جستجوی استاد راهنمای دانشگاهی

Pascal Frossard is a Full Professor at the Department of Electrical Engineering in the School of Engineering (STI) at EPFL, with a courtesy appointment in the School of Computer and Communication Sciences. He founded and directs the LTS4 laboratory since 2003, co-leads the EPFL AI Center and Swiss Data Science Center, and serves as Associate Dean for Research at STI. Research Focus: Machine Learning, Graph Signal Processing, AI Applications in Healthcare, Computer Vision Academic Leadership: IEEE Fellow, ELLIS Fellow, Conference Chair roles Key Projects: Digital Pathology for Oncology, Cardiac Digital Twins, Robust Machine Learning Research Interests: His work bridges signal processing, machine learning, and applied mathematics, emphasizing biomedical applications. Recent research includes adversarial robustness in classifiers, network representation learning, and 360-degree video analysis. Scientific Awards: IEEE Fellow ELLIS Fellow Leadership in IEEE technical committees Advising & Grants: Supervised 20+ PhD students and postdocs. Secured major grants from PHRT, Hasler Foundation, FNS-Sinergia, Armasuisse, Google, and Cisco.

• Machine Learning
• Data Science
• Graph Signal Processing
• +۶ مورد دیگر

Prof. Knut Drescher is an Associate Professor at the Biozentrum, University of Basel , leading a research group focused on bacterial biofilms , swarming , and microbial multicellularity . Previously, he served as a Professor of Biophysics and Max Planck Research Group Leader at Philipps-Universität Marburg (2015-2021) and conducted postdoctoral research at Princeton University. Research Interests: Physical and biological mechanisms of biofilm formation Cell-cell interactions in microbial communities Antibiotic resistance in biofilms Hydrodynamics of bacterial swarms Evolution of cooperation in multispecies biofilms Development of bioimaging software (BiofilmQ, BacStalk) Scientific Awards: 2023: SNSF Consolidator Grant 2019: Heinz Maier-Leibnitz Prize (DFG), VAAM Research Prize, IUPAP Young Scientist Prize 2016: ERC Starting Grant Advising & Grants: Advises PhD and Master's students in microbiology, biophysics, and bioinformatics Secured major grants from ERC , HFSP , and DFG

• Bacterial Biofilms
• Microbial Multicellularity
• Biophysics
• +۵ مورد دیگر

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

Jan Dirk Wegner is an Associate Professor at the University of Zurich, holding the chair in 'Data Science for Sciences' and leading the EcoVision Lab. He previously served as a Postdoc (2012–2016) and senior scientist (2017–2020) at ETH Zurich's Photogrammetry and Remote Sensing Group, following his PhD (with distinction) from Leibniz University Hannover (2011). His research bridges machine learning, computer vision, and remote sensing to address environmental and geoscience challenges, focusing on large-scale environmental data analysis, vegetation monitoring, and climate change mitigation. Education: PhD (with distinction) in Geodesy, Leibniz University Hannover (2011) Postdoc, ETH Zurich (2012–2016) Senior Scientist, ETH Zurich (2017–2020) Research Interests: Machine Learning, Computer Vision, Remote Sensing, Environmental Science, Climate Science, Geosciences, Explainable AI, Uncertainty Quantification, and Applications in Sustainability. The EcoVision Lab develops data-driven methods for global-scale environmental monitoring, including vegetation parameter mapping, flood prediction, forest degradation detection, and AI-driven ecological modeling. Awards: ETH Postdoctoral Fellowship (2012–2016) Science Prize of the German Geodetic Commission WEF Young Scientist Class 2020 (Top 25 globally under 40) Advising & Leadership: Director of the University of Zurich's Doctoral School in Data Science, leading the EcoVision Lab, and coordinating the CVPR EarthVision Workshops. His roles include Vice President of ISPRS Technical Commission II, member of the ETH AI Center, ELLIS, and UN-ETH Partnership. Labs/Teams: EcoVision Lab focuses on interdisciplinary AI applications for environmental challenges, collaborating with NGOs, governments, and industry to translate research into societal impact.

• Machine Learning
• Computer Vision
• Remote Sensing
• +۷ مورد دیگر

Fabio Sigrist is a Professor of Applied Statistics and Data Science at the Institute of Financial Services Zug (IFZ) , part of the Lucerne University of Applied Sciences and Arts . He also holds a Senior Scientist and Lecturer position at the Seminar for Statistics, ETH Zurich . His career spans academic research, industry consulting, and project leadership in finance and data science. PhD in Statistics (2013), ETH Zurich MSc in Mathematics with distinction (2008), ETH Zurich MEd in Mathematics Education (2008), ETH Zurich Sigrist’s research focuses on integrating Machine Learning with Spatial Statistics for applications in Financial Econometrics and Credit Risk . His work includes developing novel algorithms like GPBoost and KTBoost , advancing spatio-temporal modeling , and applying tree-based boosting to financial problems. Projects such as CreHos (credit risk in hospitality) and NISMO (interpretable real estate modeling) highlight his interdisciplinary approach. His publications address challenges in large-scale spatial data , loss given default modeling , and stock volatility prediction . He contributes to software development with tools like spate (R package) and varycoef (spatially varying coefficients).

• Machine Learning
• Spatial Statistics
• Financial Econometrics
• +۳ مورد دیگر

Hugo Duminil-Copin is a Full Professor at the University of Geneva and a permanent professor at the Institut des Hautes Études Scientifiques (IHES) since 2016. His research focuses on Mathematical Physics , Combinatorics , and Probability Theory . Education : École Normale Supérieure (ENS) Paris, University of Paris-Saclay Awards : 2022 Fields Medal for work in statistical physics Research Trends : Probabilistic aspects of lattice models Phase transitions and critical phenomena Conformal invariance and percolation theory Collaborations : Active collaborations with researchers such as R. Panis, S. Goswami, I. Manolescu, and others. Teaching : Offers courses in mathematical physics and probability at the University of Geneva. His recent publications emphasize critical models, random-cluster models, and Gaussian free fields, with applications in planar and high-dimensional systems. He supervises doctoral students including Emile Averous , Aman Markar , and Tiancheng He .

• Mathematical Physics
• Combinatorics
• Probability Theory

Johanna Ziegel is a Professor of Statistics at ETH Zurich, Switzerland, since 2024, and a Visiting Scientist at the Heidelberg Institute for Theoretical Studies (HITS). Previously, she held positions at the University of Bern, where she was promoted to Full Professor in 2023. Her research focuses on decision-theoretically sound methods for forecast evaluation, probabilistic forecasting, risk measures in finance, and applications in meteorology, medicine, and climate science. She is actively involved in editorial roles for journals like Bernoulli , JASA: Theory & Methods , and SIAM Journal on Financial Mathematics . Education: PhD in Stereological Analysis of Spatial Structures from ETH Zurich (2010), supervised by Paul Embrechts and Eva B. Vedel Jensen. Postdoctoral research at the University of Melbourne and Heidelberg University. Research Interests: Forecast evaluation, elicitable functionals, risk measures, isotonic regression, statistical calibration, and applications in finance, climate science, and biostatistics. Her work bridges theoretical statistics with practical challenges in uncertainty quantification and decision-making under uncertainty. Advising & Collaborations: Supervised 7 PhD students and mentored several postdocs. Collaborates with the Computational Statistics group at HITS and the Oeschger Centre for Climate Change Research. Her group explores distributional regression under order constraints and novel methods for forecast comparison. Recognition: Credit Suisse Award for Best Teaching (2022), H.I.T. Program for Academic Leadership (2021–2022). Active in professional service, including the Bernoulli Society Council and editorial boards.

• Statistical Forecasting
• Probability Theory
• Financial Risk Management
• +۳ مورد دیگر

Ueli Grossniklaus is an Ordinary Professor at the University of Zurich within the Faculty of Mathematical and Natural Sciences , affiliated with the Department of Plant and Microbiology . His work focuses on plant developmental biology, particularly epigenetic and genetic mechanisms governing reproduction and adaptation. Key Courses: Epigenetics, Plant Biology Workshop, Group Seminars on Current Research Laboratory Techniques: Advanced methods in plant cell mechanics, transcriptomics, and genome editing Research Interests span plant epigenetics, reproductive biology, and the interplay between environmental stress and genetic regulation. He investigates: Mechanistic control of gametogenesis and fertilization Epigenetic contributions to plant adaptation Evolutionary implications of asexual reproduction Biophysical forces in plant cell growth Publication Trends (2025–2018) reveal expertise in: Arabidopsis and fern model systems Epigenetic regulation (DNA methylation, histone dynamics) Apomixis and hybrid seed failure mechanisms Biomechanics of pollen tubes and carnivorous plants Genome editing tools (CRISPR) and long-read sequencing Scientific Collaborations include interdisciplinary projects on: Microfluidic devices for plant cell analysis Gene drive ecology and ethics 3D imaging of plant reproductive structures Advising and Grants focus on mentoring through research internships in developmental biology, genetics, and systems biology. His lab engages in: Epigenetic response to environmental stress Cell wall mechanics in reproduction Computational modeling of plant growth Laboratory Teams integrate plant biologists, bioengineers, and computational scientists to study: Mechanistic gene regulation Evolutionary developmental biology Microrobotics for cellular force measurement

• Plant Developmental Biology
• Epigenetics
• Plant Genetics
• +۵ مورد دیگر

Eva Cantoni is a Full Professor at the Research Center for Statistics within the Geneva School of Economics and Management , University of Geneva. Her expertise spans robust statistical methodology, model selection, and applications in ecology and medicine. Ph.D. from University of Geneva Accredited European Statistician (FENStatS) Research Interests : She specializes in Robust statistics for real-world data Variable/model selection in high-dimensional settings Nonparametric and semi-parametric regression Zero-inflated and overdispersed count models Longitudinal and spatiotemporal data analysis Her work addresses ecological challenges (fish stock assessment), medical applications (hospital congestion modeling), and housing market analysis. Recent Trends in Publications : Recent articles focus on Confidence intervals for robust mixed models Editorial leadership in robust statistics Applications to fisheries science and public health Flexible modeling frameworks for complex data Comparative studies of statistical measures Extremes modeling in healthcare Leadership & Grants : She has served as: Vice-Dean for Teaching (2020-2023) Director of Master's in Statistics (2012-2019) Director of Applied Statistics Certificate (2015-2019) President, Swiss Federal Statistics Committee (2024-2027) Specialty Chief Editor, Frontiers in Applied Mathematics (2024) Grants include projects on Robust solutions for modern data (2023-2025) Sustainable fisheries modeling (2018-2021) Advancements in state-space models (2014-2017) Software Contributions : Developed R packages for robust statistical methods: confintROB (bootstrap confidence intervals) RobSSM (robust state-space models) R2_LMM (explained variation measures)

• Robust statistics
• Variable and model selection
• Nonparametric regression
• +۶ مورد دیگر

Rachid Guerraoui is a Full Professor at the École polytechnique fédérale de Lausanne (EPFL) where he leads the Distributed Computing Laboratory (DCL) within the School of Computer and Communication Sciences. He holds appointments in multiple departments including IC-SSC and IC-SIN for teaching, and serves on the IC Academic Evaluation Committee. A Moroccan/Swiss/French researcher, Guerraoui has previously been affiliated with Commissariat à l'Energie Atomique in Saclay, Hewlett-Packard Labs in Palo Alto, the Massachusetts Institute of Technology in Boston, and Collège de France in Paris. Guerraoui's research focuses on distributed and concurrent computing across various scales, from multiprocessors to wide-area networks. His work spans Byzantine fault tolerance, distributed machine learning, blockchain technologies, transactional memory, and consensus algorithms. His recent publications reveal a strong emphasis on Byzantine-resistant machine learning, decentralized learning systems, and the theoretical foundations of distributed consensus. The research demonstrates significant contributions to making distributed systems more robust, efficient, and secure against adversarial conditions. Guerraoui has received numerous prestigious awards including ACM Fellow (2012), Professor at College de France (2018), Nygaard-Dahl Award (2024), and Barroso Award (2025). His work has earned multiple best paper awards at top conferences including DISC, ICDCS, IPDPS, and ACM Middleware. He serves as Associate Editor of the Journal of the ACM (2010-2025) and has chaired program committees for major conferences such as PODC, DISC, and Middleware. As an educator, Guerraoui supervises numerous doctoral students and has mentored many successful researchers who now work at leading institutions and companies including Meta, Oracle Labs, Chainlink Labs, and Protocol Labs. He teaches courses on Distributed Algorithms and Concurrent Algorithms at EPFL, emphasizing both theoretical foundations and practical implementations. His educational initiatives include Wandida, a library of scientific e-synopses, and Zettabytes, projects aimed at making computer science accessible to broader audiences.

• Distributed Computing
• Concurrent Computing
• Byzantine Fault Tolerance
• +۷ مورد دیگر

Prof. Valentina Boeva is an Assistant Professor at the Department of Computer Science, ETH Zürich, specializing in biomedical informatics. Her research focuses on integrating machine learning and computational methods to address challenges in genomics, oncology, and precision medicine. She holds a position in the Professur für Biomedizininformatik (Biomedical Informatics) and is based at CAB G32.2, Universitätstrasse 6, Zürich, Switzerland. Her work emphasizes applications such as cancer biomarker discovery, tumor heterogeneity analysis, and epigenetic profiling. She teaches courses including Machine Learning Seminar, Data Science Lab, and Machine Learning for Genomics. Her research group develops computational tools like CDState and UniversalEPI to decode complex biological systems. She actively publishes in top-tier journals, with recent work on exosome-driven diagnostics and chromatin interaction modeling. Her scientific contributions span methodologies for single-cell data analysis, survival modeling, and drug response prediction. She collaborates across disciplines to bridge computational science with clinical applications in cancer research.

• Machine Learning
• Bioinformatics
• Genomics
• +۳ 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

Jean-Louis Scartezzini is an Honorary Professor at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the School of Architecture, Civil and Environmental Engineering (ENAC) and the Solar Energy and Building Physics Laboratory (LESO-PB). His research focuses on natural/artificial lighting, solar energy systems, and building technology, with a strong emphasis on energy efficiency and sustainability. Director of LESO-PB since 1994 Founded and led several institutes, including the Institute for Infrastructure, Resources, and Environment (2002–2009) Doctorat in Physics from EPFL (1986) Extensive international collaborations, including visiting roles at NUS (2009) and LBNL/UCLA (1988) Research interests include: - Daylighting and lighting control systems - Passive/active solar technologies - Urban microclimate and energy systems - Stochastic simulation and predictive control Recent work addresses climate change impacts on energy systems, urban sustainability, and machine learning applications in energy optimization. Key publications span lighting health impacts, renewable integration, and microclimate modeling Awards include the European Solar Prize (2001/2002) and Walsh-Weston Bronze Medal (1998) Mentored over 20 PhD students, many leading in academia and industry (e.g., Marilyne Andersen at EPFL, Flavio Foradini at E4Tech).

• Natural and Artificial Lighting
• Solar Energy (Passive and Active)
• Building Technology
• +۳ مورد دیگر

Mathias Lerch serves as Lecturer and Head of the Urban Demography Laboratory (URBDEMO) at the School of Architecture, Civil and Environmental Engineering (ENAC) of the Swiss Federal Institute of Technology Lausanne (EPFL). With expertise spanning population dynamics, urbanization, and demographic estimation, he bridges demography with urban planning and environmental science through interdisciplinary research on mortality, fertility, and migration patterns. His research centers on Population and Development, International Demography, and Urban Demography, examining how socioeconomic and environmental factors interact with demographic change. Methodologically, Lerch specializes in data collection, linkage, quality assessment, and advanced statistical modeling for demographic estimation and multi-regional projection, with particular focus on migration systems, fertility transitions, and mortality disparities in urban contexts. Analysis of his 15 most recent publications (2017-2025) reveals consistent investigation into migration patterns across rural-urban continua, fertility transitions in developing regions, and mortality outcomes in urban environments. His work demonstrates methodological innovation through multi-regional projection techniques and large-scale dataset integration, significantly advancing demographic estimation practices and policy-relevant insights for urban population growth. Dr. Lerch currently advises PhD students Beckendorff Dorothee and Du Wenxiu while teaching courses including Urban Demography and Border Forensics at EPFL. His advisory work focuses on training the next generation of demographers in quantitative methods and urban population analysis. As head of URBDEMO, Lerch leads a research team developing systemic frameworks for understanding urban population dynamics. The laboratory's work integrates demographic methods with urban studies to address contemporary challenges in urbanization, migration flows, and sustainable city development through innovative data linkage and modeling approaches.

• Population and Development
• Demography
• Migration Studies
• +۳ مورد دیگر