جستجوی استاد راهنمای دانشگاهی

Claudia R. Binderمشاهده پروفایل

استاد

• Urban Sustainability
• Transition Research
• Urban Metabolism
• +۵ مورد دیگر

Claudia R. Binder is Full Professor at EPFL's School of Architecture, Civil and Environmental Engineering, leading the Laboratory for Human-Environment Relations in Urban Systems (HERUS) since 2016. Previously, she held professorships at the University of Munich (2011-2016), University of Graz (2009-2011), and University of Zurich (2006-2009). She served as Dean of EPFL's ENAC School from 2020-2023 and holds advisory roles with Swiss federal institutions including the Mercator Foundation since 2024. Her academic foundation includes a Biochemistry degree and PhD in Environmental Sciences from ETH Zurich, followed by postdoctoral research at the University of Maryland. This interdisciplinary background underpins her research approach spanning natural and social sciences. Professor Binder's work centers on urban sustainability transitions, examining urban metabolism dynamics through systems science frameworks. She investigates energy-food-transport interdependencies in cities using transdisciplinary methods that integrate material flow analysis, spatial modeling, and socio-technical assessments. Her research particularly emphasizes regulatory mechanisms and transformation drivers in human-environment systems, with case studies across Swiss and global urban contexts. Recent publications reveal evolving focus from foundational urban metabolism studies toward actionable transition strategies. Her 2024-2025 work increasingly addresses social tipping dynamics, circular decarbonization, and spatially explicit waste management, demonstrating methodological innovation through geo-referenced material flow analysis and participatory backcasting frameworks. Key thematic clusters include energy innovation diffusion, plastic waste governance, and demand-side flexibility in residential systems. She actively mentors 7 current PhD candidates while supervising 11 graduates since 2018, with research spanning urban metabolism modeling, sustainability assessment, and transition governance. Her leadership extends to Swiss National Science Foundation committees and National Research Program 71 on energy consumption management. At EPFL, she directs the HERUS laboratory which develops the Sustainability Solution Space methodology for urban assessment. The lab operates at the intersection of data science, environmental engineering, and social theory, maintaining strong field connections in Switzerland, Indonesia, and Germany for empirical validation of transition models.

Beat Hintermannمشاهده پروفایل

استاد

• Public Sector Economics
• Climate Policy
• Transportation Economics
• +۴ مورد دیگر

Prof. Dr. Beat Hintermann is a Professor of Public Finance at the University of Basel's Faculty of Business and Economics (WWZ). His research focuses on public sector economics with particular emphasis on climate policy and mobility behavior. Hintermann leads empirical research using GPS tracking data to study transportation choices and the effectiveness of pricing mechanisms to encourage sustainable mobility options. His research interests span several interconnected areas: public sector economics, climate policy design, transportation economics, and environmental economics. He investigates how pricing mechanisms can influence individual behavior to reduce environmental externalities, with special attention to sustainable mobility solutions like e-biking. His work often combines economic theory with rich empirical analysis of real-world data, particularly examining the intersection of environmental policy and individual decision-making. Hintermann's recent publications reveal a strong focus on empirical mobility studies, particularly through the MOBIS dataset that tracks mobility behavior in Switzerland. His research shows how transport pricing can effectively promote e-biking and reduce negative externalities. He has also conducted significant work on carbon pricing mechanisms, emissions trading systems, and the impacts of climate policies on economic behavior. His work during the pandemic period examining mobility changes provides valuable insights into how external shocks affect transportation choices. Hintermann's research methodology is characterized by rigorous empirical analysis, often employing field experiments and large-scale GPS tracking data to measure behavioral responses to policy interventions. His work on Pigovian transport pricing represents an important contribution to understanding how economic instruments can be designed to address environmental externalities in the transportation sector. As part of the University of Basel's Faculty of Business and Economics, Hintermann contributes to research centers focused on sustainable development and environmental economics. His work bridges academic research with practical policy applications, providing evidence-based insights for policymakers designing effective environmental and transportation policies.

Jan Dirk Wegnerمشاهده پروفایل

دانشیار

• Machine Learning
• Computer Vision
• Remote Sensing
• +۷ 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.

Julian Adamekمشاهده پروفایل

پژوهشگر

• Computational Cosmology
• Theoretical Cosmology
• Large-scale structure of the Universe
• +۳ مورد دیگر

Julian Adamek is a computational cosmologist and lead developer of gevolution , a general-relativistic N-body code for cosmological simulations. His work focuses on modeling relativistic effects in cosmic structure formation to better understand gravity’s role on large scales and dark energy. Research Interests: Computational Cosmology, Theoretical Cosmology, Large-scale structure of the Universe, Relativistic N-body simulations. Technical Leadership: Lead developer of gevolution , a public cosmological simulation code available via GitHub. Recent publications span diverse applications of deep learning in geospatial analytics, environmental monitoring, and computer vision, including phenology modeling, biomass mapping, conflict assessment, and 3D reconstruction from point clouds. Key Trends: Integration of AI/ML for environmental tasks, cross-domain applications (cosmology, ecology, forestry), and satellite data processing. Technical Focus: Transformer networks, diffusion models, super-resolution imaging, and ensemble learning for uncertainty quantification. Julian collaborates with researchers in cosmology and geospatial science, though specific students or awards are not mentioned in the provided texts.

• Cartography
• Geomatic Engineering
• Historical Map Analysis
• +۴ مورد دیگر

Dr. Yizi Chen is a Researcher affiliated with the Professorship for Cartography at ETH Zurich's Department of Civil, Environmental and Geomatic Engineering. Their work focuses on advancing cartographic techniques through AI-driven methods, historical map analysis, and geospatial technologies. Key contributions include automated map vectorization, semantic segmentation of historical maps, and integrating multimodal data for robotic systems. They have published extensively in top-tier journals and conferences, addressing challenges in deep learning applications for geomatic engineering. Education details are not explicitly provided in the text. Research interests include semantic segmentation, generative AI for cartography, and steganography in image translation. Notable publications span topics from eye-tracking segmentation to urban land use mapping, reflecting a strong interdisciplinary approach. Dr. Chen collaborates on projects involving historical map digitization and benchmarking datasets for computer vision tasks. No awards or grants are mentioned. Their work contributes to advancing geomatic engineering through innovative solutions in digital mapping and spatial data analysis.

Andreas U. Lanzمشاهده پروفایل

استاد

• Social Networks
• Influencer Marketing
• Digital Marketing
• +۳ مورد دیگر

Prof. Dr. Andreas U. Lanz is a marketing professor at the University of Basel since 2023, joining from HEC Paris. His research focuses on social networks and micro-influence strategies , with award-winning work on digital content dissemination. Education : Doctoral degree from the University of Mannheim Research Interests : Andreas Lanz specializes in influencer marketing , network dynamics , and digital consumer behavior . His work explores how micro-influencers drive content virality, status-based network seeding, and economic models for creator platforms. He co-chairs the Creator Economy Retreat and EMAC Creator Economy Special Interest Group . Recent Publications : His 2025 Management Science paper examines creator economy value chains, while 2024 Journal of Marketing studies optimize influencer targeting through triadic closure. Earlier works in MIS Quarterly and Journal of Marketing Research address social capital formation and adaptive modeling techniques. Scientific Awards : Outstanding Reviewer Award (Journal of Marketing, 2024) ISMS Early-Career Fellowship (2023) AMA Don Lehmann Award (2021, 2025) SAMS Rigour & Relevance Award (2020) EMAC/Sheth Foundation Dissertation Runner-up (2018) Academic Service : Editorial board member for Journal of Marketing and Marketing Science , organizer of the EMAC Job Market Simulation , and contributor to digital marketing education frameworks.

Giovanni Sansaviniمشاهده پروفایل

دانشیار

• Renewable Energy Systems
• Energy Infrastructure Resilience
• Power Systems Optimization
• +۳ مورد دیگر

Prof. Giovanni Sansavini is an Associate Professor in the Department of Mechanical and Process Engineering at ETH Zürich. His research focuses on energy systems resilience, renewable energy integration, and sustainable infrastructure design. He leads projects related to grid optimization, energy policy, and risk engineering, with a particular emphasis on decarbonization strategies for Switzerland and Europe. His work bridges theoretical modeling and practical implementation, addressing challenges such as power transmission equity, distributed energy resource management, and hydrogen storage integration. Recent projects include developing data-driven frameworks for grid reliability assessment and analyzing the socio-technical impacts of energy transitions. Prof. Sansavini collaborates with industry and policymakers to ensure research informs actionable solutions. His publications highlight interdisciplinary approaches to energy system design, emphasizing the trilemma of affordability, sustainability, and security.

Renata Borovica-Gajicمشاهده پروفایل

دانشیار

• Database Systems
• Machine Learning
• Artificial Intelligence
• +۱۲ مورد دیگر

Renata Borovica-Gajic is an Associate Professor in Data Analytics and an ARC DECRA Fellow at the School of Computing and Information Systems (CIS), University of Melbourne. She also serves as Associate Dean (Diversity and Inclusion) for the Faculty of Engineering and IT, demonstrating leadership in both research and academic community development. Her research lies at the intersection of database systems, machine learning, and artificial intelligence, with a vision of creating adaptive, self-driving database engines that optimize query execution in real-time. Her work spans learned indexes, query optimization, data quality, and data-driven traffic optimization, aiming to reduce costs and improve performance in data analytics. The recent publications reflect a strong trend toward integrating machine learning into core database operations—particularly through learned indexes, bandit-based tuning, and reinforcement learning for traffic systems. These works emphasize automation, provable guarantees, and real-time adaptation, showcasing a cohesive research agenda focused on intelligent, self-optimizing data systems. Her scientific excellence is recognized by numerous awards, including: L'Oréal-UNESCO for Women in Science Fellowship (2023) Victorian Young Tall Poppy (2024) Test of Time Award at SIGMOD 2022 Multiple Research and Teaching Excellence Awards from the University of Melbourne Google Research Inclusion Award (2021) She actively mentors PhD students and leads significant research projects funded by the Australian Research Council, Google, and Telstra. Her service includes roles as Associate Editor for SIGMOD Record, conference organization (e.g., aiDM, ADC, VLDB), and leadership in diversity and inclusion initiatives. She has also contributed to influential publications such as a chapter in the 7th edition of Database System Concepts . Her research lab focuses on AI-powered databases, traffic optimization via reinforcement learning, and self-healing data systems, positioning her at the forefront of next-generation data management.

• Geovisualization
• Visual Analytics
• Geomatics
• +۳ مورد دیگر

Prof. Dr. Susanne Bleisch is a faculty member at the FHNW University of Applied Sciences and Arts Northwestern Switzerland , affiliated with the School of Architecture, Civil Engineering and Geomatics and the Institute of Geomatics . She holds the academic rank of Professor specializing in Geovisualization and Visual Analytics and serves as Head of the MSE Master of Science FHNW in Engineering program. Her research focuses on the intersection of geospatial technologies and data visualization. She leads projects related to geovisualization, spatial data analysis, and visual analytics, with further details available on her personal website ( http://sbleis.ch/ ). Contact: Telephone +41 61 228 55 25 , Email susanne.bleisch@fhnw.ch . Office located at Hofackerstrasse 30, 4132 Muttenz, Switzerland, 10th floor east (report to secretariat: 10.O.11).

Alexandra Diehlمشاهده پروفایل

دانشگاهی

• Visual Analytics
• Data Science
• Environmental Sciences
• +۳ مورد دیگر

Alexandra Diehl is a Senior Researcher at the Visualization and MultiMedia Lab (VMML) at ETH Zurich. Her research focuses on Visual Analytics, Data Science, and Environmental Sciences, with an emphasis on visualization guidelines, citizen data integration, and weather event analysis. She leads the DSI Fellowship project on visual tools for severe weather communication (2020–2022) and co-leads an SNF SPIRIT grant on uncertainty visualization in weather forecasts. Her work bridges academic and industry applications, including projects like WeaVA and Hornero. Key research interests include visualization best practices (via VisGuides.org), societal impacts of visualization, and geospatial analysis. She actively contributes to IEEE VIS workshops, such as VisGuides 2022, and publishes extensively in journals like EuroVis. Her interdisciplinary projects address challenges in climate science, public safety, and multimedia analysis. Notable achievements include the DSI Fellowship and collaborative grants with Argentina. Her work emphasizes empirical methodologies, including grounded theory approaches in visualization research.

• Semantic Web and Ontology Engineering
• Agent-Based Modeling
• Knowledge Graphs
• +۴ مورد دیگر

Giovanna Di Marzo Serugendo is a researcher affiliated with the University of Geneva (Faculty of Social Sciences, Centre for Informatics) and the Institute of Information Service Science (ISS) . Her work spans semantic technologies, agent-based modeling, and sustainable systems. Research interests focus on Semantic knowledge graphs for regulatory compliance Ontology-driven resource management Self-organizing systems inspired by biological models AI applications in smart grids and urban mobility Digital agriculture platforms for smallholder farmers Recent publications highlight trends in ontology automation using LLMs, agent-based simulations for urban planning, and KG-enhanced compliance frameworks . She leads projects integrating digital twins with smart energy systems and develops bio-inspired coordination paradigms. Supervised works include 17 research projects in these domains. Current technical reports and conference papers explore cybersecurity-safety interdependencies in autonomous vehicles and decentralized event source detection in sensor networks.

Ben Jannمشاهده پروفایل

استاد

• Statistical Methods
• Data Visualization
• Social Inequality
• +۲ مورد دیگر

Ben Jann is a Professor and current Department Head at the University of Bern in the Department of Social Sciences . His methodological expertise spans statistical software development, decomposition analysis, and data visualization. Role: Department Head Institution: University of Bern Department: Department of Social Sciences Research Interests : Jann specializes in creating Stata modules for advanced statistical analysis, including geospatial mapping (geoplot), robust regression (robreg10), and inequality decomposition (oaxaca-blinder methods). His substantive work examines social inequality through economic and sociological lenses, analyzing how living costs and taxation systems impact income distribution in Switzerland. He also investigates educational transitions and gender disparities in STEM occupational choices through longitudinal studies like TREE2. Recent Publications Trends : Jann’s 15 most recent articles (2025-2023) demonstrate his focus on statistical software development for social science applications. Key contributions include methods for marginal odds ratios (2023), two-level model variance decomposition (2025), and list experiment analysis (2025). His empirical work connects statistical methodology to pressing social issues like gender wage gaps (2021) and teacher content knowledge in developing countries (2021).

Pascal A. Niklausمشاهده پروفایل

مدرس ارشد

• Plant and soil ecology
• Biogeochemical cycling
• Biodiversity and ecosystem functioning
• +۳ مورد دیگر

Pascal A. Niklaus is a Senior Lecturer and Adjunct Professor at the Department of Evolutionary Biology and Environmental Studies, University of Zurich. He leads the Global Change and Soil Ecology Group, focusing on plant-soil interactions, biogeochemical cycles, and biodiversity-ecosystem functioning relationships. His research integrates field experiments, statistical analysis, and microbial ecology to address global change impacts on ecosystems. Education: PhD in Botany, University of Basel (1997-2000) Postdoctoral positions at ETH Zurich and University of Basel National Science Foundation Postdoctoral Fellowship (2001-2002) Research Interests: His work explores how plant diversity influences ecosystem processes, particularly methane and nitrous oxide dynamics in soils. He investigates microbial community responses to environmental changes and the role of biodiversity in maintaining ecosystem resilience. His studies span terrestrial ecosystems, including forests and grasslands, using experimental approaches and advanced analytical techniques. Articles Trends: Recent work emphasizes climate impacts on tree traits, microbial diversity effects on carbon cycling, and the role of plant-soil interactions in mediating global change effects. Key themes include biodiversity-productivity relationships and the ecological consequences of species loss. Awards: No specific scientific awards listed, but recognized for editorial roles in Oecologia and Scientific Reports . Grants & Grants: Secured funding from NSF, Swiss National Science Foundation, and the Treubel Foundation. Current projects address soil ecology under global change and microbial community dynamics. Labs/Teams: Head of the Global Change and Soil Ecology Group at UZH, collaborating with international networks on biodiversity and ecosystem studies.

• Artificial Intelligence
• Explainable AI
• Computational Argumentation
• +۳ مورد دیگر

Antonio Rago is a Researcher in the Department of Computing at Imperial College London. He specializes in Explainable Artificial Intelligence (XAI) with a focus on computational argumentation frameworks and their integration with data-driven AI systems. His work bridges symbolic AI and machine learning to enhance transparency and societal benefit in AI applications. Education: PhD in Computing (2019) from Imperial College London, supervised by Prof. Francesca Toni and Dr. Marco Aurisicchio, with an MEng in Automotive Engineering from Loughborough University (2012). Research: Explores explainable AI through argumentation semantics, counterfactual reasoning, and hybrid symbolic-statistical methods. Application domains include e-learning, Formula One race strategy, healthcare, and mechanical engineering. Workshops: Organizer of international workshops like Arg&App 2025 and ArgXAI-25, and co-organizer of previous events at KR, ECAI, and COMMA conferences. Publications: Active in top AI venues (KR, IJCAI, AAAI, AAMAS) with over 25 publications since 2016, emphasizing argumentation-based explanations and robust AI systems. Industry Experience: Former Race Strategy Engineer at Mercedes AMG Petronas F1 Team (2012-2014) and Project Manager at Green Lifting Ltd. (2014-2017).

Renato Pajarolaمشاهده پروفایل

استاد

• Computer Graphics
• Scientific Visualization
• 3D Modeling
• +۵ مورد دیگر

Prof. Dr. Renato Pajarola is the Head of the Visualization and MultiMedia Lab at the Department of Informatics, University of Zurich. His research focuses on computer graphics, scientific visualization, and geometric processing, with applications in 3D scanning, point cloud analysis, and real-time rendering. He leads a team developing advanced visualization techniques for high-dimensional data, parallel rendering frameworks, and interactive systems for complex datasets. Key research areas include: 3D reconstruction of indoor environments Tensor approximation for volume visualization Interactive ray tracing and point cloud processing Parallel rendering frameworks (e.g., Equalizer) Scientific computing and sensitivity analysis His recent publications emphasize: High-dimensional data exploration using tensor methods Efficient rendering techniques for large-scale point clouds Integration of citizen-reported weather data for environmental analysis Prof. Pajarola’s lab collaborates on projects like VIAN (visual annotation tool for film analysis) and Terrender (web-based terrain visualization). His Erdős number is 3, reflecting interdisciplinary research connections in mathematics and computer science.