جست‌وجوی استاد و پژوهشگر

Olga Sorkine-Hornungمشاهده پروفایل

استاد

• Digital Content Creation
• Geometry Processing
• Shape Representation and Editing
• +۵ مورد دیگر

Olga Sorkine-Hornung is a Professor of Computer Science at ETH Zurich and head of the Institute of Visual Computing. She leads the Interactive Geometry Lab, focusing on theoretical and practical advancements in digital content creation, geometry processing, and shape modeling. Current position: ETH Zurich, Department of Computer Science Previous roles: Courant Institute (NYU), Technical University of Berlin Education: BSc and PhD from Tel Aviv University, postdoc at TU Berlin Her research spans shape representation, digital fabrication, computer animation, and fundamental geometry processing. Key contributions include Laplacian surface editing, as-rigid-as-possible deformation, and generalized winding numbers. She works on applications in VR, AR, and autonomous systems. Awards include Test of Time Awards (2024), ACM Fellow (2020), ERC Consolidator Grant (2020), and EUROGRAPHICS Young Researcher Award (2008). She has supervised numerous students and co-developed software libraries like libigl and Instant Meshes . Co-chair roles for SIGGRAPH, Eurographics, and Pacific Graphics Editorial board member for ACM Transactions on Graphics and other journals Keynote speaker at VMV, CVPR, and SIAM conferences Her work bridges mathematical rigor with practical implementation, advancing computer graphics and geometry processing through intuitive algorithms that maintain surface detail while enabling efficient computation.

Yves Marc Räthمشاهده پروفایل

پژوهشگر

• Urban Morphology
• Settlement Development
• Geospatial Analysis
• +۳ مورد دیگر

Yves Marc Räth is a Ph.D. researcher at the ETH Zürich within the Department of Civil, Environmental, and Geomatic Engineering (D-BAUG). His work intersects urban morphology, historical settlement analysis, and network modeling. Education: MSc in Spatial Development and Infrastructure Systems (2018-2020), BSc in Geography (2015-2018) at University of Zurich Research focuses on urbanization patterns , settlement network evolution , and geospatial time series analysis . Key projects include the EMPHASES study on socio-ecological systems and HistoRiCH research on historical river landscapes. Recent publications analyze settlement archetypes through ResearchGate projects, with a 2025 Cities journal article identifying five distinct urban development pathways on the Swiss Plateau since 1899. His 2023 Scientific Reports study examines morphological homogeneity in small settlements near urban centers. Current affiliations include: Ph.D. Researcher at Institute for Spatial and Landscape Development Visiting Scholar at Urban Systems Lab, New York City (2024) Contributor to Swiss transport planning at INFRAS and EBP Technical expertise spans: Historical map digitization Building footprint analysis Commuter flow modeling Predictive urban archetypes

Damian Nale Dailisanمشاهده پروفایل

مدرس

• Computational Social Science
• Machine Learning
• Multi-Agent Systems
• +۳ مورد دیگر

Dr. Damian Nale Dailisan is a Lecturer in the Department of Humanities, Social and Political Sciences at ETH Zürich, affiliated with the Computational Social Science group. He holds a Ph.D. in Physics from the University of the Philippines, specializing in traffic modeling and machine learning applications. His research focuses on multi-agent systems, particularly in transportation and urban systems. He has held postdoctoral roles and contributed to projects like the ACCeSs@AIM lab. His work bridges computational methods with real-world challenges, including traffic control optimization, AI-driven decision-making, and smart city infrastructure. Notable projects include FAIRLANE for priority lane management and studies on democratizing traffic control systems. Dailisan’s publications span journals like Transportation Research Part C and IEEE Access, addressing topics such as reinforcement learning in traffic signals and ethical AI frameworks. He has presented at workshops like 'Back to the Future' at ETH Zurich and collaborates with interdisciplinary teams to enhance urban mobility solutions. His technical expertise includes Python, network analysis, and agent-based modeling, with contributions to open-source tools for earthquake networks and social systems analysis.

Nicolas Zuffereyمشاهده پروفایل

استاد

• Operations Management
• Supply Chain Management
• Optimization
• +۴ مورد دیگر

Nicolas Zufferey is a Full Professor of Operations Management at the University of Geneva, Switzerland, where he has served since 2008. He leads research in optimization methods for complex systems, focusing on applications in supply chain management, production planning, inventory control, and transportation logistics. His affiliations include the Research Institute of Management and collaborations with CIRRELT (Transportation & Logistics) and GERAD (Decision Analysis). Education: PhD in Operations Research (EPFL, 2002), MSc/BSc in Mathematics (EPFL) Prior Experience: Postdoc at University of Calgary (2003–2004), Assistant Professor at Université Laval (2004–2007) Research Interests: His work emphasizes developing advanced metaheuristics (e.g., VNS, Tabu Search, PSO) for challenging optimization problems. Key domains include: Multi-objective scheduling with resource constraints Inventory deployment under uncertainty Network design for supply chains and transportation systems Publications: Over 150 peer-reviewed articles across journals like European Journal of Operational Research , Transportation Research , and INFORMS Journal on Computing . Recent work addresses electric vehicle routing, drone integration in delivery systems, and robust decision-making under uncertainty. Collaborations: Engaged with 35+ universities and 27 private companies globally. Active in applying operations research to industrial problems (e.g., Swiss railways, luxury watch production, pharmaceutical networks).

Martin Raubalمشاهده پروفایل

استاد

• Spatial Decision-Making
• Mobile Geographic Information Systems (GIS)
• Location-Based Services (LBS)
• +۷ مورد دیگر

Prof. Dr. Martin Raubal is a Full Professor at the Institute for Cartography and Geoinformation, Department of Civil, Environmental and Geomatic Engineering, ETH Zurich. He leads research on spatial decision-making, mobile GIS, and location-based services, with applications in transportation, energy, and aviation. His work integrates cognitive engineering and eye-tracking to analyze human mobility and interaction with geospatial systems. Doctorate in Geoinformation (with distinction), Vienna University of Technology (2001) MS in Spatial Information Science and Engineering, University of Maine (1997) Dipl.-Ing. in Surveying Engineering and Geoinformation, Vienna University of Technology (1998) His research focuses on spatiotemporal human mobility, cognitive models for GIS, and sustainable urban systems. Key projects include the Digital Underground initiative at the Singapore-ETH Centre and the Empirical Use and Impact Analysis of Mobility-as-a-Service (EIM). Awards include the UV-Helava Prize and multiple best paper recognitions. Recent publications emphasize 3D spatial analysis, AI-driven geospatial tools, and causal inference in mobility modeling. Collaborations span institutions like Lufthansa Systems, SBB, and ETH-IVT. His lab investigates applications such as electric vehicle charging networks, bikeability indexes, and augmented reality in transportation planning.

• Distributed Software Systems
• Network Function Virtualization
• Formal Verification
• +۳ مورد دیگر

Patrick Eugster is a full professor at the Università della Svizzera italiana (USI) and leads the Software Systems (SWYSTEMS) group within the Computer Systems Institute . He has held academic positions at Purdue University, TU Darmstadt, and MIT as a visiting faculty. His research focuses on distributed software systems , addressing challenges in consistency, efficiency, and security in decentralized environments. Current affiliation: USI Faculty of Informatics Prior affiliations: Purdue University (2005-2016), TU Darmstadt (2014-2017), MIT (2012/2013) Research Interests Distributed Systems : Investigating reliable failure detection, deterministic data paths for 6G, and hybrid synchronous/asynchronous architectures. Network Innovation : Optimizing TCAM encoding, analyzing microbursts, and developing quantum network protocols. Security & Verification : Creating confidentiality-preserving mechanisms and formal verification approaches for distributed software. Scientific Contributions 2025: Best paper at TACAS on Horn clause validation 2025: IFIP Jean-Claude Laprie Award for dependable computing 2024: Key papers at IEEE Network, ACM PLDI, and IEEE INFOCOM Funding & Collaborations Swiss National Science Foundation grants #200021_197353 and #200021_192121 EU Horizon Europe MSCA staff exchange project CloudStars Industry partners: Cisco, Amazon AWS, Facebook Research, SAP, Northrop Grumman Cybersecurity Research Consortium Labs & Teams Directs the SWYSTEMS group, which includes postdocs like Sina Darabi and Shamiek Mangipudi, PhD students such as Anita Buckley and Jérôme Graf, and alumni who have become faculty at institutions like Télécom Paris and University of Southern California.

Olivier Verscheureمشاهده پروفایل

استاد مدعو

• Stream and Big Data Mining
• Geospatial Analysis
• Large-scale Data Management
• +۴ مورد دیگر

Olivier Verscheure serves as the Executive Director of the Swiss Data Science Center (SDSC), a national R&D center organizationally hosted by both École Polytechnique Fédérale de Lausanne (EPFL) and ETH Zurich. He also holds multiple Adjunct Professor appointments at EPFL, specifically within the School of Computer and Communication Sciences (SIN and SSC) and the School of Engineering (SEL). His educational background includes: Ph.D. in Computer Science from École Polytechnique Fédérale de Lausanne (EPFL), June 1999 Verscheure's research focuses on the intersection of data science and real-world applications. His work centers on stream and big data mining, geospatial analysis, and large-scale data management. These technical capabilities are applied across diverse domains including personalized health and medicine, Intelligent Transportation Systems, telecommunications, smart building technologies, Smart Grid infrastructure, healthcare analytics, and waste water management systems. His approach emphasizes creating practical data science solutions that address complex challenges in these sectors while considering the constraints of real-world deployment. An analysis of his recent publication record reveals a strong focus on real-time data processing and analytics, particularly for transportation and urban systems. His work frequently addresses challenges in handling massive time series data, developing efficient architectures for low-latency analytics, and creating practical applications for smart city infrastructure. There's a clear progression from theoretical data science contributions to production-ready systems that can process billions of data points daily, demonstrating his ability to bridge research and practical implementation. His notable achievements include: Two IBM Outstanding Technical Achievement Awards Best Paper Award for his research Student Best Paper Award Verscheure has substantial experience in research leadership and mentoring. During his tenure at IBM, he managed the Exploratory Stream Analytics research group and led a technical and management team of approximately 40 people at the IBM Research lab in Ireland. He has served on PhD committees at major universities and published nearly 100 research papers that have garnered over 2,400 citations. His work has resulted in more than 40 US and international patents, demonstrating both academic and practical impact. As Executive Director of the Swiss Data Science Center, Verscheure oversees a distributed multi-disciplinary team working across domains including personalized health, transportation, earth and environmental science, social science and digital humanities, and economics. The center aims to federate data providers, data and computer scientists, and subject-matter experts around a cutting-edge analytics platform while addressing security and privacy issues. Under his leadership, the SDSC develops embedded data science support, offers end-to-end data science services, and fosters a community to share tools and knowledge in data science.

• Autonomous Driving
• Computer Vision
• Robotics
• +۵ مورد دیگر

Holger Caesar is a tenured Assistant Professor at Delft University of Technology (TU Delft) in the Intelligent Vehicles Lab . He leads research on scalable approaches for autonomous vehicle perception, prediction, and data annotation, with a focus on sensor fusion, domain adaptation, and minimal supervision. His work has been cited over 15,000 times. Education PhD in Computer Vision, University of Edinburgh Prior studies at KIT Karlsruhe, EPF Lausanne, and ETH Zurich Research Interests span autonomous driving perception, weakly supervised learning, novel view synthesis (NeRFs), diffusion models, and collaborative perception. He emphasizes reducing reliance on manual annotations through active learning and partial labeling techniques. Recent Publications include work on 4D Gaussian Splatting, camera-radar fusion, open-set scene graph generation, and safety benchmarking. These reflect trends toward multi-modal perception, robust sensor fusion, and foundation models for scalable autonomous systems. Scientific Awards ELLIS Europe Scholar (2024) TU Delft Cohesion Grant (100k EUR, 2024) Climate Action Grant (30k EUR, 2024) TKI High Tech Systems Grant (502k EUR, 2022) AiNed XS Grant (80k EUR, 2023) Argoverse Scene Flow Challenge Winner (unsupervised track, 2024) Advising & Grants include EU Horizon funding for the MOSAIC project (1 PhD and 1 Postdoc, 2024), EU KDT Cynergie4MIE grant (450k EUR, 2024), and industrial collaborations with Bosch, Motional, and partners across Europe. Labs & Teams include the Intelligent Vehicles Lab at TU Delft and founding roles in Motional's Data Annotation, Autolabeling, and Data Mining teams. He co-organizes workshops at ICCV, CVPR, and NCCV, and leads the ELLIS Delft Unit seminar series.

Antonio Carzanigaمشاهده پروفایل

استاد

• Distributed Systems
• Software Engineering
• Content-Based Networking
• +۷ مورد دیگر

Antonio Carzaniga is a Full Professor and founding member of the Faculty of Informatics at Università della Svizzera italiana (USI), where he has been active since 2004. Previously, he served as an Assistant Research Professor at the University of Colorado at Boulder from 2001 to 2007. He holds a Ph.D. in Computer Science and a Bachelor’s degree in Electronic Engineering from Politecnico di Milano. Full Professor, Faculty of Informatics, Università della Svizzera italiana (2004–Present) Assistant Research Professor, Department of Computer Science, University of Colorado at Boulder (2001–2007) Ph.D. in Computer Science, Politecnico di Milano Bachelor’s in Electronic Engineering, Politecnico di Milano His research spans distributed systems and software engineering, with a strong focus on content-based addressing networks, publish/subscribe systems, middleware, software fault tolerance, and verification. He has pioneered work in information-centric networking and developed the Siena project, a scalable publish/subscribe service. His recent work extends into programmable networks, GPU-accelerated matching, and performance annotations for cloud systems. The 15 most recent publications highlight a consistent trajectory in scalable, high-performance networking and adaptive software systems. Key themes include content-based communication, packet subscriptions, information-centric networking, and leveraging redundancy for fault tolerance and testing. His work bridges theoretical foundations with practical implementations, often involving system-level software and performance evaluation. Best Paper Award, ACM SIGCOMM Workshop on Information-Centric Networking (ICN'13) Carzaniga has advised multiple graduate students, including Michele Papalini, Koorosh Khazaei, and Daniele Rogora, and has collaborated on funded research projects in distributed systems and networking. He has contributed to software development through projects like the Siena Fast Forwarding engine and the Synthetic Workload Generator. His service includes organizing workshops and contributing to major conferences in software engineering and computer systems. He leads research initiatives such as Siena and Content-Based Networking, focusing on scalable, decentralized communication infrastructures. His lab has developed key tools for evaluating publish/subscribe performance and implementing high-speed forwarding algorithms.

Rolf Steineggerمشاهده پروفایل

مدرس

• Systems Engineering
• Project Management
• Aviation
• +۷ مورد دیگر

Rolf Steinegger is a Lecturer at the Zurich University of Applied Sciences (ZHAW) , affiliated with the School of Engineering and the Centre for Aviation . His work focuses on Project Management , Systems Engineering , and Railway Network Planning , with a career spanning academia and industry. He contributes to aviation research, transportation systems, and educational methodologies. Education : Executive Master in Business Engineering (Kaleidos, 2003-2005), Master of Advanced Studies in Higher and Secondary Education (FITZ, 1994-1996), MSc in Civil Engineering (ETH Zurich, 1989-1993) His research bridges aviation and railway engineering , emphasizing decision-making frameworks , lifecycle analysis , and optimization models . Recent publications explore fuel economy in aircraft , symmetry in wings and sails , and cash flow cycles in small businesses , reflecting interdisciplinary applications of systems thinking. Notable publications include the Beer Distribution Game simulations and analyses of slab track technology in railways. While no formal scientific awards are documented, his work impacts both academic curricula and industrial practices.

Michail Makridisمشاهده پروفایل

مدرس ارشد

• Transportation Engineering
• Traffic Flow Modeling and Simulation
• Intelligent Transportation Systems
• +۷ مورد دیگر

Dr. Michail Makridis is a Senior Lecturer at ETH Zürich's Department of Civil, Environmental and Geomatic Engineering, where he leads the Road Traffic Technology Group. He serves as the main responsible lecturer for Microscopic Modelling and Simulation of Traffic Operations and has taught Traffic Engineering courses. His work focuses on developing innovative approaches to transportation challenges with a particular emphasis on system resilience and antifragility. Dr. Makridis's research interests span multiple dimensions of modern transportation systems. His primary focus areas include traffic flow modeling and simulation, intelligent transportation systems, and traffic estimation and control. He has made significant contributions to understanding vehicle dynamics and driver behavior simulation, with particular attention to vehicle energy demand and emissions. His work on antifragile transportation systems represents a cutting-edge approach to designing networks that improve performance under disruption. His recent publications demonstrate a strong trend toward integrating machine learning with traditional transportation engineering. The research shows increasing focus on antifragility concepts in traffic networks, congestion-aware prediction models, and multimodal transportation solutions that balance the needs of different road users. His work spans theoretical frameworks and practical applications, with several publications addressing real-world challenges in urban mobility. MFC and Battery Consumption Model (April 2022) Simsub Best Simulation Development Paper Award (TRB 2020) for Enhanced MFC: Introducing dynamics of electrified vehicles for free flow microsimulation modeling Dr. Makridis leads multiple significant research projects including AntifragiCity, which aims to revolutionize how urban mobility systems respond to disruptions, and ANTIGONES, focusing on designing anti-fragile large-scale traffic frameworks. His work on ASTRA BGT examines the impact of autonomous vehicles on tunnel safety and efficiency, while BikeZ develops models for mass cycling as a service. He also contributes to OptFlow, which focuses on travel-time estimation using FLIR camera sensors. His research has practical applications in improving urban transportation resilience and efficiency.

Kenan Zhangمشاهده پروفایل

استادیار

• Urban Transportation Systems
• Operations Research
• Transportation Engineering
• +۶ مورد دیگر

Dr. Kenan Zhang is a Tenure Track Assistant Professor at EPFL's School of Architecture, Civil and Environmental Engineering, leading the Laboratory for Human-Oriented Mobility Eco-system (HOMES). She holds dual roles in teaching Civil Engineering and contributes to the EDCE and SGC programs. Her research focuses on mathematical modeling, optimization, and operations management of urban transportation systems, with emphasis on emerging mobility services and technologies. Education: BSc in Civil Engineering, Tsinghua University MSc in Architecture-Engineering-Construction Management (AECM), Carnegie Mellon University PhD in Civil Engineering (Transportation System Analysis & Planning) and second MSc in Statistics, Northwestern University Postdoctoral Researcher at ETH Zurich Research Interests: Urban transportation systems, optimization algorithms, sustainable mobility, traffic flow theory, and emerging technologies like autonomous vehicles and MaaS platforms. Her work integrates data-driven approaches with theoretical models to address real-world challenges in urban mobility. Awards & Recognition: CEE Rising Star Award COTA Best Dissertation Award TRB Committee Membership (ACP 50) Editorial Advisory Board, Transportation Research Part C Teaching & Advising: Supervises PhD students Liu Xuhang & Ma Xinyu. Teaches courses on urban transport systems, transportation network modeling, and seminars in civil/environmental engineering. Active in curriculum development for interdisciplinary mobility studies. Labs & Collaborations: Directs HOMES Lab exploring human-centric mobility ecosystems. Engages in international collaborations and policy analysis for sustainable transport solutions.

• Operations Research
• Public Transport Optimization
• Urban Logistics
• +۳ مورد دیگر

Stephan Bütikofer is a researcher at the Zurich University of Applied Sciences (ZHAW), School of Engineering, specializing in operations research and transportation systems. He focuses on public transport optimization, railway timetabling, urban logistics, and network modeling. His work integrates customer behavior and infrastructure constraints into scheduling algorithms. Current Projects: Smart UMH (urban multihub logistics), Customer-oriented Traffic Management Systems, and automated timetable planning. Research Themes: Mesoscopic infrastructure modeling, periodic timetabling with PESP/FPESP, energy optimization in vessel operations, and ULD stock allocation in air transport. Recent Publications: Address periodic timetabling with travel chain integration, maintenance scheduling stability, and graph contraction for railway optimization. Keywords: Operations Research, Public Transport, Network Analysis. Collaborations: Regularly works with ETH Zurich, RWTH Aachen University, and Swiss transport stakeholders like SBB and Swiss International Air Lines.

Thomas Ottمشاهده پروفایل

استاد

• Bio-inspired Computing
• Applied Neuroinformatics
• Machine Learning
• +۷ مورد دیگر

Prof. Thomas Ott is the Director of the Institute of Computational Life Sciences at the ZHAW School of Life Sciences and Facility Management. His research focuses on Bio-inspired Computing, Applied Neuroinformatics (including Pattern Recognition and Machine Learning), Modelling of Complex Systems, and Forecast Methodologies for Traffic/Logistics. He leads projects in AI-driven health systems, ecological sustainability, and industrial analytics. Ott has collaborated on over 50 peer-reviewed publications, with recent work emphasizing neuromorphic computing, predictive analytics in healthcare, and chaos-based network analysis. Education & Affiliations: His academic background includes prior roles at institutions like the University of Zurich and ETH Zurich. He serves on boards of Prognosix AG, Life Sciences Zurich Business Network, and Biotechnet Switzerland. Research Interests: Ott’s work bridges computational methods with real-world applications, such as AI for agriculture (fruit classification), predictive maintenance in healthcare systems, and traffic flow optimization. His team develops hybrid human-machine learning frameworks for complex decision-making processes. Projects & Grants: Key projects include 'Shapescience – AI for Morphologically-Based Fruit Recognition', 'Predictive Analytics for Hospital Supply Chains', and 'Smartstones - AI for Plant Breeding'. These reflect his focus on applied AI solutions for industry and public health. Labs & Teams: He oversees interdisciplinary teams at ZHAW’s Computational Life Sciences lab, integrating computer science, biology, and engineering for innovative problem-solving.

• Data-Driven Service Engineering
• Smart Services
• Industrial Services
• +۳ مورد دیگر

Dr. Jürg Meierhofer is a Senior Lecturer at the ZHAW School of Engineering's Institute of Data Analysis and Process Design. He specializes in Data-Driven Service Engineering, Smart Services, and Circular Economy applications. He holds a PhD (Dr. sc. ETH) from ETH Zurich and has extensive industry experience, including roles as Head of Department at Swisscom and La Mobilière. His research focuses on optimizing service value creation through data science, digital twins, and large language models (LLMs). He leads educational programs like the CAS Smart Services and MAS Industrie 4.0, emphasizing practical industry relevance. Education: Dr. sc. techn. ETH (PhD) in Electrical Engineering, ETH Zurich (2000) Dipl. NDS ETH in Information Technology, ETH Zurich (2000) Executive MBA in ICT Management, University of Fribourg (2005) Research Interests: Meierhofer's work addresses data-driven service innovation, smart service ecosystems, and value optimization in industrial contexts. Recent projects include leveraging LLMs for automation in technical customer service and developing quantitative models for sustainable smart services. Key Projects: Data Act Pioneer: Enabling circular economy through data IoT Sustainability Lab and Sustainable Mobility Lab Co-leader of BePro-CEND (Circular Economy) and Complexity 4.0 initiatives Awards: Best Paper Awards at Spring Servitization Conference (2024), Swiss Data Science Conference (2022), and Naples Forum on Service (2021) Grants & Advisory Roles: Active in the Data Innovation Alliance and Swiss Service Verband's scientific advisory board. Co-edited major conference proceedings like the Smart Services Summit series. Labs/Teams: Leads the Service Engineering Lab in ZHAW's bachelor's program and collaborates on interdisciplinary projects involving digital twins and data-sharing frameworks for SMEs.