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Estela SuarezView profile

Professor

• high performance computing (HPC)
• heterogeneous HPC system architectures
• modular supercomputing architecture (MSA)
• +4 more

Prof. Dr. Estela Suarez is a Professor of High Performance Computing at the Institute for Computer Science, University of Bonn (W2 in the Jülich Model) and Joint Lead of the Division "Novel System Architecture Design" at the Jülich Supercomputing Centre (JSC), Forschungszentrum Jülich GmbH. She also leads the Research Group "Next Generation Architectures and Prototypes" at JSC and serves as Spokesperson of Helmholtz Information Program 1, Topic 2. Currently on sabbatical during the 2024/2025 and 2025 academic years, she remains active in research leadership roles. 2010: PhD in Physics from University of Geneva, Switzerland 2004: Master in Physics, Specialization in Astrophysics, University Complutense of Madrid, Spain Professor Suarez specializes in high performance computing with particular expertise in heterogeneous HPC system architectures and modular supercomputing architecture (MSA). Her research spans hardware prototyping and evaluation, system software development, operational data analysis, and co-design methodologies. She has pioneered approaches to address hardware heterogeneity through system-wide orchestration of diverse computing resources, enabling more efficient scientific computing across multiple domains. Her work bridges theoretical computer architecture with practical implementation challenges in exascale computing environments, focusing on real-world applications that require specialized hardware configurations. Professor Suarez's publication record shows a clear evolution from foundational work on the DEEP project (2016) through the development of modular supercomputing concepts (2019-2021) to current applications across diverse scientific domains (2022-2024). Her recent publications demonstrate how modular architectures can be effectively applied to climate modeling, neuroscience simulations, quantum chemistry calculations, and other computationally intensive fields. This trend highlights her focus on practical implementation challenges and the growing importance of adaptable computing architectures in modern scientific research. 2023/2024 Lehrpreis der Universität Bonn: UniBonn teaching award Professor Suarez has secured significant research funding through major projects including NUMERIQS (Projects A05, B02, and Z02), European Processor Initiative (EPI), DEEP-SEA (Software for Exascale Architectures), IFCES2 (optimization of simulation algorithms for exascale supercomputers), and AIDAS (virtual laboratory between Forschungszentrum Jülich and CEA on AI and data analytics). While currently not accepting new students due to sabbatical, she has previously mentored graduate students in high performance computing techniques and has delivered numerous invited lectures at international conferences. Professor Suarez leads the "Next Generation Architectures and Prototypes" research group at JSC and serves as Joint Lead of the "Novel System Architecture Design" division. She chairs the Research and Innovation Advisory Group (RIAG) from EuroHPC Joint Undertaking since 2024. Her work involves close collaboration with international research teams on advancing supercomputing architectures, including contributions to the University of Bonn's new HPC system "Marvin" which ranks on both the TOP500 and GREEN500 lists.

Sandra Diaz PierView profile

Researcher

• Computational Neuroscience
• High Performance Computing
• Machine Learning
• +3 more

Dr. Sandra Diaz Pier is a Scientific Lead at the Jülich Supercomputing Centre (JSC) within the Jülich Research Centre , Germany. Specializing in computational neuroscience , high performance computing (HPC) , and machine learning , she bridges neuroscience and advanced computational methods through her research. Education: B.Sc. in Electronic Systems Engineering, Mexico M.Sc. in Computer Science (focus: machine learning, quantum computing), Mexico Second M.Sc. in Electrical Engineering, Ontario, Canada Ph.D. in Computer Science, Germany (2021) Her research focuses on modeling and simulating brain dynamics and plasticity at multiple scales, leveraging HPC to accelerate large-scale neural network simulations. She actively contributes to EU projects like the Human Brain Project (HBP) , Virtual Brain Cloud , and EBRAINS 2.0 , emphasizing infrastructure development and educational training. Her work includes open-source tools such as the NEST simulator , The Virtual Brain , and L2L , enabling efficient parameter exploration and multiscale co-simulation frameworks. The 15 most recent publications highlight her interdisciplinary approach, spanning topics from quantum computing in biomolecular simulations to neural plasticity algorithms and cloud-based brain modeling . These articles reflect her expertise in integrating machine learning , multi-scale simulation , and HPC infrastructure for neuroscience challenges, including seizure propagation, Parkinson’s disease progression, and swarm intelligence in spiking networks. She leads technical coordination in projects like EBRAINS and serves as a task leader in the HBP infrastructure work package , while also organizing workshops and hackathons for open-source tools. Her role involves supporting domain scientists through methodological research and workflow optimization for brain simulations.

• Parallel File and Storage Systems
• Modular Supercomputing
• Resource Disaggregation and Virtualization
• +6 more

Sarah Neuwirth is a tenured Professor for Computer Science at Johannes Gutenberg University Mainz (JGU) and a Visiting Researcher at the Jülich Supercomputing Centre. She manages JGU's High Performance Computing (HPC) division, coordinates regional/national HPC activities, and represents JGU in NHR, Gauss-Allianz, and HPC committees. Education : PhD (Dr. rer. nat.) in Computer Science (2018), Heidelberg University Diplom in Computer Science (2012), University of Mannheim Bachelor of Science in Computer Science (2010), University of Mannheim Research Interests : Parallel File and Storage Systems Modular Supercomputing (resource disaggregation/virtualization) Performance Engineering High Performance Computing Networking Reproducible Benchmarking Parallel I/O Publications Trends : Her work focuses on HPC performance modeling, parallel I/O optimization, modular supercomputing, network characterization, and reproducible benchmarks. Key themes include resource disaggregation, automated workflows, and data-intensive distributed applications. Scientific Awards : 2023 PRACE Ada Lovelace Award for HPC ZONTA Science Award 2019 Grants & Leadership : She leads the High Performance Computing division at JGU, participated in European DEEP projects, and serves on SC conference committees.

• High-Performance Computing (HPC)
• Computational Fluid Dynamics
• Quantum Computing
• +3 more

Stefano Markidis is a leading researcher in High-Performance Computing (HPC) and quantum computing. His work focuses on developing advanced simulation frameworks, such as the Neko framework for computational fluid dynamics, and optimizing algorithms for heterogeneous architectures. He collaborates extensively with institutions and researchers globally, contributing to fields like plasma physics, quantum systems, and machine learning applications. His research emphasizes scalability, performance optimization, and the integration of cutting-edge technologies like GPU acceleration and quantum computing. Key research interests include extreme-scale simulations, quantum algorithms, and in-situ data analysis techniques. He has published over 200 articles, with recent work addressing challenges in NISQ systems, tensor network simulations, and CUDA-based performance enhancements. His contributions span theoretical and applied domains, bridging computational methods with real-world applications in fusion energy, materials science, and space exploration. Notable collaborations include projects with Philipp Schlatter, Niclas Jansson, and the NISQ application development community. Markidis also explores hybrid frameworks combining classical and quantum computing, aiming to leverage emerging hardware for scientific breakthroughs.

Kristel MichielsenView profile

Professor

• Quantum Computing
• Quantum Annealing
• Quantum Simulation
• +3 more

Prof. Dr. Kristel Michielsen is a Professor of Quantum Information Processing at RWTH Aachen University and holds leadership roles at Forschungszentrum Jülich. She leads the division HPC for Quantum Systems and heads the Jülich UNified Infrastructure for Quantum computing (JUNIQ). As Group Leader of the Research Group Quantum Information Processing, her work focuses on quantum annealing, quantum simulation, and modular hybrid HPC-quantum computing. She is also Spokesperson of the Helmholtz Information Program 1 and a Principal Investigator in Topics 1 and 2. Affiliations: RWTH Aachen University, Forschungszentrum Jülich (IAS/JSC), JUNIQ Key Roles: Head of HPC for Quantum Systems, JUNIQ Director, Quantum Information Processing Group Leader Her research emphasizes quantum computing applications in optimization, benchmarking, and hybrid supercomputing-quantum systems. She pioneers quantum-annealing solutions for real-world problems like power grid partitioning and transportation logistics. Recent work explores error mitigation, noise modeling in D-Wave systems, and quantum-classical workflows.

Stefan LankesView profile

Researcher

• Operating Systems
• System Software
• High-Performance Computing
• +4 more

Dr. rer. nat. Stefan Lankes is an academic researcher at the Chair of Automation of Complex Power Systems, RWTH Aachen University's Faculty of Electrical Engineering and Information Technology. His work focuses on operating systems, high-performance computing (HPC), cloud computing, and lightweight virtualization techniques for embedded and real-time systems. Stefan holds a PhD in Electrical Engineering (2003) for his dissertation on real-time distributed platforms. His career spans roles from Scientific Assistant (1998-2004) to Academic Director (since 2019), with key contributions to HPC infrastructure and simulation environments. Research highlights include Rust-based OS development ( HermitCore unikernel ), GPU virtualization in distributed systems, and energy-efficient embedded computing paradigms. He pioneered the FlippedOS digital teaching platform using virtual workstations for operating systems education. Scientific awards include the 2016 Digital Teaching Fellowship and the 2021 RWTH Lecturer distinction. His publications cover topics from NUMA memory management to real-time CORBA protocols, with recent works addressing unikernel security and CUDA virtualization. Stefan leads simulation infrastructure and HPC virtualization projects, with affiliations to the E.ON Energy Research Center and involvement in European workshops like Euro-Par. His work bridges system software innovation with practical applications in energy systems and supercomputing.

Jan MeinkeView profile

Researcher

• High-Performance Computing
• GPU Programming
• Performance Portability
• +5 more

Dr. Jan Meinke is a Researcher at the Jülich Supercomputing Centre (JSC) within Forschungszentrum Jülich, Germany. His work focuses on high-performance computing, GPU programming, and performance portability across different hardware platforms. He contributes to the development of exascale computing applications and benchmarks, particularly through the JUPITER benchmark suite. Based in Building 14.14, Room 4012 at the Jülich research campus, he maintains active research collaborations across computational science domains. Dr. Meinke's research spans two major domains: high-performance computing and computational epidemiology. In HPC, he investigates GPU programming models, performance portability across vendors, and scalable computational fluid dynamics. His work on the JUPITER benchmark suite aims to address challenges in application-driven exascale computing. In computational epidemiology, he has developed forecasting models for COVID-19 spread across European nations, focusing on ensemble approaches and short-term prediction. His earlier work includes protein folding simulations and Monte Carlo methods, demonstrating a long-standing interest in computational methods across scientific domains. Analysis of Dr. Meinke's publication history reveals a strategic evolution from computational biophysics to high-performance computing infrastructure. His recent work (2023-2025) shows a strong emphasis on performance portability across GPU architectures, particularly for scientific computing applications like the N-body problem and computational fluid dynamics. The JUPITER benchmark suite represents a significant contribution to exascale computing evaluation, bridging theoretical computer science with practical applications. His dual focus on HPC infrastructure and epidemiological modeling demonstrates versatility in applying computational methods to diverse scientific challenges. Dr. Meinke has been actively involved in both teaching and research aspects of high-performance computing, authoring educational materials on GPU programming with CUDA and advanced GPU techniques. His work demonstrates a commitment to advancing both the theoretical foundations and practical applications of high-performance computing, with implications for scientific discovery across multiple domains including physics, engineering, and public health.

Stefan ZellmannView profile

Associate Professor

• Scientific Visualization
• Computer Graphics
• High-Performance Computing
• +4 more

Stefan Zellmann is an Associate Professor and Principal Investigator of the DFG Project 'VTV-AMR' at the Institute of Computer Science , University of Cologne. His research focuses on the intersection of large-scale scientific visualization and high-performance computing, particularly in developing real-time rendering algorithms for adaptive mesh refinement (AMR) data. He leads projects such as ExaBrick (AMR rendering framework) and Visionaray (cross-platform ray tracing library). Education & Roles: Completed his PhD in 2014 on 'Interactive High-Performance Volume Rendering'. Currently teaches courses on graphics processor architectures and programming, including Practical Computer Science: Architecture and Programming of Graphics and Coprocessors . Research Interests: Direct volume rendering, physically based rendering, AMR visualization, GPGPU computing, and FPGA programming. His work emphasizes low-latency interaction and efficient algorithms for supercomputers/multi-GPU systems. Awards: Honorable Mention @EGPGV 2020, Best Paper Awards @EGPGV 2018 (for Rapid k-d Tree Construction ), @VDA 2017 (for Ray Clipping ), and @PDCS 2012 (for Distributed Volume Rendering Architecture ). Key Projects: ExaBrick (AMR rendering), Visionaray (ray tracing), Virvo (volume rendering library), and HPSC TerrSys (high-performance computing in terrestrial systems). Grants & Services: Co-Chair of IEEE LDAV 2022 Posters, Program Committee member for IEEE VIS and EGPGV. Regular reviewer for journals/conferences like TVCG and IEEE VR. Labs/Teams: Part of the Center for Data and Simulation Science (CDS), focusing on visualization algorithms for exascale computing and large-scale scientific data.

Thomas LippertView profile

Professor

• Quantum Computing
• High-Performance Computing (HPC)
• Supercomputing Architecture
• +3 more

Prof. Dr. Thomas Lippert is a Professor at Goethe University Frankfurt and the Director of the Jülich Supercomputing Centre (JSC) at Forschungszentrum Jülich. He leads efforts in quantum computing integration, high-performance computing (HPC), and modular supercomputing architectures. His work focuses on hybrid quantum-classical systems, supercomputer development (e.g., JUPITER, JUWELS), and enabling computational science across domains like neuroscience, materials science, and earth systems. Research Interests include quantum algorithms, quantum-classical hybrid systems, supercomputing infrastructure, and applications in quantum simulation, optimization, and AI. He spearheads projects like JUNIQ (quantum computing infrastructure) and contributes to Helmholtz Information Program initiatives. He has been instrumental in developing Europe’s first exascale system (JUPITER) and advancing quantum computing integration into HPC environments. Notable contributions include the JUWELS Booster for AI research, the QSolid quantum computing demonstrator, and interdisciplinary collaborations in neuroscience computing. He oversees JSC’s supercomputers (JUWELS, JUSUF) and storage systems, fostering industry-academia partnerships. His team addresses challenges in quantum benchmarking, error mitigation, and large-scale scientific workflows. Lippert collaborates on EU-funded projects (e.g., HPCQS) and national initiatives, driving innovation in supercomputing and quantum technologies. His work emphasizes sustainable digital infrastructure and Germany’s tech sovereignty through advanced computing.

Thomas LippertView profile

Professor

• High Performance Computing
• Quantum Computing
• Modular Supercomputing
• +3 more

Prof. Thomas Lippert is a Professor and Senior Fellow at the Frankfurt Institute for Advanced Studies (FIAS) and holds the chair for Modular Supercomputing and Quantum Computing at Goethe University Frankfurt. He serves as director of the Jülich Supercomputing Centre and holds leadership roles in the John von Neumann Institute for Computing (NIC) and Gauss Centre for Supercomputing (GCS). His research focuses on hybrid quantum-HPC systems, modular supercomputing architectures, and energy-efficient computing. Education: He earned his diploma in Theoretical Physics from the University of Würzburg (1987), followed by PhDs in theoretical physics from Wuppertal University (lattice quantum chromodynamics simulations) and Groningen University (parallel computing with systolic algorithms). Research emphasizes three pillars: energy efficiency, scalable modularity, and AI integration with HPC. Collaborations include Jülich Supercomputing Centre and FIAS. The group recently relocated to Bockenheim campus with a focus on modular datacenter design and non-von-Neumann architectures.

Estela SuarezView profile

Professor

• High Performance Computing (HPC)
• Heterogeneous HPC Architectures
• Modular Supercomputing Architecture
• +4 more

Estela Suarez is a Professor of High Performance Computing at the University of Bonn's Computer Science Department and holds leadership roles at the Jülich Supercomputing Centre (JSC) in Forschungszentrum Jülich. Her work focuses on advancing modular supercomputing architectures, heterogeneous systems, and application optimization for exascale computing. She currently serves as Chair of the EuroHPC Joint Undertaking's Research and Innovation Advisory Group (RIAG) and leads the Next Generation Architectures and Prototypes research group at JSC. Education includes a PhD in Physics from the University of Geneva (2010) and a Master's in Physics (Astrophysics specialization) from Universidad Complutense de Madrid (2004). She has held senior research positions at JSC since 2010 and has led major EU-funded projects like DEEP, DEEP-ER, and DEEP-SEA. Research interests include HPC system design, hardware-software co-design, and energy-efficient supercomputing architectures. She was awarded the University of Bonn's 2023/2024 teaching award and actively contributes to initiatives like the European Processor Initiative (EPI) and the NUMERIQS consortium. Current projects include optimizing exascale systems for Earth system modeling (IFCES2), AI-driven data analytics (AIDAS), and modular supercomputing software (DEEP-SEA). During her 2024/2025 sabbatical, she is not accepting new students. Her work is published in journals like Geoscientific Model Development and conferences such as ISC and EuroHPC.

Stefan KriegView profile

Professor

• Lattice Quantum Chromodynamics
• HPC in physics
• Simulations of strongly correlated systems
• +4 more

Professor Stefan Krieg is a distinguished physicist holding dual appointments as a Professor of Physics at the Helmholtz Institute for Radiation and Nuclear Physics of the University of Bonn and as a senior staff member at the Jülich Supercomputing Centre (JSC) at Forschungszentrum Jülich. He currently serves as Head of Division for HPC for Quantum Systems at JSC and leads the Simulation and Data Laboratory for Numerical Quantum Field Theory within the Center for Advanced Simulation and Analytics (CASA), where he also acts as speaker for the "CASA Assembly". Krieg received his PhD in physics from Wuppertal University and completed postdoctoral positions at Forschungszentrum Jülich, Wuppertal University, and MIT before establishing his current leadership roles. Professor Krieg's research program centers on lattice quantum chromodynamics (Lattice QCD) with particular emphasis on nucleon structure calculations, parton distribution functions, and the study of strongly correlated systems. His work spans both theoretical developments and practical computational implementations, with recent publications demonstrating expertise in applying machine learning techniques to address sign problems in quantum simulations. Krieg has made significant contributions to understanding hadron spectroscopy, particularly in exotic states and charmed mesons, while also advancing computational methodologies for high-performance computing systems. His research bridges theoretical physics with practical computing challenges, focusing on efficient software implementations for the Modular Supercomputing Architecture developed at JSC. Analysis of Professor Krieg's publication record reveals a sustained research trajectory focused on fundamental questions in particle and nuclear physics using lattice methods. His work shows increasing integration of machine learning approaches with traditional lattice techniques, particularly evident in recent papers addressing sign problems in quantum simulations. The research spans multiple subfields including hadron spectroscopy, nucleon structure, parton distribution functions, and computational methods for quantum field theories. Krieg frequently collaborates with international research teams, appearing as co-author on numerous multi-institutional projects that leverage high-performance computing resources for fundamental physics investigations. As Head of Division at JSC, Professor Krieg oversees significant research infrastructure and personnel dedicated to quantum systems simulation. His leadership extends to the Center for Advanced Simulation and Analytics where he coordinates the CASA Assembly. While specific grant details aren't provided in the source material, his extensive publication record and leadership positions indicate substantial research funding and collaborative projects. Krieg's work represents a critical intersection of theoretical physics, computational science, and high-performance computing infrastructure development.

Andreas LintermannView profile

Researcher

• Computational Fluid Dynamics
• High-Performance Computing
• Artificial Intelligence
• +6 more

Andreas Lintermann is a postdoctoral researcher and group leader of the Simulation and Data Lab (SDL) Fluids & Solids Engineering at the Jülich Supercomputing Centre (JSC), Forschungszentrum Jülich. His work focuses on integrating artificial intelligence with high-performance computing for fluid and solid mechanics applications. Coordinates European Center of Excellence in Exascale Computing (CoE RAISE) Leads EU-funded projects: EuroCC/EuroCC2, interTwin, SPECTRUM Co-leads EU-project HANAMI, BMBF project StroemunsRaum, and BMWK project nxtAIM Research Interests: His group develops encoder-decoder CNNs for aeroacoustic field prediction, convolutional autoencoders for flow field compression/reconstruction, and physics-informed neural networks for large-scale simulation initialization. Applications include turbulence modeling, shape optimization, and medical imaging. Technical Focus: Specializes in AI-driven multi-physics coupling, heterogeneous hardware acceleration, and super-resolution algorithms for computational fluid dynamics.

Gabriele CavallaroView profile

Associate Professor

• Remote Sensing
• Machine Learning
• High Performance Computing
• +3 more

Prof. Gabriele Cavallaro is an Associate Professor at the Faculty of Electrical and Computer Engineering, University of Iceland (since 2024) and concurrently serves as a Visiting Professor at the European Space Agency's Φ-Lab, contributing to the Quantum Computing for Earth Observation (QC4EO) initiative. He leads the Simulation and Data Lab (SDL) at the Jülich Supercomputing Centre (JSC), Forschungszentrum Jülich, Germany, focusing on AI/ML for remote sensing. Previously, he held roles as Deputy Head of the High Productivity Data Processing (HPDP) group (2016–2021), Adjunct Associate Professor at the University of Iceland's Computer Science Department (2022–2024), and Chair/Co-chair of IEEE GRSS technical committees. He earned his B.Sc. and M.Sc. in Telecommunications Engineering from the University of Trento, Italy (2011, 2013), and a Ph.D. in Electrical and Computer Engineering from the University of Iceland (2016). His research emphasizes scalable machine learning algorithms, quantum computing integration, and high-performance computing for remote sensing applications, particularly in geospatial data analysis and earth observation. Prof. Cavallaro has received the IEEE GRSS Third Prize in the Student Paper Competition (2015) . His work bridges academic and industrial collaborations, including leadership in the HDCRS and QUEST TC committees. He has organized workshops and summer schools on disruptive computing architectures and co-edited the IEEE Transactions on Image Processing (TIP) from 2022 to 2024. His roles include advancing modular supercomputing systems like the Juwels Booster and developing tools for distributed neural network training. He is also involved in initiatives such as Sen4map (semantic land-use mapping) and Prithvi (foundation models for geospatial data).

Norbert EickerView profile

Professor

• Modular Supercomputer Architecture
• HPC Middlewares
• System Architecture

Norbert Eicker serves as Professor at Bergische University of Wuppertal and Head of the Research Group "Software for Modular Supercomputers" at the Jülich Supercomputing Centre (JSC), Forschungszentrum Jülich. His research specializes in advanced computing infrastructure with core competencies in: Modular Supercomputer Architecture HPC Middlewares development and optimization High-performance System Architecture design As a Principal Investigator in Helmholtz Information Program 1, Topic 2, he contributes to Germany's national strategy for computational science advancement through the Helmholtz Association framework. His work addresses critical challenges in creating flexible, scalable supercomputing environments that can adapt to diverse scientific workloads while maintaining performance efficiency. Based at Forschungszentrum Jülich's facilities in Building 16.3, Room 203, he operates within one of Europe's premier supercomputing environments that supports multidisciplinary research across the continent.