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Carlos Daniel Gonzalez CalazaView profile

Researcher

• Quantum Computing
• Quantum Annealing
• Cloud-based Quantum Computing
• +2 more

Carlos Daniel Gonzalez Calaza serves as a Researcher and JUNIQ Lead Developer at the Jülich Supercomputing Centre (JSC), Forschungszentrum Jülich, where he has led quantum computing infrastructure development since 2019. Concurrently pursuing his PhD since 2022 under Prof. Dr. Kristel Michielsen in the Quantum Information Processing group, he bridges practical platform development with theoretical research in hybrid quantum systems. His research expertise spans: Quantum Computing infrastructure design Quantum Annealing benchmarking methodologies Cloud-based quantum access systems HPC-quantum integration frameworks Hybrid quantum-classical optimization for industrial applications Current research funding is secured through: EuroHPC JU project HPCQS (High Performance Computer – Quantum Simulator hybrid) German project QSolid (Quantum Computer in the Solid State) with prior contributions to the OpenSuperQ initiative. These projects enable cutting-edge work on quantum platform development and hardware validation. As a PhD candidate, he does not supervise students but offers collaboration opportunities through the Quantum Information Processing group's infrastructure projects. The group's flagship JUNIQ platform provides cloud access to quantum devices and integrates them with JSC's supercomputing resources, positioning it as a European leader in practical quantum computing deployment.

Andreas HertenView profile

Researcher

• High-Performance Computing (HPC)
• GPU Programming
• Parallel Computing
• +6 more

Andreas Herten is a Researcher at the Jülich Supercomputing Centre (JSC) within Research Center Jülich GmbH. He serves as Co-Lead of the Novel System Architecture Design division and heads the ATML Accelerating Devices group, focusing on GPU programming, parallel computing, and high-performance computing (HPC) optimizations. Key Expertise: GPU programming, parallel algorithms, HPC systems, benchmarking, Python, LaTeX Research Focus: Accelerating scientific applications on GPUs, European exascale initiatives, AI workload evaluation, and heterogeneous computing architectures His recent publications highlight advancements in GPU-accelerated materials science, AI training on HPC systems, and exascale benchmarking. Herten contributes to projects like OpenGPT-X, JUPITER, and CARAML, with work spanning computational physics, environmental science, and machine learning applications.

Edgar Landinez BordaView profile

Researcher

• Quantum Physics
• Statistical Physics
• High-Performance Computing (HPC)
• +3 more

Dr. Edgar Landinez Borda is a researcher at the Jülich Supercomputing Center (JSC) , Forschungszentrum Jülich GmbH. His work focuses on high-performance computing (HPC), quantum physics, and statistical physics, with a strong emphasis on quantum Monte Carlo methods and electronic structure theory. Research Areas: Quantum Monte Carlo simulations, machine learning integration in quantum physics, and computational modeling of many-body systems. Key Contributions: Development and optimization of quantum Monte Carlo software (e.g., QMCPACK), charge density prediction models, and finite-size extrapolation techniques. Collaborations: Engaged in open-source quantum chemistry library projects like TREXIO. His recent publications highlight advancements in quantum simulation accuracy, machine learning applications for many-body systems, and scalable computational methods for materials science.

Carolin PenkeView profile

Researcher

• High-Performance Computing
• Artificial Intelligence
• Large Language Models
• +5 more

Dr. Carolin Penke is a researcher at the Jülich Supercomputing Centre (JSC) of Forschungszentrum Jülich GmbH . She leads projects in training large language models (LLMs) on high-performance computing (HPC) systems as part of the OpenGPT-X initiative and the Accelerating Devices Lab . Current focus: HPC-AI integration , memory-efficient LLM training , and accelerator evaluation Prior work: numerical linear algebra and mathematical algorithm development for quantum chemistry Her research spans computational mathematics, artificial intelligence, and high-performance computing. Key contributions include: Developing CARAML for AI workload evaluation Creating JUPITER benchmark suite for exascale systems Optimizing low-rank representations in deep learning Advancing pseudosymmetric matrix algorithms for physics simulations Designing GPU-accelerated numerical methods for eigenvalue problems Her work bridges mathematical rigor with practical AI/HPC applications, emphasizing scalability , energy efficiency , and European sovereignty in AI .

Jan Andre ReuterView profile

Research Fellow

• High Performance Computing
• Parallel Computing
• GPU Programming
• +3 more

Jan Andre Reuter serves as a Research Fellow and Software Developer at the Jülich Supercomputing Centre (JSC), part of Forschungszentrum Jülich in Germany. His role centers on developing high-performance computing solutions for scientific research infrastructure. His core research interests include: High Performance Computing (HPC) architectures GPU acceleration techniques Parallel programming models Scientific software engineering Specializing in C++, Python, CUDA, OpenACC, and OpenMP, he contributes to optimizing computational workflows for Europe's leading supercomputing facilities. His work enables efficient execution of complex scientific simulations across diverse research domains requiring massive computational power. As a key member of JSC's technical team in Building 16.3, he supports advanced computing resources that drive innovation in climate modeling, materials science, and computational neuroscience through cutting-edge software development.

Asma SemcheddineView profile

Researcher

• Deep learning
• Artificial intelligence (AI)
• Climate science
• +3 more

Dr. Asma Semcheddine is a postdoctoral researcher at the Jülich Supercomputing Center (JSC) within Research Center Jülich GmbH. Her work focuses on the intersection of climate science and deep learning, leveraging high-performance computing (HPC) resources to advance AI applications for Earth-related challenges. Key areas of expertise include: Deep learning Artificial intelligence Climate science Machine learning Remote sensing She is affiliated with the Earth System Data Exploration team and Large Scale Data Science division, conducting research at the frontier of computational methods and environmental science.

Dennis WillschView profile

Researcher

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

Dennis Willsch is a Senior Researcher in the Quantum Information Processing group at the Jülich Supercomputing Centre (JSC) , Forschungszentrum Jülich. He earned his PhD in Physics from RWTH Aachen University in 2020. Research Interests: Quantum computing, quantum annealing, simulation of quantum computers, GPU programming, high-performance computing (HPC), and machine learning. Lectures: Quantum Computing: Concepts and Algorithms SS 25 (English), Quantum Computing WS 24/25 (German), Quantum Computing WS 23/24 (German). Selected Talks: Future of HPC (IHPCSS 2024); Observation of Josephson Harmonics in Tunnel Junctions (IBM Qiskit Seminar 2023, WACQT Workshop 2023); Guided Quantum Walk (INQA Conference 2023); Applications on Quantum Annealers (INQA Conference 2022, 4DQV Lecture Series 2021); Benchmarking GPU Clusters (GPU Tech Conference 2021). He works on simulating quantum systems using supercomputers and contributes to the development of quantum algorithms and applications.

Herwig ZilkenView profile

Lecturer

• Visualization of Scientific Data
• Photo/Video Production
• High-Performance Computing
• +2 more

Dr. Herwig Zilken is the Head of ATML Visualization & Interactive HPC at Forschungszentrum Jülich, specializing in the visualization of scientific data and multimedia production. He also teaches courses in visualization at the FH Aachen University of Applied Sciences. Expertise: Scientific data visualization, photo/video production, and high-performance computing. Institutional Affiliation: Forschungszentrum Jülich (Jülich Supercomputing Centre) and FH Aachen University of Applied Sciences.

Stefan GeislerView profile

Professor

• Human-Machine Interaction
• Natural User Interfaces
• Usability Engineering
• +6 more

Stefan Geisler is a Professor at Ruhr West University of Applied Sciences since 2010. He holds the professorship for Applied Computer Science / Human-Machine Interaction and serves as Program Director for the Human-Technology Interaction program. Since 2016, he has led the Positive Computing Research Institute , contributes to the Intelligent Mobility research program , and directs the Media and Interaction Department in the North Rhine-Westphalian doctoral program. Research Focus: Human-Machine Interaction (HMI), Natural User Interfaces (NUI), Usability Engineering, Automotive HMI, and Intelligent Mobility. Projects: Golden Rules in Automotive HMI, PARCURA (smart glasses in hospitals), UsAHome (home HMI systems), BMBF-funded AHA project (safety-critical interfaces), and intercultural/intergenerational innovation development. Collaborations: FH Struktur, IQPC Conference, CAMO network, and North Rhine-Westphalian doctoral program. Teaching: Covers the entire usability engineering lifecycle, emphasizing user testing integration and intuitive interface design. Publication Trends: Focus on automotive HMI optimization, gesture-based interaction, user experience in mobility systems, and human-centered design for safety-critical applications. Subfields include driver assistance systems, natural user interfaces in automated vehicles, and usability testing methodologies. Leadership: Directs the Positive Computing Research Institute and the Media and Interaction Department. Supervises doctoral research in intercultural innovation and automotive NUI development.

Wojciech KowalczykView profile

Professor

• Biomechanics
• Biofluid mechanics
• Thermo-fluid mechanics
• +5 more

Prof. Dr.-Ing. Wojciech Kowalczyk serves as Professor of Mechanics/Biomechanics and Chairholder of the Chair of Mechanics and Robotics at the Department of Mechanical Engineering and Process Engineering, Faculty of Engineering Sciences, University of Duisburg-Essen, Germany, a position he has held since November 2007. His academic journey includes: University of Duisburg-Essen (since 11/2007): Chair of Mechanics and Robotics, Professor for Mechanics/Biomechanics Friedrich-Alexander-University of Erlangen-Nuremberg (10/2006 - 11/2007): Group Leader in Computational Fluid Dynamics and Theoretical Process Fluid Mechanics Technical University of Munich (10/2004 - 09/2006): Group Leader in Fluid Mechanics; awarded Doctoral Degree (Dr.-Ing.) in July 2004 Koszalin University of Technology (Poland) (10/1997 - 07/2001): Research Associate at Chair of Control System; received Diploma in Mechanical Engineering in July 1997 Professor Kowalczyk's research spans critical domains including Biomechanics , Biofluid mechanics , Thermo-fluid mechanics , Multiphase flow (with phase changes and particle dynamics), Computational Fluid Dynamics (CFD) , Computational Structural Dynamics (CSD) , Fluid-Structure Interaction (FSI) , and High Performance Computing (HPC) , emphasizing advanced simulation techniques for complex engineering challenges. He actively teaches core courses such as Mechanics 1-3, Biomechanics, Biofluidmechanics, and Finite Element Method across semesters while leading the Computational Sciences and Simulation (CSS) research group and contributing to the Center for Energy Research (CER.UDE).

Bengisu ElisView profile

Researcher

• High-Performance Computing (HPC)
• Parallel Computing
• GPU Programming
• +5 more

Bengisu Elis is a researcher at the Chair of Computer Architecture & Parallel Systems at the Technical University of Munich . Her work focuses on High-Performance Computing (HPC) , GPU programming, and parallel systems. Email: bengisu.elis@tum.de Room: 01.04.037, Garching near Munich Research Interests : Elis specializes in GPU-CPU parallelism , MPI profiling , and performance modeling for HPC systems. Her work addresses challenges in: Optimizing synchronization mechanisms Reducing memory access overhead Enhancing task scheduling Scientific Awards : HPCAsia '24 Best Paper Award Winner Teaching & Advising : Elis has supervised multiple master's theses and internships, including: Jakob Schäffeler (2025) - Comparing GPU Programming Models Tizian Leonhardt (2024) - Low-overhead Sampling Techniques

• High-Performance Computing
• Automatic distributed memory parallelization
• Communication optimization for CPUs and GPUs
• +9 more

Anna Mittermair is a researcher at the Chair of Computer Architecture & Parallel Systems at the Technical University of Munich . She is actively involved in teaching and research related to High-Performance Computing (HPC) systems. Teaching Roles : Lab Course Computer Architecture (IN0005), Aspects of Low-Level Programming for Games Development (IN0035) Current Projects : SEANERGYS (EuroHPC), PlasmaPEPS, OpenCUBE, ScalNEXT, and others focused on HPC, quantum computing, and AI hardware. Research Focus : Her work emphasizes automatic distributed memory parallelization and communication optimization for CPUs and GPUs , particularly in ocean models and HPC infrastructure. She supervises thesis topics centered on latency hiding schemes and code block order analysis for performance optimization. Collaborations & Infrastructure : Anna contributes to software projects like QMPI , MOVE-II , and SWEET , leveraging hardware such as CAPS Cloud and HimMUC . She is also affiliated with organizations like the MPI Forum Virtual Institute and Eurolab4HPC .

• Biomimetic Robotics
• Neurorobotics
• Spiking Neural Networks
• +5 more

Benedikt Feldotto is a Researcher at the Technical University of Munich, affiliated with the Department of Computer Science, Chair of Robotics, Artificial Intelligence and Real-Time Systems led by Prof. Knoll. He works on the Neurorobotics Platform as part of the European Human Brain Project and serves as lead developer of the NRP Robot Designer since 2017. His educational background includes a Bachelor of Engineering in Mechatronics from Baden-Wuerttemberg Cooperative State University (DHBW) with industry experience in automation pre-development, including a development stay in the USA. He further specialized with a Master of Science in "Robotics, Cognition, Intelligence" at Technical University of Munich. Feldotto's research focuses on biomimetic learning in neurorobotic systems, with particular emphasis on spiking neural networks for embodied cognition. His work bridges cognitive neuroscience and robotics, exploring how robots can interact naturally with humans and environments through biologically-inspired learning mechanisms. Key areas include musculoskeletal modeling, human-robot interaction, and the ethical implications of learning robots in society. He actively develops simulation tools to enable large-scale neurorobotic experiments and has contributed significantly to the Human Brain Project's Neurorobotics Platform infrastructure. His publication record shows a clear progression from foundational platform development toward increasingly sophisticated embodied simulations using high-performance computing. Recent work emphasizes scaling spiking neural networks for robotic control, analyzing neural network architectures for specific motor tasks, and validating biomechanical models against human movement data. The research consistently connects theoretical neuroscience with practical robotics applications. His scientific recognition includes: Best Poster Award from the Graduate School of Bioengineering (2018) As an educator, Feldotto has taught Cognitive Systems course exercises from Spring Semester 2018 through Spring Semester 2022. He regularly offers thesis and project opportunities in biomimetic robotics and neural network learning, though no current openings are listed. His teaching and research are supported through the European Human Brain Project funding framework. Feldotto leads development of the NRP Robot Designer, a critical tool within the Neurorobotics Platform ecosystem. He has presented this work internationally through workshops at major conferences including the European Robotics Forum and Japanese Neural Network Society meetings. His outreach extends to public exhibitions at the Deutsches Museum and participation in ethics discussions on robot stereotypes, demonstrating commitment to both technical advancement and societal implications of neurorobotics research.

Matthias MayrView profile

Lecturer

• Computational Mechanics
• Fluid-Structure Interaction
• High Performance Computing
• +6 more

Dr. Matthias Mayr is a Senior Researcher & Lecturer at the University of the Bundeswehr Munich, where he heads the Data Science & Computing Lab. He holds a permanent position at the Institute for Mathematics & Computer-Based Simulation and maintains affiliations with the RISK Research Center. Previously, he was a Postdoctoral Researcher at Sandia National Laboratories and TU München. His research focuses on coupled multiphysics problems including fluid-structure interaction, computational contact mechanics, and high-performance numerical methods. He develops monolithic coupling schemes, parallel solvers, and adaptive algorithms for large-scale simulations. Key application areas include biomedical engineering, cardiovascular mechanics, and materials science. His publications demonstrate consistent focus on computational mechanics innovations, particularly in developing efficient algorithms for multiphysics problems. Recent work emphasizes mortar methods, multigrid preconditioners, and HPC implementations for complex coupled systems. Scientific Awards: Robert J. Melosh Medal (Duke University, 2017) Multiple scholarships including Max-Weber-Programm (Bavaria, 2008-2010) Rudolf Diesel Award (TU München, 2009) He advises students in computational mechanics and HPC topics, supervising projects on multigrid methods, contact algorithms, and parallel FSI solvers. He contributes to major scientific software including Trilinos and 4C Multiphysics. He leads the Data Science & Computing Lab and participates in international research collaborations. He maintains memberships in GAMM, SIAM, IACM, and EUROMECH.

• High-Performance Computing
• Parallel Computing
• Distributed Systems
• +3 more

Christian Terboven is a Professor at RWTH Aachen University, affiliated with the Chair of High-Performance Computing (Informatik 12) at the IT Center. He is based in Aachen, Germany, and his work focuses on advanced computational systems. Research Interests: High-Performance Computing (HPC) architectures Parallel and distributed computing paradigms Scientific computing applications Performance optimization of computational workflows Computer architecture design Energy-efficient computing Contact Information: Email: terboven@itc.rwth-aachen.de Address: Kopernikusstr. 6, 52074 Aachen, Germany Phone: +49 241 80-24375