological and genetic approaches, as seen in studies of vermetid snails, hydroids, and invasive molluscs. He has conducted research at the Bamfield Marine Sciences Centre and contributed to biodiversity assessments in Cape Breton and Pacific coral reefs. His publications explore topics such as phylogenetic relationships, species delimitation, and ecological adaptations of marine organisms. Recent work includes investigations into novel shell morphologies, invasive species dynamics, and the evolutionary strategies of sessile invertebrates. Dr. Rawlings emphasizes the importance of understanding human impacts on marine ecosystems, including the introduction of non-native species and climate change effects on coastal communities.

Joni Storieمشاهده پروفایل

دانشیار

• Geomatics
• Remote Sensing
• GIS
• +۶ مورد دیگر

Joni Storie is an Associate Professor in the Geography Faculty at the University of Winnipeg. She holds an office in Lockhart Hall (5L05) and teaches courses including Mapping in a Global World, Intro Remote Sensing, Advanced GIS, and Advanced Remote Sensing. Her research focuses on land-use/land-cover mapping, map automation with machine learning tools, spatial statistics, and terrestrial/aquatic resource management. Teaching expertise spans Regional & Physical Geography, Resource Conservation & Management, and Geomatics (GIS & Remote Sensing). Her work integrates geospatial technologies with environmental challenges, including flood mitigation, mangrove ecosystem analysis, and food environment patterning in urban areas. Research outputs emphasize remote sensing applications in coastal conservation, surface water detection, and vegetation dynamics. Over 13 peer-reviewed articles since 2004 demonstrate sustained academic contributions to geomatics and environmental geography. Current activities include advising on geomatics projects and contributing to the University of Winnipeg’s Geography program infrastructure.