جست‌وجوی استاد و پژوهشگر

Zili Liمشاهده پروفایل

مدرس ارشد

• Innovative Monitoring Technologies
• Computational Geotechnics
• Tunnelling Engineering
• +۳ مورد دیگر

Dr. Zili Li is a Senior Lecturer (Associate Professor) in Geotechnical Engineering at University College Cork (UCC), Ireland. He holds a PhD from the University of Cambridge and has postdoctoral experience at the Colorado School of Mines and a visiting professorship at MIT. His research focuses on innovative monitoring technologies, computational geotechnics, and energy geotechnics. He leads projects funded by CERN and the SFI Frontiers Programme, totaling over €2 million as Principal Investigator. Education Bachelor in Civil Engineering, Tongji University PhD in Engineering, University of Cambridge Research Interests Dr. Li’s research integrates advanced technologies like distributed fiber optic sensing, machine learning, and wireless sensor networks with geotechnical engineering challenges. His work spans tunneling engineering, geothermal foundations, and energy geotechnics, addressing critical infrastructure needs such as underground excavation monitoring and large-scale energy geostructures. Grants and Projects Principal Investigator of SFI Frontiers for the Future Programme (€612.8k) Leading CERN-funded project on tunnel monitoring (€405k) Task Force Leader for Big Data Acquisition in ISSMGE’s TC309 Awards John Murphy Postgraduate Research Fellowship (2022) Advising and Mentoring Supervising 8 PhD students and mentoring a postdoc, Dr. Li actively contributes to training the next generation of geotechnical engineers. Labs and Teams Leads the Zili Li Group, focusing on machine learning and big data applications in geoscience. Organized the 4th International Symposium on Machine Learning and Big Data in Geoscience (ISMLG 2023).

Siddharth Misraمشاهده پروفایل

دانشیار

• Data-driven modeling
• Machine Learning
• Petrophysics
• +۴ مورد دیگر

Siddharth Misra is an Associate Professor in the Harold Vance Department of Petroleum Engineering at Texas A&M University, part of the College of Engineering. He holds the Ted H. Smith, Jr. ’75 and Max R. Vordenbaum ‘73 DVG Endowed Professorship. His research focuses on data-driven modeling, machine learning applications in subsurface systems, petrophysics, and carbon storage. Education: Ph.D., Petroleum Engineering, University of Texas at Austin M.S., Petroleum Engineering, University of Texas at Austin B.Tech., Electrical Engineering, Indian Institute of Technology, Bombay Research Interests: Dr. Misra’s work integrates machine learning with subsurface characterization, including shale reservoir modeling, geothermal energy monitoring, and carbon sequestration. He emphasizes data analytics for improving subsurface exploration and reservoir management. Publications: His recent publications highlight advancements in neural network modeling for pore structure analysis, machine learning for SEM image interpretation, and geophysical log inversion techniques. These contributions reflect a focus on bridging computational methods with traditional petroleum engineering challenges. Awards: Arie van Weelden Award (2021) J. Clarence Karcher Award (2020) Forty under 40 (Oil and Gas Investor, 2023) Advising/Grants: While specific student/advisor details are not listed, his research is supported by grants from the U.S. Department of Energy and the American Chemical Society. He collaborates on projects involving carbon storage and geothermal reservoir monitoring.

Tianhaozhe Sunمشاهده پروفایل

استادیار مدعو

• Geophysics
• Tectonics
• Geodynamics
• +۱۱ مورد دیگر

Tianhaozhe Sun is a geophysicist serving as an Adjunct Assistant Professor in the School of Earth and Ocean Sciences at the University of Victoria and as a Research Scientist at the Geological Survey of Canada, Natural Resources Canada. His work bridges academic research and national geoscience applications, focusing on plate boundary processes. PhD, University of Victoria, 2017 BSc, Tongji University, 2011 Dr. Sun's research centers on tectonic and geodynamic processes at plate boundaries, especially subduction zones. He investigates earthquakes, slow slip events, and related geohazards such as tsunamis by integrating cutting-edge observational techniques—including seafloor geodesy and borehole observatories—with advanced numerical modelling. His work aims to unravel how geological and physical processes interact to control fault mechanics, forearc deformation, fluid flow, and large-scale crustal changes throughout the earthquake cycle. Although no recent publications are listed in the provided text, his methodological focus suggests strong contributions in geophysical data integration and computational geodynamics, likely spanning marine geophysics, seismology, and hazard modeling. There are no scientific awards mentioned in the available information. Dr. Sun holds an adjunct academic role at the University of Victoria while maintaining a primary research position with the Geological Survey of Canada. He may be involved in mentoring and collaborative research, though no students or grants are explicitly listed. His position as an adjunct suggests a part-time academic affiliation complementing his government research role. He is affiliated with the Geological Survey of Canada and contributes to national-level geoscientific research, particularly in subduction zone monitoring and hazard assessment. His work likely involves collaboration with observatory networks and multidisciplinary teams focused on crustal dynamics and geohazard mitigation.

• Quaternary Geology
• Glacial Landforms
• Loose Materials Characterization
• +۷ مورد دیگر

Professor Hans Ola Fredin holds a faculty position at the Department of Geosciences, NTNU within the Faculty of Engineering. His research focuses on Quaternary geology, glacial landforms, and geohazards related to loose materials like quick clays. He employs advanced techniques such as GIS, remote sensing, and machine learning to study spatial relationships and geological processes. Current research projects include Antarctic ice volume changes, deglaciation patterns of Norway/Scandinavia, and AI-driven geoscience applications. His work bridges field observations with computational methods, contributing to understanding both past glacial dynamics and modern geohazard mitigation. Publications from 2020–2024 highlight interdisciplinary approaches to glacial geomorphology, ice sheet behavior, and environmental risk assessment. Notable contributions include studies on strandflat formation mechanisms, radon risks from rock-avalanche deposits, and mid-Pliocene Antarctic ice thickness reconstructions.

• Climate Change Mitigation
• Maritime Engineering
• Environmental Science
• +۳ مورد دیگر

Diogo Kramel is a Research Fellow in the Industrial Ecology Program at the Department of Energy and Process Engineering, Norwegian University of Science and Technology (NTNU). He holds degrees in Naval Architecture and Maritime Engineering (BSc/MSc, University of São Paulo) and Maritime Spatial Planning (MSc, University of Sevilla/University of the Azores/University of Venice). His PhD research (2024) focused on climate change mitigation in the maritime sector through the CLIMMS project. Currently, he leads the Nord_H2ub project, applying the MariTEAM model combined with Life-Cycle Assessment to reduce GHG emissions in shipping. His work integrates modeling techniques with policy analysis to inform sustainable maritime strategies. Key research interests include shipping emissions, energy systems modeling, and climate policy. He has published extensively on topics such as shipping scenarios, emissions reduction strategies, and integrated assessment frameworks. His contributions include developing the MariTEAM model for global fleet analysis and linking it with tools like MESSAGEix. Recent presentations include talks at the European Geosciences Union and the Gordon Research Conference on Climate Intervention.

• Geological Modeling
• 3D Geophysical Modeling
• Structural Geology
• +۳ مورد دیگر

Lachlan Grose is a Research Fellow at Monash University's School of Earth Atmosphere and Environment, specializing in advanced geological and geophysical modeling. His work focuses on integrating machine learning, 3D structural analysis, and geophysical inversion techniques to address challenges in subsurface resource management and tectonic understanding. Key projects include the Three-dimensional Bayesian Modelling of Geological and Geophysical data (ARC-funded) and development of the LoopStructural software, a time-aware 3D geological modeling platform. Grose also contributes to industry collaborations like the AMIRA P1249 project on ore body knowledge modeling. Research interests span structural geology, igneous intrusion modeling, FAIR data principles, and geophysical inversion methods. He has led efforts to improve usability of Loop3D and pioneered machine learning applications for geological structure imaging. Leading developer of LoopStructural (open-source 3D modeling framework) Primary investigator on usability improvements for geoscientific workflows Recipient of ARC and industry grants totaling over AUD 3M Supervises PhD candidates focusing on interdisciplinary geoscience problems Recent publications emphasize transdimensional inversion methods, FAIR data integration, and application of machine learning to geophysical datasets. His work bridges academic research with industrial subsurface resource challenges.

• Subsurface flow and transport in porous media
• Computational methods for energy and environmental subsurface systems
• Modelling and analysis of geological storage processes
• +۵ مورد دیگر

Dr. Arman Darvish Sarvestani is a Research Fellow in the Department of Earth Science and Engineering, Faculty of Engineering, at Imperial College London. His research is part of the PETRONAS-funded DSALT project, which aims to accelerate large-scale screening of CO₂ storage sites in saline aquifers and depleted hydrocarbon fields. His educational background includes: PhD in Petroleum Engineering With expertise in reservoir simulation and flow modelling, Dr. Darvish Sarvestani develops analytical and computational methods for subsurface storage assessment. His research focuses on carbon capture and storage (CCS), dynamic site screening, and subsurface heterogeneity effects on pressure and plume behaviour. He pioneers the integration of physical modelling with data-driven approaches to optimize energy transition decision-making. Key research domains include: Subsurface flow and transport in porous media Computational methods for energy and environmental subsurface systems Geological storage process analysis Multi-scale resource simulation and screening Physics-based and AI-enhanced reservoir modelling Underground system uncertainty and risk assessment Geoscience-engineering-AI integration for net-zero solutions Sustainable subsurface utilization for energy applications Dr. Darvish Sarvestani's primary engagement is the PETRONAS-funded DSALT project. No student supervision or additional grants are documented in available sources. He contributes to Imperial College London's DSALT research team, developing physics-based tools for evaluating carbon storage site performance and advancing underground energy applications.

• Marine Geology
• Geophysics
• Seafloor Mapping
• +۵ مورد دیگر

Adam Skarke is an Associate Professor of Geology in the Department of Geosciences at Mississippi State University, a position he has held since 2020 after serving as Assistant Professor from 2014-2020. His research integrates marine geology and geophysics to investigate sediment transport, seafloor morphology, and fluid dynamics across continental margins from coastal zones to deep-sea environments. Education: Ph.D. in Geological Sciences, University of Delaware (2013) M.S. in Geological Sciences, University of Delaware (2008) B.A. in Geology, Colgate University (2003) Research Focus: Dr. Skarke's work centers on seafloor gas seeps , coastal morphodynamics , and submarine groundwater discharge , employing field-based quantitative analysis of geological, geophysical, and oceanographic datasets. His innovative use of environmental observing sensors and platforms enables investigation of physical relationships across diverse spatial and temporal scales, with particular emphasis on methane dynamics and sedimentary processes. Publication Trends: Recent publications (2021-2025) demonstrate a significant methodological shift toward machine learning applications for seafloor feature detection, particularly in gas seep identification. His work bridges marine geology with computational science, while maintaining strong field components through NOAA expeditions. Key thematic clusters include methane seep inventory development, coastal wetland restoration efficacy, and interdisciplinary studies of continental margin processes. Scientific Recognition: Faculty Research Award from Mississippi State University College of Arts and Sciences Early Career Research Fellowship from National Academies Gulf Research Program Mentorship & Funding: Dr. Skarke advises graduate students Jeneil Patel, Ramon Kalski, and Jonathan Leard, with research supported by federal grants including his National Academies fellowship. His NOAA collaborations fund extensive field campaigns using advanced platforms like Wave Gliders and AUVs for seafloor mapping and environmental monitoring. Research Infrastructure: He actively participates in NOAA Okeanos Explorer missions, contributing to deep-sea exploration across Atlantic and Gulf of Mexico margins. His work integrates data from multibeam echosounders, ROVs, and autonomous systems within collaborative frameworks involving geological, biological, and computational specialists.

Aiman Solimanمشاهده پروفایل

عضو هیئت علمی

• Urban Planning
• Environmental Science
• Spatial Analysis
• +۴ مورد دیگر

Aiman Soliman is a Research Assistant Professor in Urban and Regional Planning and a Research Scientist at the National Center for Supercomputing Applications (NCSA) at the University of Illinois at Urbana-Champaign. His work bridges spatial data science with urban systems analysis, focusing on applications of machine learning to understand urban environments and public health outcomes. Education: Ph.D. in Environmental Sciences and Remote Sensing, University of Guelph, 2010 MS in Geographic Information Science, University of Twente, 2004 BS in Land Resources, Ain Shams University, 1999 Research Interests: Aiman specializes in applying computational methods to study urban systems, including spatial analysis of disease transmission dynamics, urban climate impacts, and social sensing via social media data. His work integrates geospatial data with machine learning to model feedback between human activities and environmental systems. Research Highlights: Analyzing tourism patterns and mosquito-borne disease spread in the Americas Developing cyber-infrastructure tools for Arctic land surface monitoring Exploring urban heterogeneity's impact on lung cancer disparities Data Solutions: Partners with NCSA on industrial projects in energy, finance, and agriculture, deploying production-ready data systems.

Anders Nymark Christensenمشاهده پروفایل

دانشیار

• Image Analysis
• Computer Vision
• Medical Imaging
• +۷ مورد دیگر

Anders Nymark Christensen is an Associate Professor in the Department of Applied Mathematics and Computer Science at the Technical University of Denmark (DTU), specializing in Visual Computing. His work bridges computer vision, medical imaging, and materials science, with a strong focus on explainable AI in clinical applications and structural analysis of complex materials. Institution: Technical University of Denmark (DTU) School: Department of Applied Mathematics and Computer Science Department: Visual Computing Role: Associate Professor Christensen’s research interests include image analysis, computer vision, explainable AI, ultrasound imaging, fetal medicine, and fiber orientation in composites. He applies advanced computational techniques to solve real-world problems in healthcare and materials engineering, particularly through structure tensor analysis and deep learning. His recent publications highlight a strong trend in developing AI tools for clinical decision support in fetal medicine, structural analysis of food and composite materials, and ultrasound imaging. These works span journals such as Scientific Reports , Food Structure , and IEEE Access , reflecting interdisciplinary innovation. Clinical validation of explainable AI for fetal growth scans Characterization of anisotropy in mozzarella cheese Determining fetal orientations from ultrasound video Structure tensor analysis in composites He supervises several PhD students in projects related to AI in skin lesion analysis, cancer detection, and ultrasound imaging. His collaborative network includes key researchers at DTU such as Anders Bjorholm Dahl, Vedrana Andersen Dahl, and Mads Nielsen. He has been involved in significant research grants and is active in both medical and engineering domains, contributing to open datasets and reproducible research. Christensen leads and contributes to numerous active projects, including: Decision Support AI for Skin Lesions (2024–2027) Fighting Cancer with Generative AI (2024–2027) SONAI: Explainable AI in the Clinic (2022–2026) Deep learning for identifying biomarkers in medical images (2022–2025) His work supports UN Sustainable Development Goals related to health, innovation, and responsible consumption, particularly through advancements in medical diagnostics and sustainable materials.

Tao Chenمشاهده پروفایل

استاد

• Image Processing
• Data Mining and Deep Learning
• Geo-hazards
• +۲ مورد دیگر

Prof. Tao Chen is a faculty member at the School of Geophysics and Geomatics , China University of Geosciences , specializing in advanced remote sensing and data analysis techniques. His research bridges Image Processing , Machine Learning , and Geo-environmental Monitoring . Focus on Geo-hazards (e.g., flood mapping, landslide susceptibility) Develops hybrid methods for texture enhancement and spatiotemporal change detection Active in IEEE GRSS professional networks Recent publications highlight multi-source data fusion (e.g., SAR + social media) and model interpretability in geospatial risk assessment. Collaborates with experts like Jun Li and Antonio Plaza .

Stefan Petersمشاهده پروفایل

مدرس ارشد

• Remote Sensing
• Geographic Information Systems (GIS)
• Environmental Science
• +۵ مورد دیگر

Dr. Stefan Peters is a Senior Lecturer in Surveying and GIS at the University of South Australia (UniSA) within the UniSA STEM school. His research focuses on applied remote sensing and GIS to address environmental and geospatial challenges, including fire detection, habitat modeling, and 3D reconstructions. Lecturer in Surveying and GIS, UniSA STEM Research Degree Supervisor Stefan's research spans geospatial data fusion, environmental monitoring, and participatory mapping. He has contributed to frameworks for 3D point cloud fusion in forestry, AI-driven fire smoke detection, and urban catchment analysis using LiDAR and multispectral data. His recent publications highlight advancements in hyperspectral satellite AI emulation, channel morphology monitoring, and cross-sensor fire detection algorithms. Key themes include remote sensing innovation, environmental data integration, and urban-ecosystem interactions. Scientific contributions include: Best Paper Award (2012) Stefan coordinates courses in Web Cartography and Environmental Remote Sensing, emphasizing practical geospatial applications. He collaborates with institutions like Geoscience Australia and the FWPA on projects spanning forestry, fire management, and heritage preservation.

Alan Whittingtonمشاهده پروفایل

استاد

• Petrology
• Volcanology
• Planetary Geology
• +۱۲ مورد دیگر

Alan Whittington is a Professor in the Department of Earth and Planetary Sciences at The University of Texas at San Antonio (UTSA), where he leads the Heat and Mass Transfer and Experimental Rheology (HAMsTER) Lab. His research integrates petrology, volcanology, and planetary science to study volcanic processes on Earth and other planetary bodies, with a strong emphasis on experimental techniques and materials science. His research interests focus on: Experimental determination of lava rheology and thermal properties Volcanic processes and hazards on Earth and other planets Lunar in situ resource utilization for construction materials Cryovolcanism on icy moons like Europa Heat transfer and crystallization in magmatic systems Thermal properties of planetary materials His recent publications reveal a strong trend toward interdisciplinary research combining experimental petrology with planetary applications, particularly in lunar construction materials and volcanic flow dynamics. Studies on regolith sintering, spontaneous reheating of lava, and geospeedometry demonstrate his lab's focus on thermodynamic and kinetic processes in geological materials. The work spans from fundamental laboratory experiments to applied research supporting future space exploration. Scientific honors include: AAAS Fellow (2024) Fellow of the Geological Society of America (2017) NSF CAREER Award (2008) Dr. Whittington actively mentors students at all levels, including undergraduates, MS, PhD, and postdoctoral researchers, fostering a collaborative research environment. He has secured significant research funding from NASA, NSF, and industry partners for projects related to lunar construction, stardust analogs, and lava emplacement. His lab collaborates extensively with the UTSA College of Engineering, Physics and Astronomy, and external partners on interdisciplinary projects advancing space science and volcanic hazard understanding. The HAMsTER Lab serves as a hub for experimental geoscience research, equipped with advanced instrumentation including differential scanning calorimeters, high-temperature rheometers, and thermal conductivity measurement systems. The lab supports both fundamental research on magmatic processes and applied research for space exploration technologies, particularly focused on sustainable lunar infrastructure development.

Emanuela Di Martinoمشاهده پروفایل

پژوهشگر

• Paleontology
• Paleoecology
• Marine Biology
• +۷ مورد دیگر

Emanuela Di Martino is a Researcher at the University of Catania , with significant affiliations at the Natural History Museum, University of Oslo , and the Natural History Museum London . Her work bridges paleontology, marine biology, and evolutionary ecology, focusing on bryozoans as a model for understanding macroevolutionary processes and tropical biodiversity dynamics. Education: PhD in Geosciences, Utrecht University (2014) Master’s in Geological Sciences Applied to Land Management, University of Catania (2008) Bachelor’s in Geology Applied to Land Conservation, University of Catania (2006) Her research interests include: Paleobiodiversity hotspots in tropical regions Allometric and life-history evolution under climate change Paleoenvironmental reconstructions using multitaxon approaches Taxonomy and phylogeny of Mesozoic-to-Recent marine bryozoans Her publication trends emphasize: Long-term evolutionary patterns in bryozoans Macroevolutionary dynamics and diversification Ecological impacts of marine debris Morphometric analysis via AI tools (e.g., DeepBryo) Phylogenetic studies with genome-skimming Competitive outcomes in fossil communities Scientific Awards: 2025 Visiting Professorship at CR2P, Paris 2021 Medaglia Giovanni Merla, Società Paleontologica Italiana 2018 European Commission Seal of Excellence for project ESTIMATE She has led projects like SELECT (Norwegian RCN) and macroevolution.abc (ERC), and holds editorial roles at Journal of Paleontology and Zootaxa . Her work involves collaborations with institutions in Norway, the UK, Spain, and the US, and she contributes to understanding ancient ecosystems through colonial invertebrates.

H. Hajibeygiمشاهده پروفایل

دانشیار

• Reservoir Engineering
• Porous Media
• Multiphase Flow
• +۳ مورد دیگر

H. Hajibeygi is an Associate Professor in the Department of Reservoir Engineering at Delft University of Technology's School of Civil Engineering & Geosciences. His work focuses on multiscale modeling, subsurface energy storage, and computational physics applied to geological reservoirs. Education: PhD from Stanford University (2013), MSc from ETH Zürich (2011) Research interests span porous media dynamics , fractured geological formations , and geo-energy applications . He develops advanced numerical methods like finite volume and multiscale extended finite element approaches for subsurface fluid flow and mechanical coupling. Recent projects include CO₂ sequestration and hydrogen storage in saline aquifers. His 2025 publications emphasize compositional modeling , dynamic multilevel methods , and hysteresis in multiphase flow , reflecting a focus on improving computational efficiency for complex subsurface systems. Scientific Awards ETH Medal (2012) Innovative Teaching Talent (2018) InterPore Award (2021) Vidi Grant (2019) Hajibeygi leads research on subsurface energy storage and has contributed datasets on hydrogen/brine flow, hysteresis, and molecular simulations. He actively engages in public outreach, including media discussions on underground green gas storage and geothermal energy.