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Sheela RamannaView profile

Professor

• Artificial Intelligence (AI)
• Machine Learning
• Multimodal Information Processing
• +5 more

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 WuView profile

Assistant Professor

• Indoor Air Quality (IAQ)
• Indoor Aerosol Dynamics
• Volatile Organic Compounds (VOCs) and Semi-Volatile Organic Compounds (SVOCs)
• +5 more

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 ChambersView profile

Professor

• Econometrics
• Time Series Analysis
• Continuous Time Models
• +2 more

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 PageView profile

Lecturer

• Plant Ecophysiology
• Remote Sensing
• Ecosystem Restoration
• +2 more

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
• +3 more

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 LinderholmView profile

Associate Professor

• Environmental Archaeology
• Geoarchaeology
• Archaeological Chemistry
• +3 more

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 GaneshView profile

Professor

• Computational Electromagnetics
• High-Performance Computing
• Wave Propagation
• +4 more

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 ParriView profile

Professor

• Neuroscience
• Astrocyte Signaling
• Electrophysiology
• +3 more

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 DreminView profile

Research Fellow

• Biophotonics
• Biomedical Optics
• Biomedical Engineering
• +9 more

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 LejeuneView profile

Researcher

• Disorders of Consciousness
• Pain Perception
• Neurophysiology
• +5 more

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 MaesView profile

Professor

• Organic Chemistry
• Materials Science
• Organic Electronics
• +3 more

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

Jingbo WangView profile

Assistant Professor

• Neutrino Physics
• Particle Physics
• Experimental Physics
• +3 more

Jingbo Wang is an Assistant Professor of Physics at the South Dakota School of Mines & Technology (SDSMT). His research focuses on precision measurements of neutrino properties to explore physics beyond the Standard Model. He is actively involved in experiments like the Deep Underground Neutrino Experiment (DUNE) and the Accelerator Neutrino-Neutron Interaction Experiment (ANNIE), leveraging Liquid Argon Time Projection Chambers (LArTPCs) and gadolinium-loaded water detectors. His work addresses neutrino oscillation parameters, mass ordering, and CP violation. Wang holds a B.S. and Ph.D. in Physics from Tsinghua University. Prior to SDSMT, he held roles including Assistant Project Scientist at UC Davis, Intensity Frontier Fellow at Fermilab, and Postdoctoral positions at UC Davis and Argonne National Laboratory. His research emphasizes experimental neutrino physics with a focus on detector technology advancements. Key areas include optimizing LArTPC performance, analyzing neutron interactions, and developing machine learning techniques for event reconstruction. He contributes to international collaborations like DUNE, which aims to revolutionize our understanding of neutrino behavior and the universe's matter-antimatter imbalance. Wang’s technical expertise spans neutrino detection systems, scintillation light analysis, and GPU-accelerated simulations. His recent work addresses challenges in low-energy physics, neutron cross-section measurements, and background mitigation strategies critical to next-generation neutrino experiments.

Paul RimmerView profile

Researcher

• Astrophysics
• Planetary Science
• Prebiotic Chemistry
• +4 more

Dr. Paul Rimmer is a researcher in Astrophysics at the University of Cambridge, affiliated with the Ray Dolby Centre. His work focuses on planetary atmospheres, prebiotic chemistry, and astrobiology, with particular emphasis on Venus and exoplanets. Key research areas include atmospheric composition modeling, cosmic ray ionization effects, and the search for biosignatures in extraterrestrial environments. Research interests span interdisciplinary topics such as the origin of life, chemical kinetics in early planetary systems, and the evolution of atmospheric chemistry under extreme conditions. His studies often integrate observational data with advanced computational models to explore planetary habitability and atmospheric dynamics. Recent work has concentrated on Venus's cloud chemistry, phosphine detection anomalies, and the implications for potential aerial biospheres. He also investigates exoplanet atmospheres around M-type stars, emphasizing the role of stellar radiation and cosmic particle interactions. Publications frequently address methodological advancements in spectroscopy and atmospheric analysis, including novel techniques for detecting prebiotic molecules and quantifying abiotic processes in planetary environments.

• Antarctic Ice Dynamics
• Oceanography
• Climate Modeling
• +3 more

Dr David Gwyther is a Research Fellow at the School of the Environment, University of Queensland. His work focuses on Antarctic ice shelf dynamics, ocean-ice interactions, and climate modeling. He specializes in coupled ice sheet-ocean modeling, data assimilation techniques, and the impacts of oceanographic processes on glacial stability. His research addresses critical questions about Antarctic ice mass loss and its contribution to sea level rise. Key research areas include basal melt mechanisms of ice shelves, the role of tides and eddies in ice-ocean systems, and improving computational efficiency in coupled models. He collaborates on projects like the ISOMIP+ and FISOC frameworks, advancing interdisciplinary approaches to polar environmental science. His recent contributions include studies on Totten Glacier's acceleration observed via satellite records, the influence of subglacial drainage on melt rates, and the development of the Whole Antarctic Ocean Model (WAOM). He also explores observation system optimization for western boundary currents and the integration of observational data into climate models. Dr Gwyther’s work bridges theoretical modeling with field observations, leveraging autonomous platforms and remote sensing technologies. His findings contribute to understanding past and future Antarctic climate responses, supporting global climate projections and policy-relevant research.

• Medical Devices and Sensors
• Medical Imaging
• Medical Signal Processing
• +3 more

Professor Juha Toyras is a Professorial Research Fellow in the School of Electrical Engineering and Computer Science at The University of Queensland, Australia. He also serves as the Head of Research and Innovation at Kuopio University Hospital and Wellbeing Services County of North Savo, and as Professor of Medical Physics and Engineering at the University of Eastern Finland. His research spans biomedical engineering with a focus on medical devices, sensors, imaging, signal processing, and connective tissue biomechanics. He is particularly known for his work in sleep technology and analytics, as well as cartilage biomechanics and medical diagnostics. Since 2004, he has been Vice/Co-Head of the Biophysics of Bone and Cartilage research group and Co-Head of the Sleep Technology and Analytics group at the University of Eastern Finland, leading substantial research teams comprising three professors, approximately 20 research fellows and postdocs, and over 50 PhD students. Professor Toyras has published over 320 peer-reviewed scientific papers with more than 14,000 citations and an H-index of 63. His recent research demonstrates a strong interdisciplinary approach combining biomedical engineering, sleep medicine, and orthopedics, with particular emphasis on developing novel diagnostic tools using advanced imaging techniques, signal processing, and machine learning algorithms for clinical applications. He has successfully supervised 52 PhD students and currently oversees approximately 20 PhD students across institutions. His research has been supported by various European and Australian funding sources. Notably, his work has led to practical medical innovations including the patented Bittium BrainStatus EEG-electrode set for emergency medicine, which is CE-approved and currently in global use.