جست‌وجوی استاد و پژوهشگر

• Multiscale Modeling
• Multiphysics Modeling
• Biophysics
• +۷ مورد دیگر

Dr. Igor V. Pivkin is a Full Professor at the Institute of Computing within the Faculty of Informatics at the Università della Svizzera italiana (USI) in Lugano, Switzerland. His academic journey includes degrees from Novosibirsk State University (B.Sc./M.Sc. Mathematics), Brown University (M.Sc. Computer Science and Ph.D. Applied Mathematics), and postdoctoral research at MIT's Department of Materials Science and Engineering. His research focuses on multiscale/multiphysics modeling , numerical methods , and large-scale simulations of biological and physical systems. Key areas include biophysics, cellular/molecular biomechanics, stochastic modeling, and coarse-grained molecular simulations. He leverages high-performance computing (HPC) and particle-based methods to address complex biological phenomena. His work spans diverse applications, from understanding cellular mechanosensitivity and biofilm engineering to modeling cancer cell behavior and red blood cell dynamics in the spleen. His contributions bridge computational science, biotechnology, and biomedical research. He has published extensively in top-tier journals, with recent work advancing automated biofilm analysis, deep learning for microbial classification, and systems biology approaches to metal bioleaching. His lab collaborates on interdisciplinary projects, emphasizing computational innovation for real-world biological challenges.

Alessandro Ottavianoمشاهده پروفایل

پژوهشگر

• Computer Architecture
• Embedded Systems
• Real-Time Systems
• +۳ مورد دیگر

Dr. Alessandro Ottaviano is a Researcher affiliated with the Department of Digital Integrated Circuits and Systems at ETH Zürich. His work focuses on advanced computer architecture and embedded systems, particularly in the domains of RISC-V processors, real-time systems, and heterogeneous computing. He contributes to the design of time-predictable virtual memory solutions, mixed-criticality systems, and energy-efficient hardware-software interfaces. Key research areas include modular processor architectures, hardware monitoring for safety-critical applications, and power management in high-performance computing (HPC) systems. His recent projects involve developing controllers for 2.5D systems-in-package and creating open-source networking solutions for mixed-criticality environments. Ottaviano’s work often emphasizes open-source hardware design and scalable system-level approaches to address challenges in autonomous systems and edge computing. He collaborates on advancements in interrupt handling for virtualized systems, peripheral event linking for IoT devices, and FPGA-based thermal emulation for many-core processors. His research bridges theoretical computer architecture principles with practical implementations in embedded and real-time systems.

• Applied Mathematics
• High Performance Computing
• Machine Learning
• +۲ مورد دیگر

Prof. Panayot Vassilevski is a faculty member at the Faculty of Informatics of the Università della Svizzera italiana (USI) in Switzerland. He is engaged in collaborative research involving high-performance computing (HPC) and computational methods for partial differential equations (PDEs), with a focus on scalable discretization and solver development. His work intersects applied mathematics and computer science, particularly in the context of discrete networks and GPU-accelerated algorithms. Fields of Interest: Applied Mathematics, High Performance Computing, Machine Learning, Computational Science, Partial Differential Equations Recent work includes the GPU Accelerated Shifted Penalty Multigrid for Contact Elasticity (2024), which highlights his expertise in computational methods and HPC. This project builds on prior successful collaborations, such as the LLNL sabbatical of Prof. Rolf Krause and the internship of his student Patrick Zulian, which resulted in a publication. The collaboration also involves Dr. Zulian and the Swiss Supercomputing Center (CSCS) in Lugano. During the visit, Prof. Vassilevski and his PhD student Austen Nelson will work with Prof. Krause's team on reciprocal knowledge exchange. Advising: Austen Nelson, a PhD student under Prof. Vassilevski, is participating in the project. The visit project (Grant #229884, funded by the Swiss National Science Foundation with 10,500 CHF) emphasizes in-depth methodological collaboration and personnel exchange between USI and Portland University, as well as LLNL and CSCS. Labs and Teams: The project involves the Euler Institute at USI and the Swiss Supercomputing Center (CSCS) in Lugano. These institutions are pivotal for advancing the HPC-software project, which combines theoretical and algorithmic tasks in scalable discretization methods and PDE solvers.

• High performance computing
• Computational Science and Engineering
• Scientific computing
• +۷ مورد دیگر

Olaf Schenk is a Professor at the Institute of Computing within the Faculty of Informatics at Università della Svizzera italiana (USI), Switzerland. He serves as Director of the Institute of Computing and Co-Director of the Master in Computational Science. He is also an adjunct member of the Computer Systems Institute at USI. PhD in Information Technology and Electrical Engineering, ETH Zurich (2001) Venia Legendi in Mathematics and Computer Science, University of Basel (2009) Applied Mathematics, Karlsruhe Institute of Technology (KIT), Germany His research focuses on high-performance computing , computational science and engineering , and applied algorithms for extreme-scale simulations. He bridges computer science with scientific computing needs, particularly in parallel algorithms , sparse solvers , graph analytics , and manycore architectures . His work emphasizes scalable software tools and programming models for emerging HPC systems. The 15 most recent publications reflect a consistent focus on sparse matrix computations , parallel and task-based algorithms , graph partitioning , and performance optimization for heterogeneous and manycore systems. Keywords span high-performance computing, numerical linear algebra, and large-scale data analysis, showing strong integration of theoretical algorithm design with practical implementation. Olaf Schenk has received several prestigious honors: Elected Fellow, Society for Industrial and Applied Mathematics (SIAM) Senior Member, IEEE and ACM SIAM Supercomputing Prize 2023 IBM Faculty Award Two Leadership Computing Awards from the U.S. Department of Energy He has held leadership roles as Chair, Vice Chair, and Program Director of the SIAM Activity Group on Supercomputing. He serves as Associate Editor for ACM Transactions on Mathematical Software and on the editorial board of SIAM Journal on Scientific Computing . He has participated in over 60 international program committees, including top-tier conferences such as SC, IPDPS, and IEEE CSE. He advises PhD and Master’s students in computational science and leads research projects funded by national and international agencies. He is also the Founder & Director of Panua Technologies Sagl, focusing on high-end software for simulation and optimization. His research group at USI works on next-generation computing tools for extreme-scale scientific simulations, with ongoing work in adaptive algorithms, resilience, and hybrid CPU-GPU computing. He leads collaborative projects with institutions in Europe and the U.S., aiming to develop scalable, robust, and efficient software for future exascale systems.

• Astrophysics
• Solar Physics
• Radiative Transfer
• +۳ مورد دیگر

Simone Riva is a Postdoctoral researcher affiliated with the Faculty of Informatics at the Università della Svizzera italiana . He is also associated with the Euler Institute and the Istituto ricerche solari Aldo e Cele Daccò (IRSOL) . His contact information includes simone.riva@usi.ch and offices located at East Campus, Sector D, Office D5.13 (Lugano) and Via Patocchi 57 (Locarno). His research focuses on astrophysics , particularly in the modeling of solar radiation transfer and polarization phenomena . Key areas include computational methods for solving radiative transfer equations, partial frequency redistribution effects, and high-performance computing techniques applied to stellar atmospheres. He has contributed to studies involving the Ca I 4227 Å line and the development of scalable numerical solvers for 3D transfer of polarized radiation. Recent work emphasizes the application of parallel preconditioned Krylov solvers and HPC techniques to address challenges in radiative transfer with angle-dependent partial redistribution. His research bridges computational physics with observational astrophysics, aiming to advance our understanding of solar magnetic fields and chromospheric dynamics. While no scientific awards are explicitly listed, his contributions to funded projects and collaborations with institutions like IRSOL underscore his active role in advancing solar and stellar physics research. He is affiliated with labs including the Euler Institute and IRSOL, which provide critical computational and observational infrastructure for his work.

• Computer Architecture
• Distributed Systems
• Cloud Computing
• +۳ مورد دیگر

Javier Picorel is a former researcher at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the Parallel Systems Architecture Lab (Parsa). His work focuses on computer architecture, distributed systems, and cloud computing, with an emphasis on optimizing storage systems, near-data processing, and high-performance computing. Picorel has contributed to advancements in scalable serverless computing, secure data center architectures, and accelerator design. His research interests include storage-class memory hierarchies, virtual machine performance optimization, and software-defined systems. Key projects include BlockNDP for block-storage acceleration, IndiLog for stateful serverless systems, and SPARTA for accelerator address translation. He has collaborated extensively with the Parsa group and published widely in top conferences such as ISCA, MICRO, and PACT.

• Computer Architecture
• Computer Arithmetic
• RISC-V Systems
• +۳ مورد دیگر

David Mallasen Quintana is a Scientist and Lecturer at the Swiss Federal Institute of Technology Lausanne (EPFL), affiliated with both the School of Engineering (STI) and the Integrated Systems Laboratory (ESL) within the Institute of Electrical and Microengineering. He also holds teaching responsibilities in the School of Computer and Communication Sciences (IC) at EPFL. Dr. Quintana completed his Ph.D. in Computer Engineering at Universidad Complutense de Madrid in 2024. His research focuses on: Computer architecture and arithmetic systems RISC-V ecosystem development and customization Energy-efficient hardware design and domain-specific accelerators Posit arithmetic implementations and optimizations Embedded systems and low-power computing solutions His recent publications demonstrate consistent focus on RISC-V extensions, posit arithmetic implementations, and hardware/software co-design approaches for efficient computing. The work spans from fundamental arithmetic units to application-specific accelerators, with evolving emphasis on scientific computing applications and energy-constrained environments. Dr. Quintana actively contributes to open-source hardware projects including PERCIVAL, x-HEEP, and various arithmetic unit implementations. His research group develops energy-efficient platforms and tools for hardware deployment within the RISC-V ecosystem.

• Fluid-Structure Interaction
• Geophysics Applications
• Immersed Boundary Methods
• +۳ مورد دیگر

Maria Giuseppina Chiara Nestola is a Researcher at the Faculty of Informatics, Università della Svizzera italiana (USI), and partially affiliated with the Department of Earth Sciences at ETH Zurich. Her work focuses on developing advanced numerical methods for fluid-structure interaction (FSI), immersed boundary techniques, and fracture network modeling in biomedical and geophysical contexts. She contributes to projects like FASTER (geothermal reservoir simulations) and HPC-PREDICT (cardiovascular prognosis), and leads software development for tools like AV-FLOW (FSI library), Parrot (fracture network modeling), and Utopia (linear algebra). Her research integrates high-performance computing with applications in geophysics (e.g., seismic hazard assessment, geothermal systems) and biomechanics (e.g., aortic valve dynamics, turbulent blood flow). Key collaborations include the Center for Computational Medicine in Cardiology and the Swiss Competence Center for Energy Research (SCCER-SoE). She holds roles as FOMICS administrator and project co-PI/co-investigator in PASC initiatives. Her technical expertise spans parallel algorithms, embedded finite-element methods, and multi-physics simulations. Current efforts emphasize real-time geothermal reservoir modeling using Multilevel Monte Carlo methods and benchmarking fracture flow simulations.

Marcin Copikمشاهده پروفایل

پژوهشگر

• Parallel Computing
• High-Performance Computing (HPC)
• Serverless Systems
• +۳ مورد دیگر

Dr. Marcin Copik is a Researcher in the Professorship for Scalable Parallel Computing at ETH Zürich, focusing on advancing high-performance computing (HPC), serverless systems, and cloud computing. His work emphasizes optimizing resource utilization, improving scalability, and enhancing performance in distributed and parallel environments. His research interests span parallel computing architectures, serverless benchmarking (e.g., SeBS suite), and sustainable HPC practices. He explores techniques like automatic loop scheduling, acceleration-as-a-service models, and fault-tolerant distributed systems (e.g., FaaSKeeper). His contributions address challenges in cloud elasticity, stateful services, and energy-efficient computing. Recent publications highlight innovations in serverless workflows, AI reasoning frameworks, and hardware-accelerated protocols. His work bridges theoretical foundations with practical implementations, such as Cppless for high-performance serverless programming and XaaS for HPC-cloud integration. While no formal awards or grants are listed, his contributions to open-source projects like STEllAR-GROUP/hpx and Extrapeak demonstrate active engagement in the HPC community. He collaborates closely with academic and industry partners to advance scalable computing solutions.

Frank Kagan Gürkaynakمشاهده پروفایل

پژوهشگر

• Energy-Efficient Microelectronics
• Cryptographic Hardware Security
• Digital Integrated Circuit Design
• +۴ مورد دیگر

Frank Kagan Gürkaynak is Director of the Microelectronics Design Center (DZ) and a Researcher at ETH Zurich's Department of Information Technology and Electrical Engineering (D-ITET). He leads the PULP open-source hardware project and works closely with Prof. Luca Benini in the Integrated Systems Laboratory (IIS). His academic journey includes BSc/MSc from Istanbul Technical University and a PhD from ETH Zurich. Roles: Microelectronics Design Center Director, Senior Scientist in IIS, VLSI course lecturer Research focuses on energy-efficient digital circuits, cryptographic hardware security, and open-source processor architectures. Key projects include EU-funded initiatives like European Processor Initiative (EPI), Convolve, and NeuroSoC, along with SNSF grants Tiny Trainer and PEDESITE. Active in teaching VLSI design, embedded systems, and essential engineering skills. Publications emphasize secure cryptographic accelerators, low-power processor clusters, and GALS system design methodologies. Contributions include energy-efficient ASICs for IoT to HPC domains and pioneering work in side-channel attack-resistant hardware.

Emmanuel Lantiمشاهده پروفایل

مدرس

• Plasma Physics
• Fusion Energy Research
• Gyrokinetic Simulations
• +۳ مورد دیگر

Emmanuel Lanti is a Lecturer and HPC Applications Specialist at École polytechnique fédérale de Lausanne (EPFL), affiliated with the School of Engineering and the Center for Research and Fundamental Studies (SCITAS). His work focuses on plasma physics, computational methods for gyrokinetic simulations, and high-performance computing (HPC) optimization in tokamak research environments. Research Areas: Plasma physics, fusion energy, electromagnetic turbulence, nonlinear dynamics of Alfven modes, and HPC applications in particle-in-cell (PIC) code development. Technical Expertise: Global gyrokinetic simulations, parallel computing architectures, numerical methods for plasma confinement, and wave-particle interaction analysis. Lanti's recent publications emphasize advancements in: Modeling tokamak plasmas with nonadiabatic chirping-frequency Alfven modes (2023) Optimizing computational strategies for electromagnetic turbulence simulations (2022) Developing numerical tools for burning plasmas and open-field-line configurations (2021-2019) Validating gyrokinetic code performance on many-core and GPU-accelerated systems (2016-2018) His work bridges plasma theory with practical code implementation, targeting improved understanding of magnetic confinement and turbulence in fusion devices. Key methodologies include: Particle-in-cell (PIC) simulations Hybrid kinetic electron models Pade approximation techniques Parallel computing optimizations

Nicolas Richartمشاهده پروفایل

مدرس

• High Performance Computing
• Computational Solid Mechanics
• Finite Element Methods
• +۳ مورد دیگر

Nicolas Richart is a Lecturer at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the School of Architecture, Civil and Environmental Engineering (ENAC) and the Computational Solid Mechanics Laboratory (LSMS). He works as an HPC Applications Expert within EPFL's SCITAS-GE unit, specializing in parallel computing and finite element simulations. Engineer in Computer Science (2005) from ENSEIRB, France PhD in Computer Science (2010) from Université de Bordeaux 1 His research focuses on computational mechanics, particularly finite element methods, non-local continuum damage modeling, and high-performance computing applications. He develops the open-source Akantu finite element library and investigates geomechanical modeling of CO2 storage, fault stability, and dynamic crack propagation in ceramic materials. Recent publications highlight his expertise in continuum damage mechanics, cohesive zone modeling, and parallel computing applied to structural failure analysis and geomechanical simulations. Key subfields include fault stability in CO2 storage, micro-mechanical modeling of masonry, and dynamic fracture analysis in ceramics. As an active contributor to computational mechanics research, Richart collaborates with institutions across Europe and the United States on seismic response analysis, crack propagation modeling, and non-local damage formulations. His work bridges software development (Akantu library) with practical applications in structural and geomechanical engineering. He maintains dual office locations at EPFL's ME B2 454 and GC A2 505 buildings, with both teaching and research responsibilities spanning computational methods, structural analysis, and high-performance computing.

• Simulation and Optimization
• Production Systems
• Logistics
• +۲ مورد دیگر

Lukas Hollenstein is Professor and Co-Head of the Centre for Digital Labs & Production at ZHAW School of Life Sciences and Facility Management. His research develops simulation and optimization methods for complex production and logistics systems, with applications spanning sustainable materials, supply chain management, and industrial processes. Research Leadership: Hollenstein directs the Simulation & Optimization Research Group, focusing on: HPC-enabled simulation for manufacturing optimization Sustainable alternatives in materials processing Supply chain risk mitigation through predictive modeling Industry 4.0 complexity management Interdisciplinary Projects: He leads initiatives including 'Agroforestry Carbon Token System' and 'Smart Hospital – Integrated Framework', demonstrating cross-sector applications of simulation methodologies. His work frequently appears in food science, logistics, and industrial engineering venues.

Torsten Hoeflerمشاهده پروفایل

استاد

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

Prof. Torsten Hoefler is a Full Professor at the Department of Computer Science, ETH Zürich. His research focuses on High-Performance Computing (HPC), parallel systems, networking, and AI-infrastructure. He leads projects on scalable interconnects, network topology design, and cloud computing benchmarks like SeBS. His work bridges theoretical foundations with practical implementations in distributed systems. Research Interests : High-Performance Computing & Networking Parallel Algorithms & Architectures AI Infrastructure & Distributed Systems Chiplet Interconnects & Topology Optimization Key Contributions : Developed tools like ATLAHS (AI/HPC network simulation) Advanced RDMA-based communication protocols (SDR-RDMA) Benchmarks for serverless computing (SeBS-Flow) His recent articles (2025) emphasize adaptive networks, low-precision AI models, and energy-efficient HPC systems. He also explores ethical computing and sustainability in supercomputing through initiatives like Core Hours & Carbon Credits.

Alexander Heinleinمشاهده پروفایل

استادیار

• Numerical methods for partial differential equations
• Scientific computing
• Domain decomposition methods
• +۶ مورد دیگر

Dr. Alexander Heinlein is an Assistant Professor in the Numerical Analysis group at the Delft Institute of Applied Mathematics (DIAM), Faculty of Electrical Engineering, Mathematics & Computer Science (EEMCS), Delft University of Technology (TU Delft). His work bridges scientific computing and machine learning through scientific machine learning (SciML) , focusing on domain decomposition methods and multiscale approaches for solving complex partial differential equations on modern hardware like GPUs. Research interests include: Developing high-performance computing algorithms for nonlinear PDEs with applications in fluid-structure interaction and photonic crystals Advancing physics-aware machine learning techniques for groundwater heat transport and post-burn contraction prediction Creating parallel preconditioners like FROSch for challenging problems in computational mechanics Building hybrid numerical-ML frameworks with domain decomposition for multi-physics applications His recent publications highlight a 128-235x speedup in biomedical simulations through deep operator networks , and keynote presentations on geometric challenges in machine learning-based surrogate models at international conferences like CASML 2024. Scientific awards include: 2025 NWO Open Technology Programme grant for the RAPID-Wind project on offshore wind turbine foundations Students and collaborations involve: Yuhuang Meng (PhD candidate, 2024) Jing Zhao (co-supervisor) Prof. Jun Zou (Chinese University of Hong Kong collaboration, 2024) He leads software development for COMSOL and Trilinos extensions while maintaining open-source reproducibility standards.