جست‌وجوی استاد و پژوهشگر

• Plant Breeding
• Genetic Resources Management
• Hemp Genetics
• +۳ مورد دیگر

Jos Mieog is a Research Fellow at Southern Cross University's Faculty of Science and Engineering. Previously, he spent seven years at CSIRO in Canberra specializing in plant breeding for cereal crops using both genetic modification and conventional methods. His PhD research at the University of Sydney investigated coral bleaching mechanisms, focusing on symbiotic relationships between corals and algae, particularly thermal tolerance adaptation. Currently, his work centers on establishing international-standard genetic resources for hemp, pre-breeding characterization of hemp germplasm, and leading a tea tree essential oil breeding program. His research interests span plant breeding methodologies, genetic resource management, cannabis metabolism regulation, and symbiotic relationships in marine ecosystems. He has developed high-throughput genotyping platforms (HASCH) and advanced tissue culture techniques for cannabis propagation. His work integrates proteomics, metabolomics, and spectral analysis to optimize crop yields and quality. Notable research trends include exploring light spectra effects on cannabinoid production, developing non-destructive analytical tools for essential oil composition, and investigating symbiotic flexibility in corals under environmental stress. His contributions bridge laboratory innovations with commercial agricultural applications, emphasizing both hemp and tea tree oil industries. Advising and grants: Mieog leads interdisciplinary projects involving genetic resource curation and industry partnerships. His work aligns with Southern Cross University's focus on applied ecological and agricultural research. Lab facilities include state-of-the-art genetic resource facilities and analytical laboratories for plant metabolite analysis.

• Seismology
• Engineering Seismology
• Earthquake Hazard Analysis
• +۷ مورد دیگر

Summary Dr. Dariush Motazedian is a Full Professor of Engineering Seismology at Carleton University's Department of Earth Sciences within the Faculty of Science. He has held academic roles since 2003, including Department Chair (2016-2019). His research focuses on stochastic and hybrid earthquake fault modeling, seismic microzonation, and seismic soil dynamics. He leads collaborative projects with institutions like the Geological Survey of Canada (GSC), Hydro Quebec, and international partners. Key contributions include the EXSIM earthquake modeling technique, Ottawa's first seismic microzonation maps, and dynamic studies of Champlain Sea clays. Education Ph.D. in Engineering Seismology, Carleton University (2002) M.Sc. in Geophysics/Seismology, Tehran University (1995) B.Sc. in Applied Physics, Shiraz University (1988) Research Interests His work addresses earthquake ground motion prediction, crustal velocity modeling, and seismic hazard mitigation. He developed the EXSIM method, validated globally by institutions like the Southern California Earthquake Center. His team's Ottawa microzonation studies influenced updates to the National Building Code of Canada (NBCC). Current projects include seismic risk screening tools for existing buildings and dynamic properties of postglacial sediments. Grants & Collaborations Recipient of NSERC Strategic Research Network funding for Canadian Seismic Research. Led the POLARIS geophysical consortium deploying observatories across Canada. Collaborates with GSC, Laval University, and industry partners like Hydro Quebec. Labs & Teams Leads Carleton's Earthquake Modeling and Microzonation group. Data from the POLARIS project supports student research and international studies. Active in developing seismic tools for emergency preparedness and infrastructure resilience.

Nima Ekhtariمشاهده پروفایل

استاد پژوهشی

• Civil Engineering
• Environmental Engineering
• Remote Sensing
• +۳ مورد دیگر

Nima Ekhtari is a Research Professor in the Department of Civil and Environmental Engineering at the University of Houston's Cullen College of Engineering. His office is located in UH NCALM at 5000 Gulf Freeway, Bldg. 4, Rm 216, Houston, TX 77204-5059. Current Research Focus Hydrodynamic flood modeling with deep learning LiDAR terrain uncertainty analysis Earthquake rupture dynamics Environmental remote sensing His work leverages advanced geospatial technologies for disaster management applications, integrating multispectral LiDAR data and satellite imagery for environmental monitoring. Recent publications demonstrate expertise in near-real-time flood forecasting and terrain analysis through deep learning surrogates. Contact: nekhtari@uh.edu

Yauhen Yakimenkaمشاهده پروفایل

پژوهشگر

• Information Theory
• Cybersecurity
• Machine Learning
• +۳ مورد دیگر

Yauhen Yakimenka is a Postdoctoral Research Associate in the Department of Electrical and Computer Engineering at the New Jersey Institute of Technology (NJIT). His research focuses on decentralized systems, privacy-preserving techniques, and coding theory. He holds expertise in machine learning, signal processing, and cybersecurity applications within distributed networks. Yauhen’s work addresses challenges in adversarial environments, including Byzantine attacks, differential privacy, and robust algorithm design for straggler-resilient systems. He has contributed to advancements in compressed sensing, LDPC codes, and information retrieval systems with privacy guarantees. His publications span topics such as secure matrix multiplication, fault-tolerant decentralized learning, and optimizing error correction for short LDPC codes. Research trends in his articles emphasize balancing performance, security, and privacy in distributed computing and communication systems. No scientific awards or grants are explicitly listed in the provided information. He currently advises no students, and no affiliated labs or teams are mentioned.

Sheela Ramannaمشاهده پروفایل

استاد

• Artificial Intelligence (AI)
• Machine Learning
• Multimodal Information Processing
• +۵ مورد دیگر

Dr. Sheela Ramanna is a Professor and Chair of the ACS Graduate Program in the Department of Applied Computer Science at the University of Winnipeg, and an Adjunct Professor at the University of Manitoba. She holds a Ph.D. in Computer Science from Kansas State University, and completed her earlier education at Osmania University, India. Her research focuses on AI, machine learning, and soft computing with applications in natural language processing, multimodal information processing, and topological data analysis. She has been recognized with numerous awards, including multiple UW Merit Awards and Senior Member status in the International Rough Set Society. Dr. Ramanna leads projects funded by NSERC and MITACS, including work on precipitation forecasting, microplastics analysis, and cannabinoid medicine studies. She supervises over 20 graduate students and has authored/co-authored over 150 publications in top journals/conferences. Key roles include editorial positions for EAAI and KES journals, and program chairs for major conferences like IJCRS and RSCTC. Education: B.S. Electrical Engineering (Osmania University), M.S. Computer Science (Osmania University), Ph.D. Computer Science (Kansas State University) Research Interests: Machine Learning, Natural Language Processing, Multimodal Deep Learning, Computational Topology, Rough Set Theory, Social Network Analysis Grants & Projects: NSERC Alliance/Engage Grants, MITACS Accelerate Projects, WeatherLogics collaborations on precipitation forecasting and road condition mapping

Tianren Wuمشاهده پروفایل

استادیار

• Indoor Air Quality (IAQ)
• Indoor Aerosol Dynamics
• Volatile Organic Compounds (VOCs) and Semi-Volatile Organic Compounds (SVOCs)
• +۵ مورد دیگر

Dr. Tianren Wu is an Assistant Professor at the University of Cincinnati's Department of Civil and Architectural Engineering and Construction Management. He specializes in Indoor Air Quality (IAQ) research, focusing on indoor pollutants, human exposure, and health impacts. His work emphasizes developing solutions for healthy living environments through advanced sensing technologies and ventilation strategies. Education Ph.D. in Civil Engineering (2020), Purdue University M.S. in Civil Engineering (2016), Purdue University B.Eng. in Municipal and Environmental Engineering (2013), Shenyang Jianzhu University Research Interests Dr. Wu investigates fate and transport of indoor VOCs/SVOCs, particle dynamics, ozone chemistry, air cleaning technologies, and low-cost sensor development. His studies often integrate real-time measurements using high-resolution mass spectrometers and machine learning tools to optimize sensor performance. Publications Trends His publications emphasize urban-air interactions, indoor pollutants from personal care products, and ventilation system impacts. Recent work highlights trichloramine dynamics in pools and resuspended particles in infants' microenvironments. He collaborates internationally, with studies spanning Europe and the U.S. Advising & Grants Currently seeking motivated PhD students to use advanced CIMS spectrometry for indoor pollutant characterization. His postdoctoral training at Purdue University and École Polytechnique Fédérale de Lausanne (EPFL) Switzerland has strengthened his global research network. Labs & Teams Leads a research team focused on IAQ innovation at UC, with projects in partnership with environmental agencies and building technology firms.

Marcus Chambersمشاهده پروفایل

استاد

• Econometrics
• Time Series Analysis
• Continuous Time Models
• +۲ مورد دیگر

Marcus Chambers is a Professor of Economics at the University of Essex. He joined the faculty in 1989 after completing his PhD at Essex. His research specializes in econometrics, particularly continuous and discrete time models, cointegration, temporal aggregation, and bias reduction methods. He received the Philip Leverhulme Prize (2001-2003) and has held editorial positions at the Journal of Econometrics and Journal of Time Series Analysis. Current research examines locally exact discrete time representations, frequency domain estimation with mixed data, and jackknife methods for near-unit root processes.

Gerald Pageمشاهده پروفایل

مدرس

• Plant Ecophysiology
• Remote Sensing
• Ecosystem Restoration
• +۲ مورد دیگر

Dr. Gerald Page is a Lecturer in Plant Biology at Murdoch University's School of Environmental and Conservation Sciences. His research integrates plant physiological ecology with remote sensing technologies to study plant survival mechanisms in challenging environments. Key investigations include drought resilience in trees, disease impacts on vegetation, and restoration of rangeland ecosystems in Western Australia. Methodologically, Page employs field data collection, near-surface remote sensing, and satellite imagery analysis. He develops computational tools for monitoring leaf temperature dynamics across North American ecosystems. His GitHub repository showcases open-source code for thermal data analysis and chlorophyll fluorescence processing. Education includes a PhD in Botany from the University of Western Australia and an honors degree in Environmental Science.

• Land-Atmosphere Interactions
• Surface Hydrology
• Climate Variability
• +۳ مورد دیگر

Guiling Wang is a Professor in the School of Civil and Environmental Engineering at the University of Connecticut, specializing in land-atmosphere interactions, surface hydrology, and climate change impacts. Her research integrates hydrological and climatological processes to address critical environmental challenges, with recent work focusing on drought mechanisms, extreme precipitation events, and agricultural climate vulnerabilities across diverse regions including the US, South America, and Africa. Dr. Wang received her Ph.D. from the Massachusetts Institute of Technology in 2000. Her educational background established the foundation for her interdisciplinary approach combining engineering, climate science, and environmental systems analysis. Her research program centers on five interconnected domains: Land-Atmosphere Interactions : Quantifying energy/water/carbon exchanges and feedback mechanisms driving extreme events Surface Hydrology : Modeling water fluxes from soil to atmosphere with advanced plant hydraulics integration Climate Variability & Change : Analyzing historical trends and projecting future scenarios using regional climate models Climate Impacts : Assessing agricultural vulnerabilities to heat stress, drought, and precipitation extremes Ecosystem-Climate Interactions : Studying vegetation feedbacks on carbon cycling and climate sensitivity Analysis of her 15 most recent publications (2023-2025) reveals three dominant research thrusts: (1) Development of machine learning frameworks for climate downscaling and extreme event prediction, (2) Mechanistic studies of land-surface feedbacks in compound drought-heat extremes, and (3) Translational research on climate impacts for agricultural systems in vulnerable regions. Her work consistently bridges fundamental process understanding with practical applications for water resource management and food security. As a professor at UConn, Dr. Wang leads the Hydroclimatology Research Group (accessible through hydroclimatology.uconn.edu), mentoring graduate students in climate modeling, hydrological analysis, and environmental data science. Her research program receives support from federal agencies including NSF and NOAA, enabling field campaigns, model development, and international collaborations focused on climate resilience. The Hydroclimatology Lab operates as an interdisciplinary hub where numerical modeling, remote sensing, and in-situ observations converge to study water-climate-ecosystem interactions. Current projects emphasize subseasonal forecasting capabilities, drought early warning systems, and climate adaptation strategies for agricultural communities facing increasing hydroclimatic volatility.

Johan Linderholmمشاهده پروفایل

دانشیار

• Environmental Archaeology
• Geoarchaeology
• Archaeological Chemistry
• +۳ مورد دیگر

Johan Linderholm is an Associate Professor at the Department of Historical, Philosophical and Religious Studies at Umeå University, specializing in Archaeology. He holds the research qualification of Docent, reflecting his expertise in environmental and geoarchaeological studies. His work integrates advanced analytical techniques such as spectral imaging, geochemistry, and micromorphology to investigate past environments and human interactions with landscapes. Research interests include the environmental and climatic impacts on ancient societies, particularly in Scandinavia. Key areas focus on Iron Age settlements, Mesolithic land use, and the legacy of historical environmental changes like the AD 536/540 climate crisis. He leads projects such as the Dobbeltspor Dilling settlement study and the MOBIMA initiative on mobile imaging in archaeology. Collaborations span Nordic countries, with projects in Sweden, Norway, and Denmark. Recent work emphasizes interdisciplinary methods, such as multi-block chemometrics for geological sample analysis and GIS-based environmental reconstructions for infrastructure projects. His contributions include studies on soil formation in Arctic contexts and the ecological imperialism effects of invasive species like earthworms. Linderholm is also affiliated with the Environmental Archaeological Lab at Umeå University, advancing research on paleoenvironmental data and archaeological site preservation. Key projects include the Intercity Dobbeltspor Dilling settlement analysis and the Fjällbacka coastal archaeology initiative. His publications bridge archaeology with environmental science, addressing both historical climate events and modern conservation challenges.

Mahadevan Ganeshمشاهده پروفایل

استاد

• Computational Electromagnetics
• High-Performance Computing
• Wave Propagation
• +۴ مورد دیگر

Mahadevan Ganesh is a Professor in the Department of Applied Mathematics and Statistics and the Department of Computer Science at the Colorado School of Mines. He also serves as an Affiliate Professor in Electrical Engineering. His primary research interests include stochastic algorithms, model reduction, multiscale methods, uncertainty quantification, computational electromagnetics, and high-performance computing. His work addresses challenges in wave propagation, scattering, and numerical solutions for partial differential equations on complex domains. He has developed advanced algorithms for electromagnetic and acoustic scattering, including T-matrix methods, finite element approaches, and high-order numerical schemes. His research often integrates parallel computing and uncertainty quantification to address real-world applications such as ground motion forecasting and seismic risk modeling. Dr. Ganesh has published extensively in top journals, focusing on topics like scattering theory, integral equations, and computational methods for heterogeneous media. His recent work includes advancements in neural network-driven inverse scattering problems and efficient algorithms for large-scale particle configurations. He teaches courses such as Parallel Scientific Computing, Mathematical Biology, and Numerical Methods for Partial Differential Equations, reflecting his expertise in computational science and engineering. His contributions span theoretical analysis, algorithm development, and high-performance computing applications, with a strong emphasis on interdisciplinary research. He collaborates on projects involving ground motion modeling, stochastic wave propagation, and data-driven uncertainty quantification frameworks.

Rhein Parriمشاهده پروفایل

استاد

• Neuroscience
• Astrocyte Signaling
• Electrophysiology
• +۳ مورد دیگر

Rhein Parri is a Professor of Pharmacology at Aston University, affiliated with the Aston Pharmacy School and multiple research groups including the Pharmacology & Translational Neuroscience Research Group (PTNRG). His research focuses on astrocyte-neuron signaling in the thalamus, employing electrophysiology and calcium imaging to study glial modulation of synaptic transmission and neuronal excitability. Education includes a BSc in Physiology with Pharmacology and a PhD in Neurophysiology from the University of Southampton. He has held academic positions at institutions such as Cardiff University and the University of California, San Francisco, progressing from Lecturer to Professor. Research interests emphasize astrocyte function in health and disease, optogenetic techniques, and neurodegenerative disorders like Alzheimer’s. Collaborations span optogenetics engineering, organoid intelligence, and interdisciplinary projects with statistical physics and biomedical engineering. Teaching responsibilities include coordinating modules on neuronal excitability and cardiovascular physiology. His work bridges basic neuroscience with translational applications, contributing to advancements in glial biology and therapeutic strategies for neurological conditions.

Viktor Dreminمشاهده پروفایل

پژوهشگر ارشد

• Biophotonics
• Biomedical Optics
• Biomedical Engineering
• +۹ مورد دیگر

Dr. Viktor Dremin is a Research Fellow at the Aston Institute of Photonic Technologies (AiPT), part of the College of Engineering and Physical Sciences at Aston University. He holds a PhD and is a Fellow of the Higher Education Academy (FHEA). His research focuses on biophotonics, biomedical optics, and optical imaging technologies. Key areas include laser Doppler flowmetry, fluorescence spectroscopy, and hyperspectral imaging for medical diagnostics. Dr. Dremin leads projects on cerebral blood flow monitoring, singlet oxygen generation for theranostics, and wearable medical sensors. Education: PhD (details unspecified), FHEA qualification Research Interests: Biomedical engineering applications, non-invasive diagnostics, optical sensors, machine learning integration His work spans collaborations in neurovascular dynamics, liver cancer detection, and 3D skin model analysis. He has authored 144+ research outputs, including peer-reviewed articles and datasets. Notable contributions include a hyperspectral imaging system for skin diagnostics and wearable devices for cardiovascular monitoring. Dr. Dremin's lab develops optical tools for minimally invasive surgery and metabolic assessments. Recent studies emphasize transcranial cerebral blood flow analysis, singlet oxygen's role in cellular bioenergetics, and AI-driven maxillary sinus diagnostics. His datasets explore skin polarization and intestinal perfusion under ischemia. Collaborations include institutions in Russia and the UK, focusing on translational medical optics.

Nicolas Lejeuneمشاهده پروفایل

پژوهشگر

• Disorders of Consciousness
• Pain Perception
• Neurophysiology
• +۵ مورد دیگر

Nicolas Lejeune is a postdoctoral researcher at the Coma Science Group within the Université Catholique de Louvain (UCLouvain). He specializes in disorders of consciousness (DoC) following acute brain injuries, focusing on non-invasive neurophysiological assessments of pain perception. His work bridges clinical neurorehabilitation with advanced research, particularly in collaboration with Prof. André Mouraux from UCLouvain's Institute of Neuroscience. Research Focus Pain-Consciousness Interaction: Developing bedside neurophysiological methods to assess pain in DoC patients Epilepsy Management: Analyzing seizure patterns and treatment protocols in prolonged DoC Ethical Frameworks: Exploring moral dimensions of care and decision-making Therapeutic Development: Investigating pharmacological agents like apomorphine and ketamine Publication Trends Nicolas' recent work spans both clinical neuroscience and interdisciplinary physics applications. His 15 most recent publications focus on transcranial stimulation, pharmacological interventions, and disorders of consciousness assessment tools. Notably, his research includes neuroimaging of post-concussive symptoms, validation of aphasia evaluation methods, and exploration of near-death experience models. Technical Contributions While most publications align with clinical neuroscience, his work extends to quantum physics applications with studies on superconducting nanostructures and metasurface technology. This interdisciplinary approach appears to explore neural interface materials and advanced monitoring systems.

Wouter Maesمشاهده پروفایل

استاد

• Organic Chemistry
• Materials Science
• Organic Electronics
• +۳ مورد دیگر

Prof. Wouter Maes is a Full Professor at Hasselt University, leading the DSOS research group focusing on organic semiconductor materials for electronics and healthcare. He holds a PhD in organic chemistry from KU Leuven (2005) and has held academic roles from Assistant (2009) to Full Professor (2021). His research emphasizes conjugated polymers for photovoltaics, sensors, and biomedical applications. He has authored over 200 articles (h-index 45, 6600+ citations) and serves as President of the Chemistry Department. Education: PhD in Organic Chemistry, KU Leuven, 2005 (Advisor: Prof. W. Dehaen) Postdoctoral Fellowship, Research Foundation – Flanders, KU Leuven Research Interests: Design of conjugated polymers for organic electronics Near-infrared photodetectors and LEDs Material precision and defect analysis UAV-based remote sensing applications in agriculture and ecology Therapeutic nanocarriers for biomedical delivery Key Contributions: - Pioneered studies on homocoupling defects in conjugated polymers - Developed novel materials for wavelength-selective organic photodetectors - Advanced UAV remote sensing techniques for crop monitoring and disease detection Grants & Labs: - Oversees the DSOS expertise group - Collaborates on EU-funded projects in organic electronics and precision agriculture