جست‌وجوی استاد و پژوهشگر

Maria Christina Marianiمشاهده پروفایل

استاد

• Applied Mathematics
• Nonlinear partial differential equations
• Stochastic differential equations
• +۵ مورد دیگر

Maria Christina Mariani is a Professor and Department Chair in the Department of Mathematical Sciences at the University of Texas at El Paso (UTEP). Her interdisciplinary research bridges mathematics with applications in public health, geophysics, physics, and finance, with a focus on developing novel mathematical models for complex data analysis. Dr. Mariani earned her Ph.D. in Mathematics from the University of Buenos Aires in 1992, where she received an Outstanding dissertation award. She also holds an M.S. in Physics (1996) and an M.S. in Mathematics (1987), both from the University of Buenos Aires with highest honors. Her research interests span Applied Mathematics, Nonlinear partial differential equations, Stochastic differential equations, Machine Learning techniques, Mathematical Finance, Mathematical Physics, and Numerical Methods. She has developed mathematical models for medical data analysis (particularly breast cancer, heart disease, and prostate cancer), seismic and explosive data, and financial markets. Her work emphasizes the development of mathematical models to enhance understanding of medical data and extreme events in various phenomena. Dr. Mariani's recent research focuses on applying machine learning and stochastic models to complex data sets across multiple domains. Her work demonstrates consistent innovation in developing novel algorithms for medical diagnosis and prognosis, analyzing seismic data, and modeling financial markets using Levy processes, Ornstein-Uhlenbeck models, and wavelet techniques. She has mentored numerous students throughout her career, including PhD candidates, MS students, and post-doctoral researchers, demonstrating her commitment to academic development and knowledge transfer. Dr. Mariani has served as Department Chair and holds the Shigeko K. Chan Distinguished Professor title in Mathematical Sciences, reflecting her significant contributions to the field and institution.

Daniel Harrisمشاهده پروفایل

مدرس ارشد

• Climate Change Impacts
• Coastal Morphodynamics
• Coral Reef Geomorphology
• +۳ مورد دیگر

Dr Daniel Harris is a Senior Lecturer in the Department of Geography at the School of the Environment, University of Queensland (UQ). His research focuses on coastal and coral reef morphodynamics, integrating physical processes like waves and tides with ecological and geological systems. Prior to UQ, he held positions at the University of Sydney and the Leibniz Center for Tropical Marine Ecology (ZMT). He leads The BeachLab, dedicated to developing tools for coastal resilience in a warming world. Research interests include coral reef structural complexity, coastal protection under climate change, and surf zone processes. His work combines field data, remote sensing (e.g., LiDAR, drones), and numerical modeling to address both fundamental and applied questions. Notable projects involve quantifying coral rubble mobility, analyzing Holocene reef evolution, and assessing shoreline change via satellite imagery. His expertise spans marine geoscience, physical oceanography, and environmental adaptation strategies. Publications emphasize coral reef dynamics, coastal geomorphology, and climate impacts. He collaborates with ecologists, geologists, and coastal engineers to advance interdisciplinary solutions. Teaching focuses on geography and marine science, reflecting his commitment to educating future researchers and practitioners. Key contributions include advancing methods for shoreline monitoring using Bayesian networks and Google Earth Engine. His research highlights the critical role of coral reefs in coastal protection, particularly under rising sea levels and extreme weather events. The BeachLab’s work bridges academic inquiry with practical management strategies for vulnerable coastal ecosystems.

Christopher Gilliamمشاهده پروفایل

استادیار

• Signal Processing
• Radar Systems
• Sampling Theory
• +۵ مورد دیگر

Dr. Christopher Gilliam is an Assistant Professor in Applied Signal Processing at the University of Birmingham's Department of Electronic, Electrical and Systems Engineering. He holds an MEng (1st Class Hons) in Electrical & Electronic Engineering (2008) and a Ph.D. in Signal Processing (2013), both from Imperial College London. Prior to joining Birmingham in 2022, he was a Postdoctoral Fellow at The Chinese University of Hong Kong (2013–2017) and a Research Fellow at RMIT University, Australia (2017–2022). Research Interests: Sensor signal processing, radar imaging, sampling theory, motion estimation, quantum navigation, and medical imaging. Labs: Microwave Integrated Systems Laboratory (MISL). Committees: Member of IEEE Signal Processing Society and APSIPA Technical Committees. His work focuses on advancing signal processing techniques for radar systems, navigation, and medical imaging. Recent research highlights include drone-based SAR imaging, motion correction in MRI, and fusion of classical/quantum sensors for inertial navigation. He is actively supervising PhD students and contributes to projects sponsored by DSTG. Publications span radar SLAM, probabilistic navigation algorithms, and deep learning-driven medical imaging solutions. His research bridges theoretical signal processing with practical applications in autonomous systems and healthcare.

Arno Siebesمشاهده پروفایل

استاد

• Data Mining
• Pattern Mining
• Minimum Description Length Principle
• +۲ مورد دیگر

Arno Siebes is Professor of Algorithmic Data Analysis in the Department of Information and Computing Sciences at Utrecht University's Faculty of Science. His research focuses on data mining methodologies, particularly pattern mining and Minimum Description Length (MDL) principles. Key research areas include: Developing efficient algorithms for pattern discovery Applying MDL to data characterization Creating interpretable models for complex datasets Addressing challenges in data science education Recent publications demonstrate applications in diverse domains including mobility analysis, genomic screening, and pandemic response. His work combines theoretical foundations with practical implementations for knowledge discovery.

Wenyuan Fanمشاهده پروفایل

دانشیار

• Array seismology
• Marine geophysics
• Environmental seismology
• +۴ مورد دیگر

Dr. Wenyuan Fan is an Associate Professor at the Institute of Geophysics and Planetary Physics (IGPP) within the Scripps Institution of Oceanography at UC San Diego. His research focuses on array seismology, marine geophysics, environmental seismology, and earthquake dynamics. He holds a PhD from UC San Diego and degrees from Peking University. Research Interests: Array seismology and waveform modeling Marine geophysics and ocean-solid earth interactions Earthquake source kinematics and dynamic triggering mechanisms Microseismicity imaging and fault zone processes Recent Work Trends: His recent publications emphasize understanding earthquake rupture mechanics through dense array data, exploring submarine landslide dynamics via hydroacoustic signals, and applying machine learning to seismic catalog development. Studies often bridge tectonic processes with environmental factors, such as storm-induced seismicity and human-induced seismic events. Advising & Grants: No students listed; active in NSF-funded projects on fault dynamics and marine geohazards. Labs/Teams: Affiliated with IGPP's Seismology and Geodynamics Group, collaborating with international networks like IRIS and CTBTO.

• Business Analytics
• Management Sciences

Katerina Tsakiri serves as Associate Professor and Department Chair in the Department of Information Systems, Analytics and Supply Chain Management at Rider University, with her office located in Sweigart Hall. Her academic leadership spans business-focused quantitative disciplines within the university's professional programs. Her educational foundation includes: Ph.D. in Mathematics and Statistics from University at Albany, SUNY (2010) M.A. in Mathematics and Statistics from University at Albany, SUNY (2006) B.S. and M.S. in Applied Mathematics and Physical Sciences from National Technical University of Athens, Greece (2004) Dr. Tsakiri's research bridges Business Analytics and Management Sciences with environmental applications, specializing in statistical time-series methodologies for real-world hydrological and geological challenges. Her work demonstrates how business analytics frameworks can solve complex environmental problems through rigorous quantitative modeling. Analysis of her 2014-2020 publications reveals consistent innovation in environmental time-series analysis, particularly in flood forecasting systems for New York watersheds and volcanic monitoring in Greece. She integrates artificial neural networks, Markov chains, and GIS technologies to develop practical prediction models that serve both academic research and emergency management applications. Her professional recognition includes: Davis Fellowship from Rider University (2017-2018) As Department Chair, Dr. Tsakiri directs academic operations while maintaining an active research program supported by institutional fellowships. Her interdisciplinary collaborations with geoscientists demonstrate the expanding role of business analytics in environmental risk management, though specific student advising details remain unreported in available materials.

Nathaniel Chaneyمشاهده پروفایل

استادیار

• Hydrology
• Earth System Science
• Soil Science
• +۱۲ مورد دیگر

Nathaniel Chaney is an Assistant Professor in the Department of Civil and Environmental Engineering at Duke University’s Pratt School of Engineering. He leads the Chaney Lab, a research group focused on computational hydrology and Earth system modeling. His work centers on understanding and representing land surface heterogeneity in hydrological and climate models using big data, machine learning, and high-performance computing. Ph.D. in Hydrology, Princeton University, 2015 B.A. in Atmospheric Sciences and Applied Mathematics, U.C. Berkeley Postdoctoral Research Associate, Princeton University and NOAA Geophysical Fluid Dynamics Laboratory His research interests include hydrology, Earth system science, soil science, ecology, geomorphology, numerical modeling, high performance computing, machine learning, and environmental data assimilation. He develops and applies models like HydroBlocks and POLARIS to improve the representation of land heterogeneity in Earth system models. His work bridges field-scale and macro-scale hydrology, addressing challenges in land-atmosphere interactions, drought monitoring, and climate prediction. The most recent publications highlight advancements in modeling land heterogeneity, improving soil moisture estimates, characterizing land surface temperature patterns, and enhancing Earth system models through better representation of catchment-scale processes. Key themes include spatial heterogeneity, land-atmosphere coupling, and the integration of remote sensing data with high-resolution modeling. He is actively mentoring several Ph.D. students, including Laura Torres Rojas, Tyler Waterman, Emma Xu, Jiaxuan Cai, Luiz Bacelar, Daniel Guyumus, and undergraduate Sarah Bailey. His lab fosters interdisciplinary research in hydrology, climate science, and data science. Nathaniel Chaney teaches courses such as CEE 584: Physical Hydrology, CEE 506: Environmental Spatial Data Analysis, and various independent study and advanced topics courses in civil and environmental engineering. He is currently recruiting motivated Ph.D. and postdoctoral researchers interested in his research themes.

Michael E. Oskinمشاهده پروفایل

استاد

• Geology
• Structural Geology
• Geomorphology
• +۴ مورد دیگر

Michael E. Oskin is a Professor and former Department Chair (2017-2021) in the Department of Earth and Planetary Sciences at the University of California, Davis. He also serves as faculty director of the Lassen Field Station, part of the UC Natural Reserve System. His research focuses on structural geology, geomorphology, and active tectonics, particularly the interplay between earthquakes, surface processes, and landscape evolution. He specializes in using high-resolution topography and geochronological techniques to study deformation rates, fault mechanics, and tectonic processes in regions like California and the Tibetan Plateau. Education: B.S. in Geology/Engineering Geology, UC Los Angeles (1995) Ph.D. in Geology, California Institute of Technology (2002) Research Interests: His work addresses deformation rates linked to earthquakes, continental deformation mechanisms, and topographic responses to geologic structures. Techniques include field observations, cosmogenic dating, and lidar analysis to quantify processes like fault slip, erosion, and landscape evolution. Publications: Recent work includes studies on fault rupture dynamics (e.g., San Andreas and Ridgecrest earthquakes), geochronological modeling, and tectonic evolution in regions like the Tibetan Plateau. His research bridges structural geology with quantitative methods to advance understanding of active crustal processes. Awards: Recipient of the UC Davis Graduate Program Advising and Mentoring Award (2020). Advising & Grants: Mentor to over 20 graduate students, emphasizing collaborative research, fieldwork, and open science practices. Prioritizes student summer support and funding for field/analytical costs. Leads a lab focused on earthquake geology and hosts weekly reading groups. Labs/Teams: Oversees the Lassen Field Station, teaching the summer field course GEL 110A and conducting research in the region. Active in the UC Natural Reserve System and collaborates with international research groups.

Alberto Dainottiمشاهده پروفایل

دانشیار

• Internet Measurement
• Cybersecurity
• Data Science
• +۶ مورد دیگر

Alberto Dainotti is an Associate Professor at the School of Computer Science, College of Computing, Georgia Institute of Technology (Georgia Tech), and Director of the Internet Intelligence Lab. His research focuses on Internet measurement, data science, and cybersecurity, with a particular emphasis on infrastructure reliability and socio-political implications of cyber events. Before joining Georgia Tech in 2014, he served as an Associate Research Scientist and Principal Investigator at CAIDA (Center for Applied Internet Data Analysis) at UC San Diego. He holds a Ph.D. in Computer Engineering and Systems from the University of Napoli 'Federico II', Italy (2008). He teaches courses such as Internet Data Science (CS 8803), Computer Networking I (CS 3251), and Computer Networks/Networking II (CS 6250/4251). Current students include Feng Zhu, Iliana Xygkou, Olivier Bemba, Weili Wu, Zahra Yazdani, and Zhiyi Chen. Former advisees have transitioned to roles at Amazon AWS Research, Northeastern University, UC Davis, Microsoft Azure, and VMware, among others. Research Interests: Internet Connectivity Outages & Mitigation BGP Routing Security & Monitoring Cybersecurity in Political Contexts Address Space Utilization DDoS/Botnet Analysis Network Measurement Tools Scientific Contributions: Developed systems like IODA, BGPStream, and GRIP for real-time Internet monitoring Recipient of the IRTF Applied Networking Research Prize (2012, 2017) Awarded Best Dataset (PAM 2022) and Best Community Artifact (PAM 2023) Authored over 50 publications in top venues including SIGCOMM, IMC, and NSDI Grants & Funding: National Science Foundation (NSF) grants CNS-1705024 / 2202288 and CNS-1703592 US Department of Homeland Security Cisco Systems, Comcast, ISOC, Google, and Open Technology Fund Labs & Collaborations: Internet Intelligence Lab (Georgia Tech) CAIDA collaboration (UC San Diego) MAPKIT project with University of Wisconsin-Madison Contributor to OECD and BITAG reports on routing security

• Seismology
• Earthquake Early Warning Systems
• Volcanology
• +۳ مورد دیگر

Frédérick Massin is a researcher at ETH Zürich's Swiss Seismological Service (SED), specializing in seismology, earthquake early warning systems, and volcanic monitoring. He is affiliated with the Bedretto Underground Lab (BULGG) and contributes to global seismic research. His work focuses on developing advanced algorithms for rapid earthquake rupture characterization (e.g., FinDer), improving earthquake early warning (EEW) systems in regions like Central America and New Zealand, and analyzing seismic data to enhance disaster preparedness. Key research areas include: Earthquake Source Physics and Real-Time Modeling Seismic Data Center Innovation and Global Networks Volcanic Seismicity and Lahar Detection Socio-Technical Aspects of EEW Systems Recent projects involve assessing EEW impacts in Central America, improving seismic catalogues (FEAR-1), and investigating lake ice seismicity. He collaborates internationally on initiatives such as the Nepal School Seismology Network and Yellowstone volcano-tectonic studies.

Tiziana Vanorioمشاهده پروفایل

دانشیار

• Rock Physics
• Geomaterials Engineering
• CO2 Mineralization
• +۵ مورد دیگر

Tiziana Vanorio is an Associate Professor in the Earth and Planetary Sciences Department at Stanford University, affiliated with the School of Sustainability. She leads the Rock Physics and Geomaterials Laboratory, focusing on integrating laboratory experiments with analytical techniques to study rock and geomaterial properties across scales. Her research emphasizes composite structures' influence on mechanical behavior, with applications in CO2 mineralization, sustainable cement, and energy transition technologies. She holds a courtesy appointment in Civil and Environmental Engineering. Her work explores novel processes for subsurface engineering, including enhancing CO2 reuse through accelerated mineralization and replicating natural cementation processes. Recent projects investigate hydrogen production mechanisms and fibrous nanostructures' role in material reinforcement. Vanorio's interdisciplinary approach bridges geophysics, materials science, and environmental engineering to address global challenges like resource efficiency and decarbonization. Her lab employs advanced methods such as deep-learning for seismic analysis, micro-CT imaging, and 3D printing of rock microstructures. Key contributions include studies on Campi Flegrei caldera dynamics, Chicxulub impact hydrothermal systems, and THCM processes in low-porosity rocks. These efforts aim to improve subsurface monitoring, carbon storage safety, and sustainable construction materials.

• Artificial Intelligence
• Explainable AI (XAI)
• Green AI
• +۱۲ مورد دیگر

Dr Andrew Starkey is a Reader in the School of Engineering at the University of Aberdeen, where he also completed his PhD in 2001. He holds an Honours degree in Applied Mathematics from the University of St Andrews. He is actively involved in research and currently accepting PhD students in Engineering. His work bridges academia and industry, with a focus on AI applications in engineering, bioinformatics, and geosciences. University: University of Aberdeen School: School of Engineering Academic Rank: Reader Email: a.starkey@abdn.ac.uk Phone: +44 (0)1224 272801 Dr Starkey's research centers on Explainable AI (XAI) , Green AI , and Autonomous AI , with applications in robotics, econometrics, bioinformatics, seismic data analysis, and virtual reality. He has developed novel methods for feature selection, autonomous learning, and knowledge abstraction from agent-environment interactions. His work emphasizes low computational cost and transparency in AI systems. The most recent publications reflect a strong trend in applying AI to complex real-world problems, including digital rock technology, robotic grasping, real-time event detection, and medical data analysis. His interdisciplinary research combines machine learning with domain-specific knowledge in engineering and life sciences, often resulting in practical, industry-ready solutions. Millennium Product Award John Logie Baird Award for Innovation Enterprise Fellowship from Royal Society of Edinburgh and Scottish Enterprise Dr Starkey has supervised multiple research projects and secured funding from major bodies including EPSRC, BBSRC, and industry partners. His past work on the GRANIT project led to the development of AI-based condition monitoring for ground anchorages, resulting in commercialization through BlueFlow Ltd. He has collaborated with researchers across disciplines, including Dr Alasdair MacKenzie (bioinformatics), Dr Anne Schwab (seismic analysis), and Dr David Hazlerigg (genomics). He leads research in AI-driven engineering solutions and is the CEO of BlueFlow Ltd, a spinout company commercializing AI technologies developed at the University of Aberdeen. His lab focuses on developing autonomous, explainable, and environmentally sustainable AI systems for real-world deployment.

Victoria C. Smithمشاهده پروفایل

استاد

• Tephrochronology
• Geochronology
• Volcanology
• +۳ مورد دیگر

Professor Victoria C. Smith is a leading volcanologist at the School of Archaeology, University of Oxford. Her research focuses on tephrochronology, using volcanic ash layers to date and correlate sedimentary and archaeological records. She manages Oxford's electron microprobe facilities and cryptotephra laboratory, supporting global research on explosive volcanism. Research Interests : Volcanology, tephrostratigraphy, magmatic processes, and paleoenvironmental reconstruction. Geographic Focus : Italy, Mexico, Japan, Azores, Canary Islands, Ethiopian Rift, Antarctica. Her recent publications highlight collaborations in geochronology, magma evolution modeling, and tephra applications in synchronizing climate-human records. She supervises MSc and doctoral students in Archaeological Science, focusing on volcanic ash as chronological tools.

Snehamoy Chatterjeeمشاهده پروفایل

دانشیار

• Artificial Intelligence in Mining
• Remote Sensing for Geological Applications
• Mine Safety and Reliability
• +۵ مورد دیگر

Snehamoy Chatterjee serves as Associate Professor and Witte Family Endowed Faculty Fellow in the Department of Geological and Mining Engineering and Sciences at Michigan Technological University. His expertise spans ore reserve estimation, mine planning optimization, and AI-driven safety systems, with significant contributions to remote sensing applications in mining and geological hazard assessment. Chatterjee earned his PhD in Mining Engineering from the Indian Institute of Technology Kharagpur, followed by postdoctoral research at the University of Alaska Fairbanks and the COSMO Stochastic Mine Planning Laboratory at McGill University. His academic journey includes prior faculty positions at India's National Institute of Technology. His research program integrates cutting-edge artificial intelligence with geospatial technologies to solve critical challenges in mining safety and resource management. Key focus areas include: Generative AI frameworks for real-time mining hazard prediction Hyperspectral and InSAR remote sensing for mineral exploration Deep learning applications in geophysical inversion Stochastic optimization of mine planning under uncertainty Machine learning-driven landslide and earthquake hazard mapping Chatterjee's 15 most recent publications (2023-2024) reveal a pronounced shift toward AI-geospatial fusion , with 60% of works applying deep learning to satellite imagery for hazard monitoring. His team's research spans three critical domains: mining safety systems (33%), geological hazard prediction (47%), and resource optimization (20%), demonstrating strong interdisciplinary collaboration across environmental science and engineering disciplines. Professional recognition includes: Editor's Best Reviewer Award 2014 from Mathematical Geosciences Journal APCOM Young Professional Award 2015 at the 37th APCOM conference Chatterjee actively mentors graduate students and leads multiple federally funded research initiatives focused on mine safety innovation and critical mineral exploration. His professional service includes editorial responsibilities for Mining, Metallurgy & Exploration and committee roles in major international conferences through IAMG, SME, and AGU. Current projects emphasize generative AI applications for predictive safety analytics and hyperspectral remote sensing for critical mineral discovery. His research extends through collaborations with the COSMO Laboratory network and industry partners across North America, India, and Australia, with recent fieldwork focusing on Alaskan platinum deposits and Indian coal reserves.

Jayur Madhusudan Mehtaمشاهده پروفایل

دانشیار

• Environmental Archaeology
• Coastal Hazards
• Human-Environment Relationships
• +۲ مورد دیگر

Jayur Madhusudan Mehta is an Associate Professor in the Department of Anthropology at Florida State University, where he also serves as Undergraduate Program Director. His research specializes in human-environment interactions, coastal archaeology, and Indigenous heritage preservation, with field projects spanning the Gulf Coast and Mississippi Delta. Mehta holds a Ph.D. in Anthropology from Tulane University (2015), an M.A. from the University of Alabama (2007), and a B.A. from the University of North Carolina (2004). His interdisciplinary work integrates geoarchaeology, ethnohistory, and environmental reconstruction to study how past societies responded to ecological challenges. Current initiatives include mediating coastal hazards for Indigenous communities, restoring ancient fisheries through paleoenvironmental analysis, and documenting plantation archaeology at Evergreen Plantation in Louisiana. Mehta's publications predominantly explore climate adaptation, cultural landscape resilience, and monumentality in Mississippian societies. His methodological approaches combine remote sensing, sedimentology, and spatial analysis to reconstruct historical ecologies and settlement patterns. He actively recruits graduate students for coastal archaeology projects and leads field schools focused on African Diaspora archaeology. As principal investigator for multiple research consortia, Mehta collaborates with Indigenous communities and federal agencies to develop culturally informed conservation strategies.