جست‌وجوی استاد و پژوهشگر

Laura Grigoriمشاهده پروفایل

استاد

• High-Performance Scientific Computing
• Numerical Linear Algebra
• Communication-Avoiding Algorithms
• +۶ مورد دیگر

Laura Grigori is a Professor of Applied and Computational Mathematics at EPFL and Head of the Laboratory for Simulation and Modeling at the Paul Scherrer Institute (PSI), Switzerland. She holds a Ph.D. in Computer Science from Université Henri Poincaré (2001) and has been a leading figure in high-performance numerical algorithms and communication-avoiding methods. Her research focuses on numerical linear algebra, randomized algorithms, and scalable scientific computing for applications in astrophysics, molecular simulations, and exascale systems. Affiliations: EPFL Chair of High-Performance Numerical Algorithms & Simulation; Head, PSI Laboratory for Simulation and Modeling. Education: Ph.D. in Computer Science, Université Henri Poincaré (2001); Postdoctoral Researcher, UC Berkeley/LBNL (2001–2003); Senior Researcher at INRIA (2004–2023). Research Interests: Communication-avoiding algorithms, randomized numerical linear algebra, parallel preconditioners, tensor computations, and exascale computing challenges. Awards: SIAM Fellow (2020), ERC Synergy Grant (2018), SIAM Supercomputing Career Prize (2024), and Best Paper Awards (2016, 2023). Grants & Leadership: PI of the ERC Synergy Project EMC² (Extreme-scale Computational Chemistry); Chair of PRACE Scientific Steering Committee (2021–2022); SIAM SIAG Supercomputing Chair (2016–2017). Labs/Teams: Alpines Group (INRIA/Sorbonne University), EMC² Collaboration (Cancès, Maday, Piquemal).

Rizlan Bernier-Latmaniمشاهده پروفایل

استاد

• Geomicrobiology
• Environmental Microbiology
• Bioremediation
• +۳ مورد دیگر

Professor Rizlan Bernier-Latmani is a Full Professor at École Polytechnique Fédérale de Lausanne (EPFL) within the School of Architecture, Civil and Environmental Engineering, Department of Environmental Sciences and Engineering. She leads the Environmental Microbiology Laboratory (EML), focusing on geomicrobiology, bioremediation, and isotope geochemistry. Her research explores microbial processes in extreme environments, including radioactive waste repositories and contaminated aquifers. She holds academic roles in teaching and curriculum design, and serves on committees such as the Diversity Office at ENAC and the EPFL Academic Evaluation Committee. Her work integrates molecular biology, geochemistry, and field studies to address environmental challenges. Research interests emphasize microbial redox cycling, uranium transformation mechanisms, and environmental microbiology applications. She has supervised numerous doctoral theses, advancing understanding of microbial biogeochemistry and its impact on ecosystems. Her lab develops novel methods for microbial isolation and bioremediation strategies, with recent contributions to studies on clay barriers, radioactive waste management, and microbial interactions in subsurface environments. Publications highlight advancements in uranium oxide dynamics, microbial adaptation in confined spaces, and the role of microbial communities in geochemical cycling. Her interdisciplinary approach bridges fundamental science with practical solutions for environmental sustainability.

Nicolas Boumalمشاهده پروفایل

استادیار

• Optimization
• Non-convex Optimization
• Riemannian Manifolds
• +۵ مورد دیگر

Nicolas Boumal is an Assistant Professor in Mathematics at EPFL, Switzerland, holding dual affiliations in the Continuous Optimization Chair (OPTIM) within the Institute of Mathematics (MATH) and the SMA Education Group. He leads research in optimization on Riemannian manifolds, non-convex optimization, and statistical estimation. His work bridges geometry, numerical analysis, and applications in cryo-electron microscopy and synchronization problems. Education: PhD in Mathematical Engineering from UCLouvain (2014), postdoctoral research at Inria Paris and Princeton University. Prior to EPFL, he was an Instructor and Assistant Professor at Princeton’s Mathematics Department. Research Interests : Non-convex optimization landscapes, optimization on manifolds, low-rank matrix optimization, synchronization, phase retrieval, and computational methods in cryo-EM. His ERC Starting Grant (GEOSYM, 2022–2027) focuses on geometric and symmetric optimization techniques. Grants & Awards : ERC Starting Grant (2021), SIAM Optimization Prize (2018 for student co-author), and several conference best paper awards. Teaching : Courses include Continuous Optimization (MATH-329), Algebra Linéaire (MATH-111), and graduate-level Optimization on Manifolds (MATH-512). He authored the textbook An Introduction to Optimization on Smooth Manifolds (Cambridge University Press, 2023). Labs & Teams : Heads the OPTIM lab at EPFL, collaborating with global researchers in optimization and applications. His group develops the Manopt toolbox for manifold optimization.

Andrei Atanovمشاهده پروفایل

پژوهشگر

• Computer Vision
• Artificial Intelligence
• Machine Learning
• +۳ مورد دیگر

Andrei Atanov is a Researcher at the Laboratoire d'intelligence et d'apprentissage visuels (VILAB) within the School of Computer and Communication Sciences at École Polytechnique Fédérale de Lausanne (EPFL) . His research focuses on advanced topics in artificial intelligence, computer vision, and machine learning, with particular emphasis on multimodal learning, vision-language models, and robust generalization. He is affiliated with the Department of Computer Science and contributes to projects exploring innovative solutions for vision tasks using computationally designed sensors and diffusion models. His work often bridges theoretical advancements with practical applications in robotics and generative systems. Key research areas include developing large vision-language models, optimizing vision algorithms for low-sensor environments, and enhancing model robustness through diversification strategies. His publications span topics from 3D data augmentation to uncertainty estimation in deep learning, reflecting a broad yet technically deep expertise in AI fundamentals and applications.

• Model Predictive Control
• Nonlinear Systems Control
• Robust Control
• +۳ مورد دیگر

Dr. Johannes Köhler is a Lecturer at the Department of Mechanical and Process Engineering at ETH Zürich, Switzerland. His research focuses on advanced control systems, particularly model predictive control (MPC), robust control of nonlinear systems, and data-driven control strategies. He holds a Master's degree in Engineering Cybernetics from the University of Stuttgart (2017) and a Ph.D. in Mechanical Engineering (2021), for which he received the 2021 European Systems & Control PhD Award. His work emphasizes safety, optimization, and adaptability in control systems, with applications ranging from autonomous navigation to energy-efficient building systems. Key academic achievements include the 2022 ETH Zurich Career Seed Award for his work on data-driven predictive control, and the 2020 Best Publication Award at the University of Stuttgart for applying MPC to combat the COVID-19 outbreak. He has authored over 60 peer-reviewed articles, with recent contributions in stochastic MPC, robust nonlinear control, and safety-aware exploration strategies. Education: Ph.D. in Mechanical Engineering, University of Stuttgart (2021) Master of Engineering Cybernetics, University of Stuttgart (2017) His research group at ETH Zürich develops algorithms for real-time control of complex systems, with a focus on embedded MPC for robotics and energy systems. Current projects include safe autonomous navigation, adaptive control under uncertainty, and data-driven methods for nonlinear systems.

• Parallel Computing
• High-Performance Computing
• Computer Science
• +۳ مورد دیگر

Dr. Nabil F. T. Abubaker holds the position of Staff of Professorship for Scalable Parallel Computing at ETH Zürich. He is affiliated with the Department of Scalable Parallel Computing, contributing to research and academic activities within this field. His work is centered on advancing computational methods and systems, particularly in parallel and high-performance computing domains.

• Reinforcement Learning
• Machine Learning
• Artificial Intelligence
• +۳ مورد دیگر

Marco Bagatella is a doctoral researcher at the Institute of Machine Learning (ETH Zürich), focusing on advanced machine learning and artificial intelligence research. His work spans reinforcement learning, behavioral cloning, and causal inference, often addressing challenges in generalization, exploration, and policy adaptation. Contact: marco.bagatella@inf.ethz.ch Specializes in Reinforcement Learning (including offline and multi-task settings) Expertise in causal modeling and counterfactual data augmentation Investigates graph neural networks for biological systems Active contributor to AI/ML publications (15+ recent works) His research explores problem space transformations, optimal transport for zero-shot imitation learning, and temporal logic-based exploration. Current projects focus on improving policy robustness and adaptability across diverse domains. Scientific awards: No formal honors listed yet. Collaborates with ETH Zurich's machine learning teams on cutting-edge algorithm development and theoretical analysis.

• Robotics
• Computer Graphics
• Control Systems
• +۳ مورد دیگر

Prof. Stelian Coros is an Associate Professor at the Department of Computer Science, ETH Zürich, and Head of the Institute for Intelligent Interactive Systems. His research focuses on robotics, computational design, and control systems, with applications in robotic manipulation, simulation, and autonomous systems. His work integrates principles from computer science, mechanical engineering, and artificial intelligence to advance the capabilities of robots in real-world environments.

• Computational Robotics
• Artificial Intelligence
• Path Planning
• +۳ مورد دیگر

Valentin Hartmann is affiliated with the Computational Robotics department at ETH Zürich. His research focuses on advanced robotics, motion planning, and multi-agent systems. He develops algorithms for optimal path planning, task allocation, and autonomous decision-making in complex robotic environments. His work addresses challenges in multi-robot coordination, manipulation, and scalable solutions for construction and industrial automation. Key contributions include benchmark datasets for multi-agent planning and novel methods for efficient motion and task scheduling. Recent research highlights include advancements in kinodynamic motion planning (e.g., iDb-A*, iDb-RRT), optimization of multi-arm systems, and robotic construction applications. His projects emphasize reproducibility through dedicated planning tools (Planner Developer Tools) and leverage material integration for collective building tasks.

Mak Đukanمشاهده پروفایل

پژوهشگر

• Climate Finance
• Renewable Energy Policy
• Energy Economics
• +۵ مورد دیگر

Dr. Mak Đukan is a researcher in the Climate Finance & Policy (CFP) group at ETH Zurich since May 2022, focusing on renewable energy financing landscapes, offshore wind investment policies, and decarbonization technologies like carbon capture and hydrogen. His work addresses cost of capital challenges and policy design for renewable projects in Switzerland and Europe. He holds a PhD in Energy Economics from DTU (Denmark), with research on renewable auctions' impact on financing, and master's degrees in circular economy from Ritsumeikan Asia Pacific University and Trier University of Applied Sciences. Prior roles include UNDP energy cooperative development in Croatia, EU policy research at Joanneum Research, and consulting on Southeast European energy policies. He secured Interreg funding for the ENES-CE project improving regional energy governance. Education: PhD (DTU), M.Sc./M.Eng. (Ritsumeikan/Trier), B.Sc. Economics (University of Zagreb). Research methods combine interviews and stochastic cash flow analysis. Notable contributions include studies on solar PV policy fragmentation in Switzerland and merchant risk in offshore wind projects. His current projects include the SWEET Edge initiative on decentralized energy financing.

Liyang Chenمشاهده پروفایل

پژوهشگر

• X-ray Imaging
• Nanopatterning
• Materials Science
• +۳ مورد دیگر

Dr. Liyang Chen is a Researcher at ETH Zürich's Department of Information Technology and Electrical Engineering, affiliated with the Professorship for X-ray Imaging. His research focuses on advanced materials science, nanotechnology, and optoelectronics, with emphasis on X-ray imaging components, metallic micro-nano networks, and nanostructured materials. Key areas include nanopatterning techniques, strain engineering of 2D materials, and transparent electrode development. His work integrates fabrication methods like interference lithography and nanoimprint processes to advance optoelectronic and energy-related applications. Publications highlight contributions to metallic surface micropatterning, perovskite-based devices, and fog-harvesting materials. Chen’s interdisciplinary approach bridges materials synthesis, manufacturing processes, and device applications. His lab focuses on high-precision nanostructuring for next-generation optical and electronic systems, leveraging curved substrate technologies and hybrid modeling approaches.

• Control Systems
• Data-Driven Control
• Optimization Algorithms
• +۳ مورد دیگر

Jaap Eising is a Lecturer at the Department of Information Technology and Electrical Engineering at ETH Zürich. His research focuses on control systems, data-driven control methodologies, optimization algorithms, and system identification. He explores topics such as affine time-invariant systems, robust control of linear systems, and adaptive control strategies for uncertain systems. His work emphasizes theoretical foundations and practical applications in control theory, leveraging data-driven approaches to enhance system analysis and stabilization. Recent publications highlight advancements in data-driven techniques for mode detection, parameter variation decoupling, and cautious optimization under noisy data. His research also addresses challenges in online adaptive control and stabilization of switched systems. Key themes include informativity frameworks, quadratic matrix inequalities, and the integration of statistical modeling with control theory. No scientific awards or grants are explicitly mentioned in the provided texts. His academic contributions are centered on advancing control systems through rigorous mathematical analysis and innovative algorithmic designs.

• Biopolymers
• Food Science
• Materials Science
• +۳ مورد دیگر

Dr. Shrestha Roy Goswami is a Researcher at the Laboratory of Food & Soft Materials, part of the Institute of Food, Nutrition and Health at ETH Zürich. Her work focuses on developing sustainable, bio-based materials and advanced polymers for food packaging and industrial applications. She specializes in starch modification, ionic liquid-mediated chemistry, and nanomaterial synthesis. Her research interests span biodegradable polymers, amyloid fibril formation, and the valorization of agricultural byproducts (e.g., tofu wastewater). She explores innovative methods to enhance material toughness, biodegradability, and functional properties using eco-friendly approaches. Notable projects include starch-based bioplastics reinforced with soy amyloids and shape-memory polyurethanes from abietic acid. Publications highlight trends in starch-derived materials, ionic liquid applications, and nanotechnology for biomedical and food industry uses. Her work bridges fundamental chemistry with practical sustainability solutions. No scientific awards or grants are explicitly mentioned in the provided text. She advises no students in listed publications.

• Transportation Planning
• Urban Design
• Agent-Based Modeling
• +۴ مورد دیگر

Dr. Alexander Erath Rusterholtz is a Lecturer at ETH Zurich's Department of Mechanical and Process Engineering. He leads the 'Engaging Mobility' research project at the Future Cities Laboratory (FCL) in Singapore, focusing on mobility solutions for dense urban areas. His work integrates agent-based modeling, Big Data, and urban design to analyze travel behavior, particularly cycling and pedestrian mobility. He also directs projects in Switzerland funded by the Swiss Federal Roads Office (FEDRO) to quantify pedestrian potential in agglomerations. Education: PhD in Transport Infrastructure Vulnerability (2011, ETH Zurich) Research Interests: Erath’s research emphasizes multi-agent transport demand modeling, activity-based simulations, and the interplay between transport infrastructure and urban design. His work leverages immersive virtual reality (VR) for behavioral studies, Big Data for modeling urban mobility, and agent-based systems for pandemic spread analysis. Key areas include cycling safety, walkability indicators, and policy impacts on transport systems. Grants & Awards: His projects are funded by the National Research Foundation (NRF) Singapore, Swiss federal agencies, and collaborations with institutions like FCL and Urban Redevelopment Authority (URA). Notable outputs include the MATSim Singapore transport model and the first behaviorally-based walkability metric for Singapore. Advising & Labs: Erath oversees interdisciplinary teams at FCL and ETH Zurich, focusing on mobility futures and urban analytics. His lab develops tools like the Pedestrian Accessibility Tool (PAT) and VR cycling simulators for experimental research.

Alexander Fuchsمشاهده پروفایل

پژوهشگر

• Power Grid Simulation
• Optimization
• Energy Networks
• +۳ مورد دیگر

Dr. Alexander Fuchs serves as Principal Expert for power grid simulation at the Research Center for Energy Networks (FEN) at ETH Zurich, where he focuses on applications of optimization, simulation and geometric approaches for the planning and safe operation of power grids. His work spans European power grid modeling, renewable energy integration, and grid security analysis. Dr. Fuchs' research interests center on power grid optimization and simulation, with particular emphasis on the integration of renewable energy sources into existing grid infrastructure. His work addresses critical challenges in energy transition, including grid stability with high renewable penetration, optimal storage operation, and security analysis of power systems. He has developed specialized software for N-1 security analyses and secure load flow optimization, demonstrating his technical expertise in computational power system analysis. His publication record reveals a consistent focus on power system stability, HVDC transmission technologies, and renewable integration challenges. The research trajectory shows increasing attention to practical implementation challenges of energy transition policies, particularly evident in his more recent work on Swiss energy strategy and photovoltaic integration. His work bridges theoretical control systems with practical grid operation challenges. Dr. Fuchs has conducted significant research for the Swiss Federal Electricity Commission (ElCom), demonstrating his role as a trusted expert in national grid security matters. His projects span multiple European initiatives including ISCHESS, SCCER-FURIES, and ACSICON, indicating strong collaborative networks across the European energy research community. His work on the Energy Strategy 2050 simulation demonstrates direct policy relevance of his research.