جستجوی استاد راهنمای دانشگاهی

Christof Bigler is an Adjunct Professor at ETH Zurich's Department of Environmental Systems Science, where he also serves as Deputy Group Head of the Professorship of Forest Ecology and Senior Scientist. He leads the ETH Tree-Ring Laboratory and teaches courses in dendroecology, applied statistics, and forest ecology. His research focuses on tree mortality, climate impacts on forests, disturbance ecology, and phenology, with a strong emphasis on quantitative methods and long-term data analysis. Bigler holds a PhD in Forest Ecology from ETH Zurich (2003), awarded the ETH Medal for his thesis on tree mortality modeling. He has conducted postdoctoral research in Switzerland and the University of Colorado Boulder, exploring disturbance interactions and dendroecology. He has supervised numerous PhD and master's students, contributing to over 150 publications in top journals like Nature Climate Change and Ecology . His work integrates dendrochronological techniques with statistical modeling to understand forest responses to climate change, including drought effects, tree competition, and mortality patterns. He serves on editorial boards for journals like Agricultural and Forest Meteorology and reviews proposals for national and international science foundations. His research also includes managing forest reserves and studying natural forest dynamics in the Alps and beyond. Education: PhD in Forest Ecology, ETH Zurich (2003) Postdoctoral Research: University of Colorado Boulder (2004–2005) Diploma in Biology, ETH Zurich (1998) Key Awards: ETH Medal for PhD thesis (2003) Professional Roles: Member of the Tree-Ring Society, Editor for Frontiers in Forests , and Commission for Phenology and Seasonality (KPS). Bigler's lab and fieldwork emphasize long-term datasets, including analyses of tree-ring records from Swiss National Park and other reserves. His research highlights the critical role of historical climate data in predicting future forest resilience and adaptation strategies.

• Dendroecology
• Statistical Modeling
• Quantitative Ecology
• +۶ مورد دیگر

Prof. Dr. Oliver Schilling is an Assistant Professor of Hydrogeology at the University of Basel and affiliated with Eawag , the Swiss Federal Institute of Aquatic Science and Technology. He leads research on surface water-groundwater interactions using integrated surface-subsurface hydrological models (ISSHM) and novel tracer techniques including dissolved atmospheric noble gases, environmental DNA, and radioactive tracers. Research Focus : Surface-subsurface hydrology, ecohydrology, groundwater-surface water interactions, tracer hydrogeology, climate change adaptation in water systems Key Projects : Integrated Hydrological Modeling for Operational Forecasting, Sustainable Nitrogen Fertilization, Slow Water Initiatives, Cryosphere-Groundwater Connectivity in Alpine Regions Scientific Contributions include developing HGS-PDAF (modular data assimilation framework), advancing microbial transport algorithms in HydroGeoSphere, and pioneering online flow cytometry for microbial analysis in high-turbidity environments. His work addresses drinking water production via bank filtration along alluvial rivers, critical for 30% of Swiss and 50% of European drinking water supply. Scientific Leadership : Editor, Hydrogeology Journal (since 2025) Associate Editor, Frontiers in Water (since 2021) Coordinator, Swiss Water-Earth Systems (WES) PhD School (2020–2022)

• Hydrogeology
• Biogeochemistry
• Environmental Tracer Techniques
• +۳ مورد دیگر

Dr. Mauro Werder is a Lecturer at the Department of Civil, Environmental and Geomatic Engineering at ETH Zurich. His work focuses on glaciology, subglacial hydrology, and numerical modeling, combining computational methods with field measurements. He has developed widely used models such as GlaDS (Glacier Drainage System) and BITE (Bayesian Ice Thickness Estimation), and contributed to projects like SHMIP and 4D-Antarctica. Current Projects: Gladder (2025-2028), DIWING (2023-2026), LEAD (2020-2026), 4D-Antarctica (2019-2022), CORDS (2023-2024) Education: PhD in Glaciology (2009, Swiss National Science Foundation funded) His research spans subglacial drainage systems, sediment transport (SUGSET model), Bayesian inversion techniques, and field experiments involving artificial lakes and R-channels. He actively teaches courses on GPU-based PDE solving, applied glaciology, and reproducible scientific computing. Scientific Awards: Swiss National Science Foundation (SNF) Fellowship for Prospective Researchers (2010-2011) European Union (FP7) Marie Curie International Outgoing Fellowship (2011-2014) He collaborates with institutions like the Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), and contributes to software development through packages like BITEmodel.jl and Parameters.jl. His fieldwork includes experiments on Greenland's Jakobshavn Isbræ and Switzerland's Plaine Morte glacier.

• Glaciology
• Hydrology
• Numerical Modeling
• +۷ مورد دیگر

Prof. Patrick Jenny is a Full Professor at the Department of Mechanical and Process Engineering and Head of the Institute of Fluid Dynamics at ETH Zurich. His research focuses on computational fluid dynamics (CFD), numerical methods for turbulent and multiphase flows, and reservoir simulation. He has held positions at ChevronTexaco and Cornell University, and received the National Latsis Prize 2005. PhD in CFD from ETH Zurich (1997) Postdoctoral work at Cornell University (1997–1999) Senior Researcher at ChevronTexaco (1999–2003) Research interests include: turbulent reactive flows, PDF modeling, multi-scale reservoir simulation, and data assimilation in engineering systems. He teaches courses on fluid dynamics, turbulence, and computational methods. Over 100 peer-reviewed publications span topics like fracture modeling, LES/RANS coupling, and particle-laden flows. His work bridges academia and industry, addressing challenges in energy systems, environmental engineering, and numerical algorithms. Winner: National Latsis Prize 2005 Led over 20 PhD projects and collaborates with institutions globally. His lab develops open-source tools for CFD and energy systems analysis.

• Computational Fluid Dynamics
• Turbulent Reactive Flows
• Multiphase Flow Modeling
• +۳ مورد دیگر

Niklas Linde is a full professor at the University of Lausanne's Faculty of Geosciences and Environment, leading the Department of Earth Sciences. He holds a PhD in Geophysics from Uppsala University (2005) and has held roles including Assistant Professor (2008), Associate Professor (2013), and Full Professor (2019). His research focuses on transforming geophysical signals into realistic hydrogeological models with rigorous uncertainty quantification. Key areas include probabilistic inversion, Bayesian methods, and geostatistical modeling applied to environmental and subsurface processes. Education: PhD in Geophysics (Uppsala University, 2005), postdoctoral positions at Lawrence Berkeley National Lab (USA), CNRS-CEREGE (France), and ETH Zurich (Switzerland). He joined UNIL in 2008 as an Assistant Professor in Environmental Geophysics. Research interests span geophysical inversion techniques, subsurface heterogeneity characterization, and the integration of geophysical and hydrological data. Current projects emphasize Bayesian approaches for model selection and rare event estimation, supported by grants from the European Commission and Swiss National Science Foundation. Collaborations involve international teams addressing challenges in hydrogeology, rock fracture dynamics, and 4D hydrogeology. Publications reflect advancements in inverse problem solving, stochastic simulation, and machine learning applications. His work bridges theory and practice, with field studies in alpine environments, fractured media, and environmental monitoring. Students under his supervision have explored topics like deep generative networks and Bayesian hydrogeological inversion. Advising: Supervised over a dozen PhD students, including recent works on variational Bayesian methods and geophysical data fusion. Grants include projects on uncertainty quantification and experimental design. Active in scientific societies and editorial roles, contributing to methodological advancements in Earth sciences.

• Geophysics
• Environmental Geophysics
• Probabilistic Inversion
• +۳ مورد دیگر

Philip Brunner is a Professor of Hydrogeology at the University of Neuchâtel's Faculty of Science since 2012. He is based at the Center for Hydrogeology and Geothermics (CHYN), leading the Laboratory of Hydrogeological Processes. His work centers on sustainable water resource management through quantitative tools. He earned his PhD from ETH Zurich, focusing on sustainable salt and water management in Western China's agricultural basins. Post-PhD, he conducted three years of postdoctoral research in Australia, developing new approaches for simulating river-aquifer interactions. Brunner's research spans surface water-groundwater interactions, numerical modeling, and remote sensing. He integrates methods from numerical modeling, remote sensing, scientific computing, and isotopic chemistry. His interdisciplinary collaborations with mathematicians, biologists, and physicists address challenges in agriculture, ecohydrology, engineering, and sustainable resource management. Recent publications highlight innovative tracer techniques (noble gases, microbes), low-cost monitoring systems, and advanced numerical models. His work tackles climate change impacts on ecosystems, groundwater in conflict zones, and sustainable practices in diverse environments including mountains and agricultural regions. He teaches courses such as Introduction to Hydrological Processes (Master), Numerical Modeling (Master), Remote Sensing (Master), and Introduction to Soil Physics (Bachelor, in French). His laboratory serves as a center for experimental and computational hydrogeological research.

• Hydrogeology
• Surface Water-Groundwater Interactions
• Numerical Modeling
• +۳ مورد دیگر

Théo Blanc is a PhD researcher at the Centre for Hydrogeology and Geothermics (CHYN) within the Faculty of Science at the University of Neuchâtel. He concurrently serves as a visiting scientist at the Environmental Isotopes Group of eawag (Dübendorf). His research focuses on surface water-groundwater interactions, hydrogeological tracers, and riverbed clogging dynamics. Blanc holds a Bachelor's degree in Earth Sciences from ETH Zurich (2015–2018) and a Master's in Hydrogeology and Geothermal Energy from the University of Neuchâtel (2019–2022). His work integrates experimental approaches such as in-situ column experiments and novel gas tracer technologies (e.g., helium and dissolved gases) with advanced numerical modeling. Key contributions include development of silicone membrane-based gas tracer systems and microbial cytometry techniques for subsurface flow analysis. Recent studies have explored the impacts of river engineering projects on hydrological systems and flood dynamics using portable spectrometry tools like miniRUEDI. Blanc teaches as a course assistant in the General Geology (Bachelor) and Geological Modeling (Master) programs. His research outputs emphasize tracer-based methodologies and their application in understanding complex hydrological processes. He actively collaborates with the Hydrogeological Processes Group and the Environmental Isotopes Group, focusing on advancing field instrumentation and model-data integration techniques.

• Surface water – groundwater interactions
• Hydrogeological tracers
• Impacts of river works
• +۳ مورد دیگر

Leon Bungert is a Professor of Mathematics of Machine Learning at the University of Würzburg, working in applied analysis and numerics with a particular focus on data science and machine learning. His research investigates PDEs and variational models on graphs, adversarial robustness of machine learning, variational regularization, and nonlinear optimization. Dr. Bungert serves as a guest editor for the European Journal of Applied Mathematics, an associate editor for Advances in Continuous and Discrete Models: Theory and Applications, and is a member of the program committee at SSVM 2025. He is also an ELLIS member and actively organizes conferences and workshops, including "MIA'25" at IHP in Paris (January 13-15, 2025), "Synergies of Machine Learning and Numerics" in Osaka (March 11-13, 2025), and "Mathematical Analysis of Adversarial Machine Learning" in Oaxaca (August 17-22, 2025). Research Interests Dr. Bungert's primary research areas include: PDEs on graphs Adversarial robustness in machine learning Inverse problems Optimization Variational problems in L-infinity Nonlinear eigenvalue problems Image reconstruction with structural priors His work bridges theoretical mathematics with practical applications in machine learning, particularly focusing on the mathematical foundations of deep learning and developing robust algorithms that can withstand adversarial attacks. He has made significant contributions to understanding the connections between partial differential equations and machine learning algorithms. Research Trends Analysis of Dr. Bungert's recent publications reveals a strong focus on the intersection of machine learning and mathematical analysis. A key theme is the application of variational methods and partial differential equations to machine learning problems, particularly in understanding and improving the robustness of neural networks against adversarial examples. His work on Lipschitz learning on graphs has established important theoretical foundations for graph-based semi-supervised learning. Additionally, his research on the infinity Laplacian and p-Laplacian equations provides deep insights into the mathematical structure of machine learning algorithms. The development of Bregman learning frameworks for sparse neural networks represents a significant contribution to efficient deep learning model training. Professional Activities Dr. Bungert is actively involved in the academic community through editorial roles and conference organization. His current professional activities include: Guest editor for the European Journal of Applied Mathematics Associate editor for Advances in Continuous and Discrete Models: Theory and Applications Member of the program committee at SSVM 2025 ELLIS member Co-organizer of multiple international conferences and workshops Technical Contributions Dr. Bungert has developed several open-source software packages that implement his theoretical contributions, including: Code for convergence rates of Lipschitz learning on graphs A Bregman training framework for sparse neural networks CLIP: Cheap Lipschitz Training of Neural Networks Nonlinear Power Method for Proximal Operators and Neural Networks Robust Image Reconstruction with Misaligned Structural Information These implementations are primarily in Python and MATLAB, demonstrating his commitment to making theoretical advances accessible for practical applications.

• Applied Analysis
• Numerical Analysis
• Data Science
• +۶ مورد دیگر

Qi Tang is a Research Fellow in the Department of Environmental Science at the University of Basel and concurrently serves as Coordinator of the Swiss Water Earth Systems PhD School at the University of Neuchâtel. His expertise spans hydrogeology, data assimilation, and Earth system modeling. He holds a PhD in Hydrogeology from RWTH Aachen University (2017) and has held postdoctoral positions at institutions including the Alfred Wegener Institute (Germany), the University of Basel, and the Chinese Academy of Sciences. Education: PhD in Hydrogeology, RWTH Aachen University, Germany (2012–2017) MSc in Hydrology and Water Resources, Beijing Normal University (2009–2012) BSc in Applied Mathematics, China Agriculture University (2005–2009) Research Interests: Qi Tang focuses on advancing coupled Earth system models through data assimilation techniques. His work integrates hydrological, oceanographic, and climatic processes to improve predictive accuracy. Key areas include river-aquifer interaction dynamics, satellite data integration in ocean-atmosphere models, and cloud computing for real-time water resource management. His research bridges theoretical modeling with practical applications in environmental monitoring and climate prediction. Publications: His articles emphasize data-driven approaches to environmental systems. Recent work highlights coupled model improvements using satellite data (e.g., ocean-atmosphere interactions), ensemble Kalman filtering for flood simulations, and Bayesian networks for precipitation modeling. These studies underscore his expertise in both computational methods and field applications. Advising & Grants: While no formal advisees are listed, his postdoctoral roles suggest involvement in mentoring junior researchers. No specific grants are mentioned in the provided texts. Labs/Teams: Affiliated with the Hydrogeological Processes group at the Center for Hydrogeology and Geothermal Energy (CHYN), University of Neuchâtel. This group specializes in geothermal energy, hydrochemistry, and stochastic hydrogeology.

• Hydrogeology
• Data Assimilation
• Earth System Modeling
• +۳ مورد دیگر

Jörg Franke is a Lecturer in Climatology and PostDoc researcher at the Institute of Geography, University of Bern, Switzerland. He specializes in paleoclimatology, climate modeling, and data assimilation techniques. His research focuses on reconstructing historical climate patterns using proxy data and climate models, particularly through the development of paleo-reanalysis systems like ModE-RA and EKF400. Educational Background: Franke earned a Diploma in Physical Geography (2003) from the University of Hanover, followed by a PhD in Geosciences (2008) from the University of Bremen, where he studied radiocarbon reservoir ages in marine environments. His postdoctoral work (2008–2011) at the Swiss Federal Research Institute WSL focused on dendrochronology and paleoclimatic reconstructions. Research Interests: His work emphasizes data assimilation of instrumental and proxy records, climatic extremes analysis, and spatial climate reconstructions. He has contributed to understanding the impacts of volcanic eruptions (e.g., Laki 1783) on global and regional climate systems, as well as the role of atmospheric circulation patterns in historical climate variability. Key Projects: Co-developed the ModE-RA global paleo-reanalysis system (1421–2008 CE) and led efforts to integrate satellite and reanalysis data for climate studies in regions like Eritrea and the Hindu Kush Himalaya. His tools, such as ClimeApp, advance climate data processing for historical reconstructions. Professional Roles: In addition to teaching quantitative methods in geography, Franke managed climate data services at the Oeschger Centre for Climate Change Research (2012–2014) and has contributed to interdisciplinary projects linking paleoclimate data with modern climate models. Lab/Team Affiliations: Active in the Climate Research Group and Oeschger Centre at the University of Bern, collaborating with international teams on paleo-reanalysis and climate variability studies.

• Climate Modeling
• Paleoclimatology
• Data Assimilation
• +۴ مورد دیگر

Naonori Ueda is a Research Professor and Deputy Director at RIKEN Center for Advanced Intelligence Project. He also serves as a Visiting Fellow at NTT Communication Science Laboratories, Research Supervisor for Mathematical Information Platform at Japan Science and Technology Agency (JST), and Visiting Professor at Kobe University's Graduate School of System Informatics. His distinguished career spans academia, government research institutions, and industry collaboration, with significant contributions to advancing artificial intelligence and machine learning applications across multiple scientific domains. Dr. Ueda's research interests focus on the intersection of machine learning, artificial intelligence, and physical sciences. He specializes in physics-informed deep learning approaches that integrate governing physical equations with neural network architectures. His work spans geophysical data analysis, remote sensing applications, computational seismology, and environmental monitoring systems. He has pioneered methods for crustal deformation modeling, earthquake prediction, tsunami inundation forecasting, and satellite imagery analysis using advanced machine learning techniques. His research demonstrates how AI can solve complex scientific problems by bridging the gap between data-driven approaches and physical domain knowledge. His publication record reveals a strong trend toward applying machine learning to solve real-world geophysical and environmental challenges. His recent work shows increasing sophistication in physics-informed neural networks that incorporate domain-specific knowledge into deep learning architectures. The publications span high-impact journals like Nature Communications, demonstrating the interdisciplinary significance of his work. His research consistently focuses on practical applications of AI for disaster prevention, environmental monitoring, and scientific discovery. Fellow of IEICE (Institute of Electronics Information and Communication Engineers) Member of Japan Prize field review committee Selection Committee Member for Brilliant Female Research Award (The Jun Ashida Award) Member of Kyoto Prize Selection Committee Dr. Ueda has secured substantial research funding through multiple government-sponsored projects including RIKEN Pioneering Project 'Prediction Science,' JST AIP Acceleration Research projects on weather prediction and drug discovery, and AMED-funded medical research initiatives. His leadership extends to serving as Sub-project Director for Japan's Moonshot R&D Project. He actively mentors researchers through his roles at RIKEN, NTT, and various academic institutions, fostering the next generation of AI scientists. As Deputy Director of RIKEN Center for Advanced Intelligence Project, Dr. Ueda leads one of Japan's premier AI research initiatives. He also serves on the Advisory Board of Kobe University's Mathematical and Data Science Center and Kyoto University's Graduate School of Informatics. His leadership extends to coordinating the AI Seminar at Osaka Industrial Association and supervising the Keihanna 'Edison Society' at the International Institute for Advanced Studies, demonstrating his commitment to bridging academic research with industrial applications.

• Machine Learning
• Artificial Intelligence
• Physics-Informed Deep Learning
• +۵ مورد دیگر

Dr. Constantin Zohner is a Lecturer at the Department of Environmental Systems Science, ETH Zürich. His research focuses on plant phenology, climate change impacts, and ecosystem responses to global environmental changes. He investigates how temperature, precipitation, and atmospheric conditions influence plant growth cycles, carbon dynamics, and species interactions across ecosystems. Affiliation: ETH Zürich, Department of Environmental Systems Science Key Research Themes: Phenological shifts in temperate and boreal forests Soil organic carbon dynamics Climate change mitigation strategies His work integrates field observations, remote sensing data, and modeling to address questions about plant adaptation to environmental stressors. Recent studies highlight the role of leaf senescence timing, phosphorus dynamics, and species composition in shaping ecosystem resilience. He collaborates on global assessments of forest restoration potential and urban tree phenology.

• Ecology
• Climate Change Biology
• Plant Phenology
• +۳ مورد دیگر

Matthias Huss is a Senior Researcher in the Department of Geosciences at the University of Fribourg. His primary affiliation is within the Faculty of Science and Medicine. His research focuses on glaciology, climate change impacts, hydrology, and mountain ecosystems, with a strong emphasis on glacier dynamics, mass balance modeling, and climate change adaptation strategies. He has contributed extensively to understanding the global hydrological response to glacier retreat and the implications for hydropower and water resources. His work integrates field observations, remote sensing, and numerical modeling to address challenges in cryospheric science. Key areas include the impact of glacier retreat on water availability, the development of bedrock topography models for glaciers, and the assessment of glacier volume projections under various climate scenarios. He collaborates internationally on projects such as glacier monitoring in Central Asia and the Antarctic Peninsula. Huss has authored over 100 peer-reviewed articles since 2007, with significant contributions to journals like Nature Climate Change , The Cryosphere , and Geophysical Research Letters . His research highlights the urgency of addressing cryospheric changes in mountain regions and their cascading effects on ecosystems and human societies. While no formal awards or grants are explicitly listed in the text, his extensive publication record and collaborative projects reflect a high level of academic engagement and recognition. He is actively involved in interdisciplinary initiatives, such as the Ice Thickness Models Intercomparison Experiment (ITMIX), and contributes to policy-relevant studies on climate change mitigation and adaptation.

• Glaciology
• Climate Change
• Hydrology
• +۳ مورد دیگر

Senn Jeremy is a doctoral student and associate researcher at the University of Lausanne, affiliated with the LIVES network. His research focuses on the evolution of local religious groups in Switzerland, particularly secularization trends, diversity dynamics, and inclusivity/exclusivity processes. His recent work analyzes how religious communities appear, persist, or disappear over time, using sociological and demographic frameworks. Key publications include studies on Muslim communities in Switzerland, generational faith decline, and institutional adaptation to societal changes. He collaborates with scholars like Jörg Stolz and Christophe Monnot, contributing to journals such as the Journal for the Scientific Study of Religion. Senn Jeremy's methodological approach combines historical data analysis, large-scale surveys, and sociological case studies, though no explicit awards or grants are mentioned in the provided texts.

• Religious Studies
• Sociology
• Social Dynamics
• +۳ مورد دیگر

Prof. Martin Wild is a Lecturer in the Department of Environmental Systems Science at ETH Zürich. His research focuses on the global energy and water cycle, surface radiation budgets, and climate change dynamics. He leads the Global Energy Balance Archive (GEBA) and serves as a Lead Author for the IPCC's 5th and 6th Assessment Reports. His work bridges observations and climate models, emphasizing global dimming/brightening mechanisms and their implications for Earth's energy balance. Wild has held key roles, including Chair of the International Radiation Commission's Global Energy Balance Working Group and EGU Science Officer. His research integrates atmospheric physics, climate modeling, and observational data to address critical questions about radiative forcing, climate feedbacks, and energy budget changes. Notable contributions include assessing CMIP6 models' representation of the global energy balance and analyzing decadal trends in solar radiation. Publications highlight his expertise in radiative processes, cloud effects, and climate system interactions. His work on global dimming and brightening mechanisms, aerosol impacts, and extreme radiation events underscores the interplay between human activities and climate variability. Wild's interdisciplinary approach informs climate policy and renewable energy strategies through insights into solar radiation trends and their socioeconomic implications.

• Global Energy and Water Cycle
• Climate Change
• Global Dimming and Brightening
• +۳ مورد دیگر