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Konstantinos FokianosView profile

Professor

• Time Series Analysis
• High-Dimensional Statistics
• Integer-Valued Time Series
• +2 more

Konstantinos Fokianos is a Professor of Statistics at the University of Cyprus. He completed undergraduate studies in Mathematics at the University of Ioannina and earned his M.A. (1993) and Ph.D. (1996) in Statistics from the University of Maryland, USA. His academic career includes positions at Ohio State University (Visiting Assistant Professor), Lancaster University (2018-2020), and the University of Cyprus where he advanced from Lecturer to full Professor. Professor Fokianos specializes in time series analysis with focus areas including integer-valued time series models, high-dimensional time series, spectral analysis, semiparametric modeling, and isotonic estimation. His methodological research encompasses network autoregression, multivariate count time series, causal inference for health questionnaires, and clustering techniques. Applied work includes epidemiological network analysis, medical prognostics for leukemia, and tourism competition modeling. He has held visiting positions at Ludwig Maximilians University, National Institutes of Health, EPFL, and other institutions. Elected member of the International Statistical Institute since 2005, he serves on editorial boards of Journal of Time Series Analysis and Statistical Modeling, and edits Springer's 'Frontiers in Probability and Statistical Sciences' series.

Jennifer DruhanView profile

Associate Professor

• Geochemistry
• Hydrogeology
• Stable Isotope Geochemistry
• +4 more

Jennifer Druhan is an Associate Professor in the Department of Earth Science & Environmental Change and holds a joint appointment in the Department of Civil and Environmental Engineering at the University of Illinois at Urbana-Champaign. Her research focuses on reactive transport processes in porous media, particularly integrating stable isotope fractionations into numerical models to identify underlying geochemical mechanisms. She leads the Druhan Lab, which explores interdisciplinary topics such as carbonate mineral precipitation, sulfate reduction in bioremediation, and the effects of physical heterogeneity on solute transport. Her work combines field studies (e.g., Rifle IFRC site in Colorado) with laboratory experiments and computational modeling. Key areas include quantifying dust impacts on critical zone chemistry, ecological regulation of riverine weathering, and lithium isotope signatures during storm events. She has pioneered methods using nuclear imaging tomography to visualize 3D tracer distributions in porous media, enhancing geostatistical modeling of permeability changes during reactive flow. Her recent publications highlight advancements in reactive transport modeling for weathering dynamics, biogeochemical cycling in intensively managed landscapes, and the role of nanophases in critical zone processes. Collaborative projects span shale caprock mechanics, AI-driven solute prediction, and climate change impacts on catchment biogeochemistry. Affiliations: School of Earth, Society & Environment; Coordinated Science Lab Labs/Teams: Druhan Lab, Critical Interface Network (CINet) Grants: NSF-funded projects on reactive transport modeling and shale reservoir dynamics

• Environmental statistics
• Bayesian statistics
• Statistical computing
• +3 more

Andrew O. Finley is a Professor at Michigan State University with a joint appointment in the Departments of Forestry and Statistics & Probability. He is also affiliated with the Ecology, Evolutionary Biology, and Behavior Graduate Program. His research focuses on environmental statistics, Bayesian methods, spatial statistics, and statistical computing, particularly in monitoring and modeling ecological processes. He leads the Geospatial Lab, supported by NSF, NASA, USDA Forest Service, and NPS grants, utilizing a Linux cluster for large-scale data analysis. Education : PhD in Natural Resources Science and Management (University of Minnesota, 2006) MS in Statistics (University of Minnesota, 2007) MS in Forestry (University of Massachusetts, 2003) BS in Forestry (Pennsylvania State University, 2000) Research Interests : Finley develops statistical methodologies for integrating disparate data sources to study environmental processes, with applications in spatial-temporal modeling of ecosystems. His work emphasizes hierarchical models, Bayesian approaches, and scalable geostatistical techniques for large datasets. Recent projects include analyzing tree species decline in western U.S. forests, bird abundance using acoustic data, and ecological memory in boreal tree growth. Advising & Grants : He mentors graduate students in statistical ecology and computational methods. Current advisees include Elliot Shannon, Grayson White, and Hunter Stanke. His lab has secured funding from NSF, NASA, and USDA for projects on forest dynamics, biodiversity, and geostatistical modeling. Notable software contributions include the R packages spBayes , spNNGP , and rFIA for spatial analysis and forest inventory. Labs & Collaborations : The Geospatial Lab at Michigan State University focuses on advancing statistical methods for environmental data science. Collaborations include work on macrosystems ecology, climate change impacts, and integrating remote sensing with field data for forest management.

Hakan TanyașView profile

Assistant Professor

• Landslide Hazard Analysis
• Earthquake Impact Studies
• Geohazard Modeling
• +3 more

Hakan Tanyaș is an Assistant Professor in Applied Earth Sciences specializing in geohazards, earthquake impacts, and environmental modeling. His research focuses on landslide dynamics, post-seismic recovery, submarine volcanoes, and cascading disasters. He has contributed to global inventories of submarine mud volcanoes and developed data-driven models for hazard assessment. Key Research Areas: Landslide Hazard Analysis, Earthquake Impact Studies, Submarine Volcanology Recent Contributions: Finite element methods for hillslope stability, atmospheric river-earthquake interactions His work integrates advanced computational techniques like Graph Transformers and finite element analysis to address complex geohazards. Collaborations include projects on pan-European landslide risk and cryospheric hazards in Arctic regions.

• Geomechanics
• Sustainable Resource Recovery
• Deep-Earth Energy Systems
• +7 more

Professor Ranjith Pathegama Gamage is a Professor in Geomechanics Engineering at Monash University's Department of Civil and Environmental Engineering, within the Faculty of Engineering. He serves as Director of International Affairs and leads global research initiatives in sustainable resource recovery, deep-earth energy systems, and climate resilience. His work aligns with UN SDGs 7 (Affordable Energy), 9 (Industry Innovation), and 13 (Climate Action). Education: PhD (University of Wollongong, Australia) and BSc (University of Moratuwa, Sri Lanka). Professional roles include ARC Future Fellow and leadership in industry consortia. Key research areas include CO₂ sequestration, geothermal energy, unconventional gas recovery, and eco-green cement technologies. Notable awards: Humboldt Research Award, Senior Fulbright Fellowship, Fellowships from ATSE, CAE, and INAE. Supervised over 100 PhD students and 53 researchers, many holding senior academic/industry roles globally. Active projects focus on hydrogen storage in depleted reservoirs, CO₂-based rock stimulation, and Climate Action Plans for resource recovery. Collaborates internationally with funding from ARC, industry, and foundations like Humboldt and Fulbright.

Sharif MahmoodView profile

Associate Professor

• Causal Inference
• Machine Learning
• Experimental Design
• +3 more

Sharif Mahmood is an Associate Professor in the Department of Mathematics at the University of Central Arkansas (UCA). His research focuses on causal inference, machine learning, and experimental design, particularly in developing methodologies to address confounding and bias in observational studies while optimizing experimental designs for causal identification. He holds a Ph.D. in Statistics and has contributed extensively to interdisciplinary research at the intersection of statistics, public health, and environmental science. Education background includes advanced training in statistical theory and applications, though specific degree details are not provided in the source text. Research interests emphasize leveraging machine learning to enhance causal reasoning and bridging gaps between observational and experimental studies. Key research areas include: Causal effect estimation in non-experimental data Algorithmic advancements in machine learning for statistical problems Optimization of experimental design for treatment allocation Recent work spans diverse domains such as metabolic syndrome analysis in Bangladesh, disaster recovery modeling post-tornadoes, and fiscal policy impacts on government debt dynamics. His methodologies have applications in public health policy, environmental risk assessment, and econometric modeling. No scientific awards or grants are explicitly mentioned in the provided text. He advises no listed students but collaborates extensively with interdisciplinary teams. His office is located in MCS 204, and he can be reached at smahmood1@uca.edu.

Jonathan GreenbergView profile

Associate Professor

• Remote Sensing
• Climate Change
• Ecosystems
• +3 more

Jonathan Greenberg is an Associate Professor in Remote Sensing at the Department of Natural Resources & Environmental Science, University of Nevada, Reno. He is affiliated with the Max C. Fleischmann College of Agriculture, Biotechnology & Natural Resources. His research focuses on using remote sensing technologies like LiDAR, hyperspectral imaging, and satellite data to study climate change impacts on ecosystems, vegetation dynamics, and land-use changes. Key areas include vegetation response to climate shifts, wildfire fuel dynamics, and carbon sequestration modeling. Greenberg holds a B.S. from Boston University (1996) and a Ph.D. from the University of California, Davis (2004). His work integrates geospatial analysis with environmental science, emphasizing high-resolution data for ecological monitoring and management. He leads the Global Environmental Analysis and Remote Sensing Lab, advancing methods for large-scale environmental data processing. Recent research highlights include quantifying climate-driven vegetation changes across the U.S., developing robust geospatial analysis tools, and modeling fire behavior and carbon dynamics in California forests. His interdisciplinary approach bridges remote sensing innovations with ecological and climatic challenges, addressing critical issues like wildfire mitigation and climate adaptation. Greenberg has contributed to over 50 peer-reviewed publications since 2005, with a focus on remote sensing applications in vegetation mapping, hydrology, and ecosystem modeling. His lab collaborates on projects such as the GigaFire initiative, leveraging cloud computing for large-scale fuels and carbon mapping.

Georg KosakowskiView profile

Researcher

• Coupled physical and chemical processes in porous media
• Reactive transport modeling
• Long-term evolution of nuclear waste materials
• +3 more

Georg Kosakowski is a Senior Scientist at the Paul Scherrer Institute (PSI), Switzerland, within the Nuclear Energy and Safety Research Division. His research focuses on coupled physical and chemical processes in heterogeneous porous media, particularly in the context of nuclear waste repositories. He holds a Dr. rer. nat. from the University of Bonn and a Habilitation from the University of Tübingen. His work emphasizes reactive transport modeling, long-term material evolution (e.g., cement, clays), and numerical risk assessment for nuclear waste storage. Research interests include the geochemical evolution of repository materials, gas production in waste repositories, and interface reactions between cement and bentonite. He has contributed to over 100 peer-reviewed publications, focusing on topics like coupled multi-phase flow, mineral precipitation/dissolution, and computational methods. His studies often involve collaboration with institutions like Nagra (Switzerland) and Hiroshima University (Japan). Publications highlight advancements in modeling tools (e.g., OpenGeoSys-Gem, FEniCS-Reaktoro), experimental validation of transport processes, and repository safety assessments. Teaching includes geostatistics at the University of Bern and specialized courses on thermodynamic modeling in Japan. Labs/Teams: He leads research within the Laboratory for Waste Management at PSI, contributing to Switzerland’s nuclear waste disposal program. His work supports the development of engineered barriers and long-term safety evaluations for geological repositories.

• Spatial Statistics
• Machine Learning
• Environmental Science
• +3 more

Hao Zhang is a Research Fellow at the Department of Mechanical Engineering, Purdue University. His work focuses on spatial statistics, machine learning, and environmental science, with applications in climate modeling, ecosystem analysis, and geostatistical methodologies. He has contributed to studies on urbanization impacts, precipitation patterns, and landslide hazard assessment. His research integrates computational techniques with domain-specific challenges, emphasizing interdisciplinary approaches. Notable contributions include developing novel methods for spatial data analysis, applying neural networks to geoscience problems, and exploring trade-offs between economic development and ecological sustainability. His work often bridges theoretical advancements with practical applications in environmental monitoring and risk management.

Siamak KhorramView profile

Adjunct Professor

• Remote Sensing
• Geospatial Analysis
• Image Processing
• +1 more

Siamak Khorram is an Adjunct Professor in the Department of Environmental Science, Policy, & Management at the University of California, Berkeley. His research focuses on remote sensing, geospatial analysis, and computational methods for land cover classification and environmental monitoring. He developed foundational techniques in neural network-based image classification and correspondence analysis fusion, with applications spanning urban mapping, land use change detection, and water quality modeling. His publications demonstrate consistent innovation in remote sensing methodologies since the 1980s. Professor Khorram established the Computer Graphics Center (later Center for Earth Observation) at North Carolina State University and held leadership roles at the International Space University, including Dean and Vice President for Academic Programs. He currently serves on ISU's Board of Trustees.

• Climate Change
• Remote Sensing
• Environmental Science
• +3 more

Tingbao Xu is a researcher affiliated with the Fenner School of Environment & Society at The Australian National University (ANU). His work focuses on climate change, remote sensing, and environmental science, with expertise in spatial analysis and hydrological modeling. He leads research projects addressing climate resilience, precipitation patterns, carbon emissions, and water resource management. Key areas of research include: Climate change impacts on ecosystems and water resources Development of gridded climate datasets (e.g., ANUClimate) Remote sensing applications for flood mapping, vegetation dynamics, and urban metabolism Interdisciplinary approaches to environmental policy and community adaptation He has contributed to over 40 peer-reviewed publications and actively supervises research students. His projects span Australia, China, and the Himalayan region, emphasizing practical solutions for climate resilience and sustainable resource management.

Matthew DennisView profile

Senior Lecturer

• Urban Ecology
• Environmental Sciences
• Geographic Information Science
• +3 more

Matthew Dennis is a Senior Lecturer in Geography at the University of Salford, specializing in Urban Ecology and Geographic Information Science. He holds a PhD in Urban Social-Ecological Systems and dual undergraduate degrees in Wildlife Conservation and French/English Studies. His research focuses on rewilding, biodiversity conservation, and the intersection of urban green spaces with human well-being. He also serves as an Associate Researcher at the University of Salford and leads or collaborates on projects such as CASTOR (Creative Adaptive Solutions for Treescapes of Rivers) and MEaSURE (Maximising Ecosystem Services in Urban Environments). Key research interests include beaver ecology, urban climate dynamics, and landscape connectivity. He has published extensively on topics like floodplain modeling, habitat fragmentation, and the socio-ecological impacts of urban green infrastructure. Notable contributions include spatial analyses of beaver dam effects and frameworks for integrating ecological restoration with urban planning. His work aligns with UN Sustainable Development Goals related to environmental sustainability and health equity. Recent projects include developing national-scale models for beaver habitat assessment and evaluating urban green space interventions for older populations' physical activity and mental health. He has also contributed expert commentary on beavers' ecological benefits and limitations, emphasizing balanced perspectives on rewilding.

Goh Siang HuatView profile

Associate Professor

• Geotechnical Engineering
• Earthquake Engineering
• Soil-Pile Interaction
• +5 more

Dr. Goh Siang Huat is an Associate Professor in the Department of Civil Engineering at the National University of Singapore. He holds a B.Eng. (First Class Honours) and M.Eng. from NUS (1991, 1995) and a Ph.D. from Cornell University (2001). His research focuses on geotechnical centrifuge modeling, seismic soil-pile interaction, and large deformation numerical analysis. He has contributed to the recovery efforts of the World Trade Centre post-9/11 and led roles in the Centre for Protective Technology and Underground Singapore Conference. Education: B.Eng. (First Class Honours), National University of Singapore (1991) M.Eng. (Civil), National University of Singapore (1995) Ph.D., Cornell University (2001) Research Interests: Geotechnical Centrifuge Modeling of Dynamic Events Numerical Analysis of Seismic Soil-Pile Interaction Large-Scale Parallel Computations Offshore Foundation Design (Spudcans, Lattice Legs) Recent Trends in Publications: His recent work emphasizes computational methods for seismic response analysis, geotechnical reliability under spatial variability, and machine learning applications in subsurface modeling. Key themes include spudcan foundations, slope stability, and gas reservoir dynamics. Awards: Silver Award, Singapore Accreditation Council Assessor (2012) Bronze Award, Singapore Accreditation Council Assessor (2009) Teaching & Service: He teaches Geotechnical Finite Element Methods and has served as Associate Editor for Journal of Earthquake and Tsunami . His roles include Operations Manager at the Centre for Protective Technology and organizer of APSSRA2012 and Underground Singapore Conference. Labs/Teams: Active in the Centre for Protective Technology within the Faculty of Engineering, focusing on geotechnical innovation and disaster resilience.

Jery Russell StedingerView profile

Professor

• Hydrology
• Water Resources Engineering
• Risk Analysis
• +6 more

Jery Russell Stedinger is a Professor in the Department of Civil and Environmental Engineering at Cornell University, affiliated with the College of Engineering. He holds a B.A. in Applied Mathematics from the University of California, Berkeley (1972), and a Ph.D. in Environmental Systems Engineering from Harvard University (1977). His career includes sabbaticals at institutions such as the U.S. Geological Survey, U.S. Army Corps of Engineers, and Technische Universität Wien. Stedinger’s research focuses on statistical methodologies in hydrology, flood frequency analysis, and water resource systems optimization. He has pioneered approaches to incorporate historical and paleoflood data into risk assessments and has contributed to national guidelines like Bulletin 17C for flood flow frequency. His work extends to geothermal resource assessment and energy systems engineering. Awarded the ASCE Ven Te Chow Award (2014) and elected to the National Academy of Engineering (2014), Stedinger has authored over 140 professional papers and textbooks, including co-authorship of the foundational Water Resource Systems Planning and Analysis . He teaches courses on uncertainty analysis (CEE 3040) and risk management (CEE 5970), mentoring students in systems engineering and environmental management. Stedinger serves on committees for dam safety, flood risk, and water resources policy, advising federal agencies like the USACE and Bureau of Reclamation. His contributions bridge academic research, policy, and practical applications in hydrology and sustainable engineering.

Haruko Murakami WainwrightView profile

Assistant Professor

• Environmental Informatics
• Nuclear Waste Management
• Radiation Monitoring
• +5 more

Haruko Murakami Wainwright is an Assistant Professor at the Massachusetts Institute of Technology (MIT), affiliated with the Department of Nuclear Science and Engineering. Her research focuses on environmental informatics, integrating mechanistic modeling and machine learning to address challenges in nuclear waste management, radiation monitoring, and environmental resilience. She leads interdisciplinary projects such as the DOE’s Advanced Long-term Environmental Monitoring Systems (ALTEMIS) and the Artificial Intelligence for Earth System Predictability (AI4ESP) initiative. Education: BEng in Engineering Physics from Kyoto University (2003), MS and PhD in Nuclear Engineering and Statistics from UC Berkeley (2006–2010). Research emphasizes Bayesian geostatistical methods, real-time environmental monitoring systems, and applications in watershed science. Notable contributions include radiation dose rate mapping post-Fukushima, groundwater contamination modeling, and sustainable remediation strategies. Her work bridges nuclear engineering, environmental science, and data science, with a focus on resilience to environmental disasters and sustainable energy waste management.