Find Academic Supervisors

• High Performance Computing
• Resource aware programming
• Power management in HPC systems
• +2 more

Dr. Jophin John is a researcher at the Technical University of Munich's Department of Informatics, affiliated with the Chair of Computer Architecture and Parallel Systems under Prof. Martin Schulz. His work focuses on advanced HPC systems and resource management frameworks. Research Interests: Specializes in High Performance Computing with emphasis on power-aware resource allocation and fault tolerance mechanisms Develops innovative parallel programming models for elastic HPC applications Investigates invasive computing paradigms for power corridor management in supercomputing environments Project Involvement: Key contributor to the Invasive Computing project, developing frameworks for dynamic resource adaptation in heterogeneous HPC systems. His research bridges theoretical models with practical implementations in power-constrained computing environments. Teaching Contributions: Served as student tutor for Parallel Programming and IoT courses (2016-2020), and led practical sessions for Supercomputer Programming. His instructional focus emphasizes hands-on experience with modern parallel architectures and programming models.

Keerthi GaddameediView profile

Researcher

• High Performance Computing
• Parallel Programming
• Parallel-in-time methods
• +3 more

Keerthi Gaddameedi is a PhD candidate at the Department of Computer Science, Technische Universität München (TUM), affiliated with the Chair of Scientific Computing in Computer Science (SCCS). Their research focuses on High Performance Computing, Parallel Programming, and Numerics, with contributions to scalable kernel matrix approximation techniques. They actively teach courses such as Modelling and Simulation, Numerical Algorithms for HPC, and Advanced Programming. Keerthi has advised multiple student theses on topics like parallel-in-time integration and kernel matrix inversion. Education: Bachelors in Computer Science and Engineering from JNTU Hyderabad (India), Masters in Informatics from TUM. Current PhD research involves hierarchical decomposition methods for dense kernel matrices. Teaching roles span from 2022 to 2025, covering both undergraduate and graduate courses in scientific computing. Their work has been presented at venues like SIAM-PP 2024 and ISC 2024, focusing on dynamic resource management for parallel-in-time methods. Open projects include high-performance computing for time-series data and scalable linear solvers.

Markus WeinhardtView profile

Professor

• Reconfigurable Computing
• Compiler Development
• Image Processing
• +3 more

Prof. Dr.-Ing. Markus Weinhardt is a Professor at the Faculty of Engineering and Computer Science at Osnabrück University of Applied Sciences. His research focuses on reconfigurable computing, compiler development, and image processing. He earned his Ph.D. from Karlsruhe Institute of Technology (2000) and held postdoctoral positions at Imperial College London (2000) and PACT XPP Technologies AG (2009). He leads the DFG-funded HiPReP project and organizes workshops like FSP 2016. Education: Ph.D. in Computer Science (Karlsruhe Institute of Technology), postdoctoral research at Imperial College London, and industry experience at PACT XPP Technologies AG. Research Interests: Reconfigurable architectures, FPGA-based acceleration, compiler optimization, and high-performance computing. Projects include HiPReP (high-performance reconfigurable processor) and HPVis (software optimization via FPGA coprocessors). Teaching: Courses on Hardware/Software Codesign, Programming, and Master’s projects in compiler design and hardware optimization. Key Contributions: Over 30 publications, including works on CHiPReP compilers, dynamic scheduling in reconfigurable arrays, and FPGA-accelerated algorithms.

• High Performance Computing
• Energy Efficiency
• Parallel Computing
• +6 more

Laura Carrington is a researcher at the University of California, San Diego, specializing in High Performance Computing (HPC) with a focus on energy efficiency, memory management, and performance optimization. She has contributed to the development of tools like PEBIL for binary instrumentation, ADAMANT for data movement analysis, and frameworks for power management in large-scale systems. Her research spans multiple domains including ARM processor evaluation, Xeon Phi vectorization, and communication reduction in graph algorithms. Key collaborations include work with Michael Laurenzano, Allan Snavely, Ananta Tiwari, and Pietro Cicotti. Laura's work addresses critical challenges in HPC such as DVFS configuration optimization, workload colocation, and energy-aware algorithm design. While no explicit academic rank is stated, her extensive publication record across 2002-2019 in top venues like SC, IPDPS, and IJHPCA establishes her as a significant contributor to HPC research. Her work has influenced practices in system-level power management, scientific application characterization, and energy-efficient computing for both CPU/DRAM domains and emerging memory technologies.

Martin SchulzView profile

Professor

• Parallel and Distributed Architectures
• Performance Monitoring and Analysis
• Memory System Optimization
• +4 more

Prof. Martin Schulz is a Full Professor and Chair for Computer Architecture and Parallel Systems at Technische Universität München (TUM), joining in 2017. He also serves on the board of directors at the Leibniz Supercomputing Centre. Previously, he worked at Lawrence Livermore National Laboratory (LLNL) and Cornell University. His research focuses on parallel architectures, quantum computing integration, HPC optimization, and fault tolerance. He has published over 250 papers and chairs the MPI Forum, a key standard in HPC. Education: Doctorate in Computer Science (TUM, 2001), Master of Science (UIUC). Research Interests: Parallel systems, performance analysis, quantum computing, memory optimization, and tool support for HPC. Awards: Gordon Bell Award (2006), R&D 100 Award (2011), Best Paper Awards at IPDPS and SC. Grants/Projects: SEANERGYS, PlasmaPEPS, OpenCUBE, and others. Active in academic service, including program chairs for ISC, EuroMPI, and IPDPS.

Dirk PflügerView profile

Professor

• Scientific Computing
• High-Performance Computing (HPC)
• Parallel and Distributed Systems
• +3 more

Dirk Pflüger is a Professor at the University of Stuttgart's Institute of Parallel and Distributed Systems, within the Faculty of Computer Science, Electrical Engineering and Information Technology. His research focuses on high-performance computing (HPC), parallel and distributed systems, and sparse grids. He has led projects in astrophysical simulations, machine learning applications, and uncertainty quantification. Notable contributions include developing scalable algorithms for exascale computing using HPX, Kokkos, and SYCL frameworks. His expertise spans distributed computing architectures, task-based parallel programming, and interdisciplinary applications in astrophysics and medical AI. Recent work includes optimizing hyperparameter tuning, simulating stellar mergers, and enhancing blood glucose prediction models using deep reinforcement learning. Pflüger's research emphasizes performance portability, fault tolerance, and cross-platform collaboration. He has contributed to open-source tools like PLSSVM and hws, which address hardware monitoring and GPU acceleration challenges. His work bridges theoretical advancements with practical implementations for real-world computational problems.

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.

Olav ZimmermannView profile

Researcher

• Bioinformatics
• Molecular Simulation
• Markov Chain Monte Carlo
• +3 more

Olav Zimmermann serves as Team leader of Simulation & Data Laboratory "Biology" at the Jülich Supercomputing Centre (JSC), which operates within the Institute for Advanced Simulation at Forschungszentrum Jülich. He also functions as a Principal Investigator in Helmholtz Information Program 1, Topic 1, indicating his significant research responsibilities within this major German research institution. His research expertise encompasses multiple computational biology domains: Bioinformatics Molecular Simulation techniques Markov Chain Monte Carlo statistical methods Machine Learning applications for biological problems Protein Folding dynamics Python programming for High-Performance Computing environments Dr. Zimmermann's work sits at the critical intersection of advanced computing infrastructure and biological research, where he likely develops and implements sophisticated computational approaches to address complex problems in molecular biology. His leadership of the Simulation & Data Laboratory suggests responsibility for directing research strategy, managing technical resources, and facilitating collaborations between computational scientists and domain researchers in biology.

Barry LinnertView profile

Researcher

• Resource Management in Cluster and Grid Environments
• High Performance Computing (HPC)
• Operating Systems
• +2 more

Barry Linnert is a researcher at Freie Universität Berlin, affiliated with the Software Engineering research group. His work focuses on resource management in cluster and grid environments, high-performance computing (HPC), and operating systems. He also has additional interests in parallel and distributed simulations. Email: barry.linnert@fu-berlin.de | Office: Takustr. 9, Room 008, Berlin, Germany | Phone: +49 30 838 50953 Research Areas: Resource Management in Cluster/Grid, HPC, Operating Systems, Parallel/Distributed Simulations Teaching: Cluster Computing, Non-sequential Programming, Operating Systems, Software Engineering Publications (Selected): Dynamic resource allocation in HPC, Advance reservations in grid systems, Failure recovery in distributed environments, Workflow management for large-scale grids Barry Linnert actively contributes to the development of resource scheduling algorithms and grid computing architectures. His recent publications (2024-2023) address deadline-oriented job management and dynamic allocation policies in HPC systems, while earlier works (2014-2004) explore advance reservation protocols, Manhattan distance mapping, and distributed recovery mechanisms. Research spans both theoretical frameworks and practical implementations for cluster management. He holds positions in academic advisory bodies: Advisory board member of Berlin University Alliance's cooperation platform Board member of Landesvertretung Akademischer Mittelbau Berlin (LAMB)

• Bioinformatics
• Scientific Workflows
• Biomedical Natural Language Processing
• +3 more

Prof. Dr. Ulf Leser serves as Professor and Deputy Director at the Institute of Computer Science within Humboldt University of Berlin's Faculty of Mathematics and Natural Sciences. His work bridges computer science and life sciences through bioinformatics and knowledge management systems, with significant contributions to scientific workflow optimization and biomedical text mining. His research spans multiple high-impact areas: Bioinformatics and precision oncology tool development (e.g., OncoTagger for cancer gene curation) Scientific workflow systems with focus on carbon-aware execution and energy efficiency Biomedical natural language processing for relation extraction and knowledge base curation Advanced time series analysis methods (e.g., ClaSP for segmentation) Environmental monitoring through satellite data analysis He actively develops infrastructure for reproducible scientific computing while addressing sustainability challenges in HPC environments. Recent publications (2023-2026) reveal three dominant trends: (1) Integration of explainable AI in healthcare assessment systems, (2) Sustainable computing approaches for scientific workflows including carbon-aware scheduling, and (3) Advancement of biomedical text mining through knowledge-augmented language models. His work consistently targets real-world applications in precision medicine and environmental science. Prof. Leser currently supervises students including Michael Piechotta (Diplom in Bioinformatics, defense scheduled September 2025). As Deputy Director and Faculty Council member, he shapes institutional research strategy while leading projects at the intersection of computer science and life sciences. His group maintains active collaborations with biomedical research institutions and contributes to community standards in scientific workflow systems.

• High Performance Computing
• Energy Efficiency
• Data Center Operations
• +3 more

Dr. Torsten Wilde is a researcher at Technical University Munich , Germany, with a focus on High Performance Computing (HPC) and Energy Efficiency in data centers. His work spans over a decade, integrating Machine Learning , Simulation and Modeling , and Operational Data Analytics to optimize HPC systems.

• Data Science
• Climate Science
• Oceanography
• +3 more

Prof. Dr. Stephan Frickenhaus is a Professor and Head of the Computing and Data Centre at the Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research. His primary affiliation is with the Bremerhaven Site, where he leads the Computing Division and oversees High-Performance Computing (HPC) infrastructure. His research focuses on Cluster Analysis, Big Scientific Data Analytics, and sustainable data science infrastructures. He actively contributes to interdisciplinary projects like the MOSAiC Arctic expedition and the Digital Earth initiative, emphasizing data integration and FAIR principles. Key responsibilities include managing HPC resources, developing data management frameworks, and advancing collaborative digital ecosystems in Earth System Science. His work bridges computational methods with environmental research, addressing challenges in climate modeling, oceanography, and cryosphere dynamics. Prof. Frickenhaus is also involved in policy and steering groups such as the Steering Group Digital Earth and HIDA-Steer, promoting data-driven scientific advancements. Research interests span data science applications in polar and marine environments, with publications emphasizing Arctic ecosystem studies, HPC optimization, and AI-driven climate analysis. His contributions to projects like MOSAiC underscore his expertise in large-scale data collection and analysis, ensuring scientific data remains accessible and reusable for future research.

Hartwig AnztView profile

Professor

• High-Performance Computing
• Sparse Linear Algebra
• Iterative Methods
• +6 more

Prof. Hartwig Anzt is a Professor at TU Munich, leading the Chair of Computational Mathematics within the TUM School of Computation, Information, and Technology. He also holds a professorship at the University of Tennessee and directs the Innovative Computing Lab (ICL). His research focuses on high-performance computing, particularly in sparse linear algebra, iterative methods, Krylov solvers, and preconditioning. He emphasizes sustainable software development and leads the Ginkgo open-source library for scientific computing. Academically, Anzt earned his PhD in 2012 from the Karlsruhe Institute of Technology (KIT) and led a Helmholtz junior research group there. He has extensive collaborations with institutions like Sandia National Laboratories, Argonne National Laboratory, and the University of Tennessee. His software projects include Ginkgo and MAGMA-sparse, both part of the xSDK ecosystem. Recent talks highlight his work on exascale computing, GPU optimization, and software sustainability. He advocates for platform-portable numerical libraries and has contributed to the Exascale Computing Project (ECP). His research addresses challenges in energy efficiency, fault tolerance, and algorithm design for multi/manycore architectures.

Daniel PflugfelderView profile

Researcher

• Plant Biology
• Agricultural Science
• Medical Imaging
• +7 more

Daniel Pflugfelder is a Researcher at the Plant Sciences (IBG-2) department of the Institute of Bio- and Geosciences at Forschungszentrum Jülich. His work focuses on developing non-invasive imaging tools to study plant root systems, carbon dynamics, and water uptake using Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET) . He is based in Jülich, Germany, and his research supports sustainable agriculture and bioeconomy goals. Expertise: Plant research, Magnetic Resonance, 3D Data analysis, Positron Emission Tomography, Root research His research integrates molecular, physiological, and ecological approaches to analyze plant-environment interactions and develop technologies for alternative biomass utilization. He has contributed to plant phenotyping tools like phenoPET and phenoVein , enabling precise studies of root architecture, carbon allocation, and water fluxes in crops such as sugar beet, maize, and wheat. Daniel's publications emphasize multimodal imaging techniques , particularly MRI-PET co-registration , to explore heterogeneous carbon distribution, root hydropatterning, and symbiotic interactions in legumes. His work addresses challenges in quantifying root water uptake, soil-root interactions, and climate adaptation strategies in agriculture. Key applications of his research include improving resource efficiency in crops and understanding plant responses to drought stress and warming scenarios. He has also contributed to computational tools for image processing and radiation therapy optimization in earlier works.

Michael GerndtView profile

Professor

• Cloud Computing
• Internet of Things (IoT)
• High Performance Computing (HPC)
• +11 more

Prof. Dr. Michael Gerndt is a Full Professor at the Chair of Computer Architecture and Parallel Systems , School of Informatics, Technische Universität München (TUM). His research focuses on cloud and IoT systems, high-performance computing (HPC), and performance analysis tools for parallel/distributed systems. Current projects: SEANERGYS , PlasmaPEPS , OpenCUBE , and MUNIQC-ATOMS Past projects: AutoTune , READEX , InvasIC , and CrossGrid Research Highlights: Developed the Periscope Tuning Framework and iOMP (OpenMP extension for invasive computing) Pioneering work in performance analysis, energy efficiency, and resource management in HPC and cloud systems Focus on AI-driven cloud operations, quantum-HPC integration, and hardware accelerators for machine learning Scientific Awards: Outstanding Paper Award, IEEE SC2 Symposium (2017) Teaching Contributions: Lectures: Parallel Programming Systems , Advanced Computer Architecture , Cloud Computing Lab courses: Efficient Programming of Multicore Processors , IoT Sensor Nodes Seminars: Hardware Accelerators for AI , Quantum Computing Integration Education & Career: PhD in Computer Science (1989, University of Bonn), postdoc at University of Vienna (1990-1991), habilitation at TUM (1998), Professor at TUM since 2000.