جستجوی استاد راهنمای دانشگاهی

Neil Coffeeمشاهده پروفایل

استاد

• Geographic Information Systems (GIS)
• Spatial Epidemiology
• Urban Health
• +۳ مورد دیگر

Professor Neil Coffee is a Geographer and Professor at Deakin University, where he leads the Centre for Australian research into Access (CARA). With over 35 years of experience, he pioneered the application of Geographic Information Systems (GIS) to social and health research in Australia through initiatives including the National Key Centre for Social Applications of GIS (University of Adelaide, 1995-2000), the South Australian Epidemiological GIS (SAEGIS), and the Australian Geospatial Health Lab (AGeoH-L). Coffee's research integrates spatial techniques with public health and urban studies, focusing on developing environmental exposure metrics like walkability indices and accessibility measures. His work bridges geography, epidemiology, and urban planning through novel applications including Cardiac ARIA and real-time surveillance systems that merge administrative data with physical/social environmental risk assessments. His publication trajectory reveals consistent innovation in spatial analytics, evolving from foundational walkability frameworks (2007) to sophisticated analyses of property value determinants (2020) and longitudinal population density visualization (2016). This progression demonstrates increasing methodological complexity in examining urban-spatial relationships while maintaining core focus on environmental health determinants. Coffee established key research infrastructure including SAEGIS, AGeoH-L at the University of Canberra, and currently directs CARA at Deakin University, creating integrated platforms for geospatial health research that combine government administrative data with environmental exposure modeling.

• Rock Mechanics
• Fault Mechanics
• Geo Energy
• +۷ مورد دیگر

Dr. Wenzhuo Cao is an Assistant Professor at the Faculty of Geosciences , Utrecht University , specializing in coupled subsurface processes within the Department of Earth Sciences and the Earth Simulation Lab . His work bridges geomechanics, geo-energy, and sustainability. Key research areas include: Induced seismicity from fluid injection and mining Thermo-hydro-mechanical (THM) modeling for energy systems Rock fracture and permeability under stress Subsurface storage (CO2, geothermal, hydrogen) His 2023-2025 publications focus on forecasting seismic risks, optimizing energy storage, and experimental rock deformation. Recent works employ numerical simulations and statistical models to address mining hazards and geothermal systems. Current affiliations: Assistant Professor, Utrecht University Experimental Rock Deformation/HPT Group Pathways to Sustainability Research Theme

• Computational Subsurface Hydrology
• Discrete Fracture Network Modeling
• Anomalous Transport in Porous Media
• +۷ مورد دیگر

Rishi Parashar serves as a Research Professor in Hydrologic Sciences at the Desert Research Institute (DRI), affiliated with the University of Nevada Reno's Graduate Program of Hydrologic Sciences. His work bridges computational hydrology, geothermal systems, and microbial transport processes within fractured rock environments. Education: Ph.D. in Civil Engineering, Purdue University (2008) M.S. in Civil Engineering, Purdue University (2003) B.S. in Civil Engineering, Indian Institute of Technology, Roorkee (2001) Parashar's research centers on computational subsurface hydrology , where he develops discrete fracture network (DFN) models to simulate anomalous transport in porous media and upscaling techniques for complex flow systems. His hydro-bio-chemical systems work examines microbial motility, biofilm growth, and biogeochemical reactions governing contaminant fate. In thermo-hydro-mechanical interactions , he investigates enhanced geothermal systems (EGS) and induced seismicity through coupled process modeling. Recent publications reveal increasing integration of machine learning with traditional hydrological modeling, particularly in particle tracking and reactive transport upscaling. Analysis of his 15 most recent articles (2021-2025) shows dominant focus areas: 40% on microbial transport in porous media (including bacterial motility and biofilm effects), 30% on fracture network modeling and upscaling, 20% on contaminant remediation (particularly arsenic), and 10% on geothermal system dynamics. His collaborative work spans environmental engineering, computational science, and microbiology, with frequent co-authorship patterns indicating strong mentorship of early-career researchers. Parashar actively secures research funding through Department of Energy contracts, particularly for Nevada National Security Site projects involving fractured rock characterization. His advising portfolio includes numerous graduate students leading publications in high-impact journals like Water Resources Research and Advances in Water Resources . Current projects involve quantum algorithms for well capture zone determination and heat-sensitive epoxy foams for geothermal permeability alteration. Research Infrastructure: His work leverages DRI's computational resources for large-scale DFN simulations and collaborates with DOE laboratories on experimental validation through microfluidic devices and field-scale tracer tests. The Hydrologic Sciences division provides access to advanced characterization facilities for fractured rock systems.

• Constrained Clustering
• Explainable AI
• Constraint Programming
• +۴ مورد دیگر

Thi-Bich-Hanh DIEP-DAO serves as a Lecturer with Habilitation à Diriger des Recherches (HDR) at the University of Orleans, where she is affiliated with the LIFO laboratory (Laboratory of Informatics of Orléans). She holds significant administrative roles including THAT Lab correspondent at the Doctoral School and Member of the Board, demonstrating leadership in academic governance and doctoral education. Her research centers on constrained clustering methodologies, with evolving focus areas including explainable AI, constraint programming applications, and knowledge integration in machine learning systems. Early work established foundational approaches for constraint-based clustering using declarative frameworks, while recent publications demonstrate sophisticated extensions to mineral prospectivity mapping, social media analysis, and knowledge graph-enhanced image classification. Her research consistently bridges theoretical constraint programming with practical applications across diverse domains. Analysis of her publication trends reveals increasing emphasis on explainability and knowledge integration since 2020, with notable contributions to incremental clustering systems and graph-based knowledge representation. Her work maintains strong methodological consistency in constraint programming while expanding into new application areas, particularly evident in her 2023-2025 publications on mineral prospectivity mapping and tweet-based event characterization. As an HDR-qualified researcher, Dr. DIEP-DAO actively supervises doctoral students and contributes to academic training through her roles in the Doctoral School. Her extensive collaboration network, particularly with Christel VRAIN, has produced over 60 publications since 2010, reflecting consistent research productivity. She is integral to the LIFO laboratory's data mining and constraint programming research group, where her work on declarative clustering approaches forms a core research pillar. Current projects focus on knowledge graph integration for explainable image classification systems and constraint-based social media analysis frameworks.

• Soil Science
• Hydrobiology
• Ecosystem Management
• +۳ مورد دیگر

Christine Ornetsmüller Ph.D. is a researcher affiliated with the University of Natural Resources and Life Sciences, Vienna (BOKU), working at the Institute of Soil Research and Institute of Hydrobiology and Aquatic Ecosystem Management . Her work focuses on vulnerability assessment and spatiotemporal analysis of mountain hazards. Research Focus: She specializes in applying geostatistical methods like spatial scan statistics to evaluate environmental risks, particularly related to torrent events and mountain hazards. Her research integrates environmental science with advanced statistical modeling. Publications: Her recent work centers on geospatial vulnerability analysis, focusing on spatiotemporal patterns in mountain hazard scenarios and statistical approaches to disaster risk reduction.

Matthieu Marbac-Lourdelleمشاهده پروفایل

دانشیار

• Biostatistics
• Model-based Clustering
• Computational Statistics
• +۲ مورد دیگر

Matthieu Marbac-Lourdelle is an Associate Professor in Statistics at ENSAI/CREST (Bruz, France) since September 2023. Previously, he served as an Assistant Professor at the same institution from September 2017 to September 2023. He is also an external collaborator of the PreMedical team, a joint team between Inria and Inserm, since September 2022. He completed his PhD in October 2014 at the University of Lille 1 under the supervision of Christophe Biernacki and Vincent Vandewalle. In 2022, he defended his habilitation, the French qualification required to supervise PhD students. Dr. Marbac-Lourdelle's research focuses on Biostatistics , Model-based Clustering , Computational Statistics , Empirical Likelihood , and Mixture Models . His work bridges theoretical statistical methods with practical applications in various domains including epidemiology, sports science, and genomics. His recent publications reveal a strong emphasis on developing advanced clustering techniques, particularly for complex data structures including functional data, mixed data types, and data with missing values. His research has significant applications in health monitoring, epidemiological studies, and sports analytics. Dr. Marbac-Lourdelle serves as an Associate Editor for Computational Statistics & Data Analysis (since 2021) and Econometric and Statistics (since 2023). He currently supervises five PhD students working on diverse topics including nonparametric mixture models, soccer game analysis, swimming technique monitoring, arrhythmia detection in racehorses, and probabilistic substitution models. His collaborations span multiple institutions including CREST, Inria, Inserm, and international partners at HEC Montreal and the University of McMaster.

• fuzzy clustering
• time series clustering
• clustering methods for complex data structures
• +۶ مورد دیگر

Pierpaolo D'Urso is a Full Professor of Statistics at Sapienza University of Rome, where he serves as Dean of the Faculty of Political Science, Sociology, Communication. He is Director of the Master's Program in Data Science for Public Administration and holds the Department of Social and Economic Sciences. His academic career includes serving as Director of the Department of Social and Economic Sciences, Vice Rector for Staff Training, and Member of the Academic Senate at Sapienza University. His primary research interests focus on advanced statistical methodologies, particularly fuzzy clustering , time series clustering , and clustering methods for complex data structures . He has extended these methods to diverse applications including statistics and democracy, electoral systems analysis, sports analytics, and public sector management. His work bridges theoretical statistical development with practical applications in social sciences and policy-making. His recent publications demonstrate a strong focus on spatial regularization techniques, entropy-based approaches, and novel applications of fuzzy clustering to interval-valued data and network structures. The research spans multiple disciplines including statistics, data science, economics, and political science, reflecting his interdisciplinary approach to statistical methodology. D'Urso has been recognized with inclusion in Stanford University's World's Top 2% Scientists ranking. He serves as Associate Editor and reviewer for numerous international journals in Statistics and Data Science, contributing significantly to the scholarly community through peer review and editorial work. At the institutional level, he has held significant administrative roles including Director of the Master in Data Science for Public Administration, demonstrating his commitment to developing statistical education for public sector applications. His work with government entities, particularly as a member of expert committees at the Presidency of the Council of Ministers, highlights the practical impact of his research on policy and governance.

• Soil and Water Conservation
• Environmental Engineering
• Climate Change Impact on Erosion
• +۳ مورد دیگر

Assistant Professor Katarina Lazarević is affiliated with the Faculty of Forestry, University of Belgrade , where she teaches and conducts research in soil and water conservation. Her academic engagement includes roles as a PhD teaching assistant and research intern on critical projects related to climate change adaptation, flood risk management, and ecosystem restoration. Department: Environmental Engineering in the Protection of Land and Water Resources Teaching: Fundamentals of Environmental Protection, Economics of Natural Resource Conservation Research Focus: Torrential flows, erosion modeling, sustainable land management, and socio-economic impacts of climate change on forest areas. She contributes to projects funded by the Ministry of Education, Science and Technological Development, and the Ministry of Agriculture and Environmental Protection. Recent Publications: Analyze flash flood hazard mapping, erosion control strategies, and socio-demographic influences on land degradation. Her work integrates geostatistical methods and multi-criteria analysis for environmental risk assessment. Email: katarina.lazarevic@sfb.bg.ac.rs Office: 6A, Faculty of Forestry Consultation Hours: Tuesdays & Wednesdays, 12:00–13:00

Ulrich Leopoldمشاهده پروفایل

مدرس

• Energy Policy
• Environmental Studies
• Geographic Information Systems (GIS)
• +۶ مورد دیگر

Ulrich Leopold is a Lecturer at Johns Hopkins University and a Senior Research Associate in Geocomputation at the Luxembourg Institute of Science and Technology (LIST) . He holds an MSc in Physical Geography and Geo Sciences from the University of Trier, Germany, and conducted PhD research at the Universities of Amsterdam and Wageningen, Netherlands, focusing on 'Spatial uncertainty analysis of integrated assessment models'. His research spans geospatial modeling, geostatistics, uncertainty analysis, and the development of decision support systems for environmental policy challenges. He has led work packages in European projects MUSIC and QUICS and pioneered the iGUESS framework for urban emission reduction, energy planning, flood management, and city logistics. Geospatial Modeling : Specializing in energy, noise, water, soil, and air policy problems Decision Support Systems : Web-based spatial technologies and frameworks Uncertainty Analysis : Spatial uncertainty propagation and downscaling

• Structural Engineering
• Architectural Acoustics
• Agricultural Economics & Policy
• +۵ مورد دیگر

Valero Pascual Gallego serves as an Assistant Professor in the Department of Building Structures and Physics at the Technical University of Madrid. He has been an active member of the Architectural Acoustics research group since January 2009, contributing to interdisciplinary work spanning structural engineering and agricultural systems. His research integrates structural engineering education with agricultural economics, focusing on hands-on methodologies for building structures instruction and microeconometric modeling for agricultural policy evaluation. Key areas include architectural acoustics for urban noise assessment, highway safety analysis using UAV technology, and sustainability frameworks for agrarian systems. His educational innovations feature open-source hardware/software tools and active learning techniques to enhance structural dynamics comprehension. Gallego's publication trends reveal dual expertise: recent work (2018-2022) emphasizes engineering education technologies and structural safety applications, while earlier research (2007-2014) centers on agricultural policy modeling, traffic noise analysis, and renewable energy impacts. This interdisciplinary approach bridges civil engineering with environmental economics through spatial data analysis and nonlinear mixed modeling. No scientific awards are documented in available sources. His advising activities remain unspecified, though his research group involvement suggests collaborative projects in architectural acoustics and agricultural information systems. Current work likely extends into practical applications of structural failure analysis and sustainable agrarian policy design. The Architectural Acoustics research group, where Gallego has contributed since 2009, specializes in urban noise mapping using nonlinear mixed models and area sampling techniques, directly informing city planning and environmental regulations through empirical acoustic classification of urban spaces.

Daniel Lawsonمشاهده پروفایل

پژوهشگر

• Data Science
• Genetics
• Bayesian Modelling
• +۵ مورد دیگر

Daniel Lawson is a researcher at the School of Mathematics, University of Bristol , specializing in data science and genetics. His work bridges interdisciplinary domains, including Bayesian epidemic modeling , population genetics , and machine learning . Key methodologies include CLARITY for cross-domain similarity analysis and badMIXTURE for validating admixture models. He teaches the Data Science Toolbox unit for the MSc Mathematics of Cybersecurity program. His research spans genomic architecture , cultural dynamics , and wind energy market models . Recent publications focus on dynamic network embeddings , ancestry inference , and simulation-based earthquake modeling . Lawson collaborates with Prof. Patrick Rubin-Delanchy and Prof. Robert Allison on clustering techniques. Contact: dan.lawson@bristol.ac.uk | Fry Building, University of Bristol.

Abhishek Mukherjeeمشاهده پروفایل

دانشیار

• Ecology
• Entomology
• Invasive Species Management
• +۵ مورد دیگر

Abhishek Mukherjee is an Associate Professor at the Agricultural and Ecological Research Unit of the Biological Sciences Division at Indian Statistical Institute's Giridih Branch in Jharkhand. With a PhD in Entomology from the University of Florida (2011) and postdoctoral experience at Texas A&M University, he has approximately 15 years of research experience focusing on ecology and management of invasive weed species in natural and agricultural systems. His educational background includes: Bachelor of Science (Agriculture) from Uttar Banga Krishi Viswavidyalaya (1997-2001) Master of Science (Agricultural Entomology) from Bidhan Chandra Krishi Viswavidyalaya (2001-2003) PhD in Entomology from the University of Florida (2007-2011) Postdoctoral research at Texas A&M University (2011-2014) Dr. Mukherjee's research spans ecological niche modeling of invasive weeds, plant-pest interactions, biorational management of pests and diseases, and applications of geostatistical techniques to identify spatial patterns of species distribution. He also explores applications of nano-biotechnology for sustainable agriculture, particularly in nematode management and plant disease control. His work integrates ecological modeling with practical agricultural solutions to address critical challenges in crop protection. Analysis of his recent publications (2020-2022) reveals a strong focus on invasive species management, nematode control in agricultural systems (particularly rice), and applications of nanotechnology in plant protection. His research demonstrates a consistent integration of ecological modeling approaches with field applications, with particular emphasis on sustainable and eco-friendly management strategies. The interdisciplinary nature of his work connects entomology, nematology, ecology, and agricultural science. His professional trajectory shows progression from Assistant Professor (2014-2020) to Associate Professor (2020-current) at the Indian Statistical Institute. He has also gained international experience as a Visiting Scientist at CSIRO Health and Biosecurity in Brisbane, Australia (2015), supported by an Endeavour Executive Fellowship from the Australian government. Dr. Mukherjee's work contributes significantly to understanding invasive species dynamics and developing sustainable management approaches for agricultural pests, with particular relevance to Indian agricultural contexts and ecosystems.

• Applied Mathematics
• Computational Statistics
• Environmental Modeling
• +۳ مورد دیگر

Georg Zimmermann serves as an Außerplanmäßiger Professor (Extraordinary Professor) at the Department of Applied Mathematics and Statistics, University of Hohenheim. His active academic role is evidenced by teaching responsibilities for Winter Semester 2025/26 including Mathematics and Computational Sciences of the Earth System, Mathematisches Kolloquium, and specialized courses for agricultural sciences. His research integrates advanced mathematical techniques with environmental applications, focusing on uncertainty quantification in large-scale systems. Key specialties include Gaussian quadrature methods for stochastic simulation, soil radiation modeling with moisture correction algorithms, and computational approaches for environmental data exploitation. This interdisciplinary work bridges applied mathematics, earth system science, and agricultural technology. Recent publications (2021-2025) reveal consistent methodological innovation in numerical analysis for environmental modeling, particularly through rotational Gaussian quadrature techniques that enhance computational efficiency in uncertainty analysis. His work appears in high-impact journals spanning soil science, environmental informatics, and computational economics. No scientific awards or major grants are documented in available records. Current information does not indicate formal student supervision or advisory roles.

• Geochemistry
• Mineralogy
• Hydrothermal Systems
• +۴ مورد دیگر

Tatsuo Nozaki is a Professor at Waseda University's School of Creative Science and Engineering, with affiliations spanning Earth resource engineering, energy sciences, and deep-seafloor mineral exploration. His research integrates geochemistry, isotope analysis, and hydrothermal system dynamics through extensive fieldwork and laboratory investigations. Current affiliations: Waseda University (since 2009), University of Tokyo (visiting researcher), Chiba Institute of Technology Key methodologies: Re-Os geochronology, MC-ICP-MS analysis, subseafloor drilling, 3D geostatistical modeling Research interests focus on: Subseafloor sulfide mineralization mechanisms Deep-sea rare earth resource characterization Hydrothermal fluid-rock-microbe interactions Volcanogenic massive sulfide (VMS) deposit formation Os isotope stratigraphy for paleoenvironmental reconstruction Publication trends reveal interdisciplinary work connecting: Hydrothermal ore genesis with microbial sulfate reduction Deep-sea mineral resource quantification techniques Magmatic-seawater interaction in arc volcanism Environmental impacts of deep-sea mining operations High-precision isotope analytical methods Geostatistical modeling of metal distribution Scientific awards include: 2025 Nishida Memorial Prize (Japan Geoscience Union) 2023 Minister of Education, Culture, Sports, Science and Technology Award 2018 Nitto Prize (Geological Society of Japan) Multiple student presentation awards as advisor Professional leadership encompasses editorial roles in Scientific Reports and Resource Geology , committee memberships in Japan Geoscience Union and resource societies, and advisory positions for Japanese government energy agencies.

Harald Kunstmannمشاهده پروفایل

استاد

• Hydrological Modeling
• Meteorological Modeling
• Water and Energy Fluxes
• +۲ مورد دیگر

Professor Harald Kunstmann is affiliated with the University of Augsburg , where he works at the Institute of Geography . He is a Principal Investigator in the Hydrological Modeling (HM) research module under the Cosmic Sense - DFG-Forschungsgruppe FOR 2694 consortium. Expertise in high-resolution hydrological and meteorological modeling Model development for studying coupled water and energy fluxes between land surface and atmospheric boundary layer Geostatistical integration of hydrometeorological data Leadership in establishing hydrological observatories: TERENO , ACROSS , and WASCAL His work bridges theoretical modeling with practical implementation of observational networks.