جست‌وجوی استاد و پژوهشگر

• Data Science
• Climate Science
• Oceanography
• +۳ مورد دیگر

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.

• High-Performance Computing
• Parallel I/O Systems
• Scientific Computing
• +۳ مورد دیگر

Venkatram Vishwanath is a Professor in the Department of Computer Science at the University of Illinois at Urbana-Champaign (UIUC), affiliated with the College of Engineering. His research focuses on high-performance computing (HPC), parallel I/O systems, machine learning applications, and scientific computing. He has contributed to advancing scalable data management, performance optimization on supercomputers, and interdisciplinary projects such as the HACC cosmological simulation framework. Collaborations with institutions like Argonne National Laboratory highlight his work in bridging computational science with practical applications. Key areas of expertise include topology-aware data aggregation, GPU performance modeling, and accelerating I/O operations for large-scale simulations. His work on frameworks like vl3 and PIDX has improved parallel data handling and visualization. Awards and recognitions are not explicitly listed in the provided data, but his extensive publication record and leadership in HPC projects reflect significant contributions to the field.

Sebastian Wernerمشاهده پروفایل

استاد

• Serverless Cloud Computing
• Distributed Cloud Applications
• Sustainability in Distributed Systems
• +۳ مورد دیگر

Dr.-Ing. Sebastian Werner is an Acting Professor leading the SWK research group at the University of Hamburg (UHH) since October 2024. He holds a PhD from TU Berlin's Information Systems Engineering group and has extensive experience in postdoctoral research and teaching. His academic focus lies in serverless computing, distributed systems, and cloud-native architectures. He teaches modules such as SE 1, SEE, and SWA at UHH, ensuring continuity in the SWK group's educational offerings. Research Interests: Sebastian’s work emphasizes sustainability, maintainability, and trustworthiness in distributed architectures. He has contributed to EU projects like TEADAL and DITAS, exploring cloud continuum data management and serverless platforms. His dissertation, 'Serverless Data Processing: Application Platform (Co-) Design,' highlights his expertise in scalable computing solutions. Key Projects: Includes the BMBF-funded SMILE project (2020), focusing on serverless migration and cloud application measurement. His research spans fog computing, blockchain-based systems, and edge performance benchmarking. Awards: Received the BMBF Software Campus - SMILE project award in 2020. Grants & Collaborations: Active in EU-funded initiatives and industry collaborations, such as the Gaia-X 4 Future Mobility project. His team at SWK includes researchers like Stephanie Schulte, Leif Bonorden, and Alireza Hakamian.

Katinka Wolterمشاهده پروفایل

استاد

• Dependable Distributed Systems
• Stochastic Models
• Performance Evaluation
• +۶ مورد دیگر

Prof. Katinka Wolter is a Professor at Freie Universität Berlin's Department of Mathematics and Computer Science, leading the Dependable Distributed Systems group. Her research focuses on adaptive and resilient distributed computing systems, leveraging stochastic models and machine learning. She is the Erasmus Coordinator for international student exchanges and serves on the department board and exam committee. Education: PhD in Computer Science (TU Berlin, 1999), Habilitation in Computer Science (Humboldt University Berlin, 2008). Previous roles include Visiting Professorships at Imperial College London and Cochin University, and positions at Newcastle University and Humboldt University. Research Interests: Evaluating dependability, performance, and security of complex systems, stochastic modeling, fault-tolerance, blockchain technology, and phase-type distributions. Tools developed include HyperStar and HyperStarC for distribution fitting. Awards: Best Paper Awards at ICPE 2015 and QEST 2004, DFG-funded research projects, and recognition as a top reviewer for the Journal of Systems and Software. Grants: Multiple DFG-funded projects on system evaluation and service-oriented architectures. Collaborations with institutions like Imperial College London and Technical University Budapest. Labs/Teams: Head of Dependable Systems Group, managing projects on cryptocurrency analysis, distributed restart algorithms, and mobile offloading systems.

Simon Portegies Zwartمشاهده پروفایل

استاد

• Computational Astrophysics
• Gravitational Dynamics
• Stellar Evolution
• +۴ مورد دیگر

Simon Portegies Zwart is a Professor of Computational Astrophysics at Leiden University's Leiden Observatory (Sterrewacht Leiden). His research focuses on computational gravitational dynamics, stellar evolution, and supercomputing applications in astrophysics. He leads the AMUSE software framework project, enabling multi-domain astrophysical simulations. He holds editorial roles at the Journal of Computational Astrophysics and is a member of the Royal Netherlands Academy of Arts and Sciences (KHMW). Education: PhD in Astrophysics (Utrecht University) Research Interests: His work spans numerical stellar dynamics, galaxy evolution, and high-performance computing. Notable contributions include simulating star cluster dynamics, supermassive black hole interactions, and planetary system formation. He emphasizes sustainable computational practices and interdisciplinary software development. Key Contributions: Developed the Starlab, AMUSE, and OMUSE software packages Recipient of the HPC Innovation Excellence (2020) and SURF Innovation Challenge (2015) awards Advising & Grants: Supervises multiple PhD candidates and postdocs, focusing on computational astrophysics and oceanography. Collaborates with institutions like RIKEN (Japan) and the Massachusetts Institute of Technology (MIT). Labs & Teams: Leads the Computational Astrophysics group at Leiden, specializing in gravitational dynamics and multi-physics simulations.

Alberto Leonardiمشاهده پروفایل

پژوهشگر ارشد

• Nano-materials for energy and sustainability
• Scattering and diffraction methods
• Multiscale simulation
• +۵ مورد دیگر

Dr. Alberto Leonardi is a Beamline Scientist at Diamond Light Source Ltd. (UK) and holds a Habilitand position at Friedrich-Alexander Universität Erlangen-Nürnberg (Germany) . His research focuses on nano-materials for energy and sustainability, combining experimental scattering techniques with multiscale simulations. He specializes in developing high-performance algorithms for simulating diffraction patterns of large atomistic models, as demonstrated by the ROSE-X software. Education: University of Trento (Italy) Indiana University Bloomington (USA) Friedrich-Alexander-Universität Erlangen-Nürnberg (Germany) Key Research Areas: Structure-property relationships in nanomaterials Diffraction-based analysis and simulation High-performance computing (HPC) for materials modeling Leonardi’s work emphasizes linking experimental observations with computational models to study material kinetics, mechanical properties, and chemical sensitivity. He has developed innovative methods for analyzing structural defects and disorder in nano-polycrystalline materials. His ROSE-X software enables rapid simulation of diffraction patterns for systems with millions of atoms, leveraging parallel computing on CPU/GPU clusters. He has taught at academic and high-school levels, emphasizing interdisciplinary approaches. His international collaborations span diverse institutions, including the Rutherford Appleton Laboratory (UK).

• Neuroscience
• Computer Science
• Neurobiology
• +۲ مورد دیگر

Jan-Harm Betting is a Researcher at Erasmus MC, where he conducts interdisciplinary research spanning neuroscience and computer science. His primary affiliations center on computational approaches to neural systems and high-performance computing applications. His research integrates Neuroscience and Computer Science, focusing on: Neuroscience: Purkinje cell dynamics, neural oscillations, sensorimotor integration, and rodent behavioral analysis. Computer Science: Deep-learning algorithms, high-performance computing optimization, and computer-vision techniques for biomedical data. Publications from 2020–2023 reveal a consistent focus on developing computational tools for neuroscience, including whisker-tracking algorithms for rodent behavior studies and resource-management systems for cloud HPC. His work frequently combines empirical neural data with advanced computational modeling. He collaborates internationally, as evidenced by multi-institutional research networks and co-authored publications with peers across neuroscience and engineering disciplines.

Jean-Pierre Hickeyمشاهده پروفایل

دانشیار

• Multiphysics Simulations
• Turbulent Simulations (LES/DNS)
• High-speed Aerothermodynamics
• +۴ مورد دیگر

Associate Professor Jean-Pierre Hickey at the University of Waterloo specializes in multiphysics simulations, turbulence modeling, high-speed aerothermodynamics, and acoustics. His research focuses on LES/DNS simulations, supercritical mixing, and thermoacoustic coupling. He holds a Ph.D. in Mechanical Engineering from the Royal Military College of Canada and has postdoctoral experience at Stanford University's Center for Turbulence Research and the German Aerospace Center (DLR). Education: 2012: Ph.D., Mechanical Engineering, Royal Military College of Canada 2007: M.Sc., Computational Mechanical Engineering, TU-Darmstadt 2004: Bachelor's, Mechanical Engineering, École Polytechnique de Montréal His research interests span turbulent flows, hypersonic aerodynamics, and combustion processes. He has authored over 50 publications, including studies on shock-turbulence interaction, transpiration cooling, and particle clustering in turbulent flows. His work bridges computational fluid dynamics (CFD), experimental validation, and machine learning for aerospace and environmental applications. In 2019, he received an award for excellence in teaching and scholarship. He teaches advanced fluid mechanics courses (ME 351, ME 566, ME 664) and mentors graduate students in experimental and computational fluid dynamics. His lab (www.mpilab.ca) focuses on developing novel methodologies for turbulence modeling and flow control. Awards: 2019 University Excellence Award for Teaching and Scholarship Current research includes in-situ resource utilization for space applications, deep learning for acoustic source localization, and turbulence modeling for hypersonic flows. He collaborates on projects funded by NASA and the Canadian Space Agency, aiming to advance propulsion systems and thermal protection technologies.

Erik Schnetterمشاهده پروفایل

استاد مدعو

• Computational Science
• High-Performance Computing (HPC)
• Scientific Software Development
• +۳ مورد دیگر

Erik Schnetter is the Research Technologies Group Lead at the Perimeter Institute for Theoretical Physics in Waterloo, Canada, and holds adjunct professorships at the University of Waterloo's Department of Physics & Astronomy, the University of Guelph's Department of Physics, and Louisiana State University's Center for Computation & Technology. His research focuses on computational science, high-performance computing (HPC), and developing tools for scientific collaboration and application development. His expertise includes numerical relativity, gravitational physics, and quantum field theory in curved spacetime. He has contributed to major projects like the Einstein Toolkit and AsterX, advancing GPU-accelerated simulations for astrophysical phenomena such as black hole mergers and core-collapse supernovae. Schnetter’s work emphasizes bridging HPC communities and improving accessibility to computational infrastructure. Key Awards: 1st place in the 2009 IEEE International Scalable Computing Challenge. Teaching: Regularly teaches Numerical Methods (PHYS 777) at the University of Waterloo, covering topics like computational physics and relativity. Software Contributions: Leads development of open-source tools for HPC and relativistic simulations. His recent work explores GPU-accelerated algorithms, quantum field localization, and black hole echo modeling, reflecting his dual focus on foundational physics and computational innovation.

• Computer Architecture
• Reliable Computer Design
• Fault Detection and Recovery
• +۳ مورد دیگر

Gülay YALÇIN is an Assistant Professor at Abdullah Gul University since 2016. She holds a Ph.D. in Computer Architecture from Universitat Politècnica de Catalunya (2014), an MS in Computer Engineering from TOBB University (2007), and a BS in Computer Engineering from Hacettepe University (2003). Her research focuses on reliable computer design, fault detection, parallel architectures, and low-power systems. She has led projects like ParaDIME (2012-2015) and Velox (2008-2011), advancing energy-efficient computing and transactional memory. Education: Ph.D., Universitat Politècnica de Catalunya, Department of Computer Architecture (2008-2014) M.S., TOBB University of Economics and Technology, Computer Engineering (2007) B.S., Hacettepe University, Computer Engineering (2003) Research Interests: Her work spans fault-tolerant computing, energy-efficient designs, hardware transactional memory, and parallel architectures. She has contributed to error detection techniques leveraging comparators, voltage scaling for reliability, and novel cache designs like Flexicache. Key Projects: ParaDIME (2012-2015): Energy minimization in data centers. Shortlisted for the 2016 Innovation Radar Prize. Velox (2008-2011): Transactional memory for multi-core systems. Reliable Embedded Processors (2007-2008): Fault mitigation in embedded systems. Teaching: She teaches undergraduate courses on 'Exploring Profession' and graduate courses on 'Computer Architecture.' Advising: Currently advising M.S. student Albert Njoroge Kahira on reliable microarchitecture design. Labs/Teams: Active in the Barcelona Supercomputing Center (BSC) during her postdoc (2014-2015) and as a graduate researcher (2009-2014).

Terrance M. Figyمشاهده پروفایل

دانشیار

• Theoretical Particle Physics
• High Energy Physics
• Collider Physics
• +۳ مورد دیگر

Terrance M. Figy is an Associate Professor and Director of High-Performance Computing (HPC) at Wichita State University, within the Department of Mathematics, Statistics, and Physics at the Fairmount College of Liberal Arts and Sciences. His research focuses on theoretical particle physics, particularly in Higgs boson physics, collider physics, and computational methods for high-energy physics experiments. Figy earned his B.S. in Physics and Mathematics from the University of Wisconsin-Eau Claire (2000) and his Ph.D. in Physics from the University of Wisconsin-Madison (2006). He held postdoctoral positions at Durham University, CERN, and the University of Manchester before joining Wichita State in 2015. His work emphasizes precision calculations in particle physics, including QCD corrections to Higgs production processes and the development of computational tools like VBFNLO for vector boson fusion simulations. He has contributed to studies at the LHC and explores future collider potential, such as muon collider research. His recent efforts focus on Higgs boson interactions and triplet model scenarios at high-energy colliders.

Majid Salimibeniمشاهده پروفایل

پژوهشگر ارشد

• High Performance Computing
• Parallel Computing
• Message Passing in Large-scale HPC systems
• +۶ مورد دیگر

Majid Salimibeni is a PostDoc Researcher and Research Fellow at Vienna University of Technology (TU Wien) , affiliated with the Parallel Computing research unit. He previously held a Postdoc position at the Department of Computer Science at the University of Salerno, Italy (2024), and has been a visiting researcher at TU Wien (2023). Currently based in Vienna, Austria, his work focuses on High Performance Computing (HPC) and its interdisciplinary applications. Education: Ph.D. in Computer Science, University of Salerno, Italy (2020–2024) M.Sc. in Computer Engineering (Software), Shiraz University, Iran (2017–2020) B.Sc. in Computer Engineering (Software), University of Birjand, Iran (2012–2016) Salimibeni's research explores High Performance and Parallel Computing , with a focus on optimizing GPU communication via NCCL , improving energy efficiency in heterogeneous computing environments , and enhancing MPI collective algorithms for large-scale systems. His work bridges HPC infrastructure with emerging applications in Distributed Deep Learning and AI . Recent publications highlight his expertise in GPU frequency scaling , NCCL profiling , and process arrival pattern analysis to improve distributed system performance. These works appear at top conferences like IPDPS , Cluster Computing , and ASHPC . Scientific Awards: Best Paper Award, Bench 2022 Salimibeni contributes to academic committees as a program committee member for IEEE ICPP 2025, ISC 2025, and BigHPC 2024, and serves on artifact evaluation committees for ASPLOS and CF conferences.

Philippe Poncetمشاهده پروفایل

استاد

• Numerical Analysis
• High Performance Computing
• Fluid Dynamics
• +۵ مورد دیگر

Philippe Poncet is a Professor at the Université de Pau et des Pays de l'Adour (UPPA) and Vice-President for Digital Environment. He leads the Numerical Methods and Complex Fluids team at the Laboratory of Mathematics and their Applications (LMAP). His expertise spans particle/vortex methods, high-performance computing, and applications in geoscience, microfluidics, and biomathematics, with a focus on reactive flows and porous media. Poncet's research integrates numerical analysis with practical challenges in environmental and biomedical engineering. Key interests include Lagrangian methods for fluid dynamics, optimization algorithms, pore-scale modeling, and cystic fibrosis biomechanics. His work bridges theoretical mathematics and industrial-scale simulations. Recent publications demonstrate advances in pore-scale dissolution modeling, Bayesian neural networks for inverse problems, and viscous flow simulations. His articles consistently address multi-scale challenges in geosciences and biomedicine using innovative computational frameworks. He has led significant projects including the ANR-funded MucoReaDy (mucus dynamics in respiratory diseases) and MicroMineral (CO₂ mineral storage). These collaborations involve multidisciplinary teams addressing environmental and health-related fluid dynamics.

Frederick Gentمشاهده پروفایل

استادیار

• Magnetohydrodynamics
• Dynamo Theory
• Solar Magnetic Activity
• +۳ مورد دیگر

Frederick Gent is an Assistant Professor at the Nordic Institute for Theoretical Physics (Nordita) and a Research Fellow at the Department of Computer Science, affiliated with the Korpi-Lagg Maarit and Vehtari Aki professorships. He holds a PhD in Natural Sciences from Newcastle University (2012) and has been a Visiting Researcher there since 2018. His research focuses on magnetohydrodynamics, dynamo theory, and interstellar medium dynamics, with applications to solar magnetic activity and supernova-driven turbulence. Gent has been awarded the 2018 Grand Challenge Award for his work on galactic dynamo interactions. He supervises postgraduate students, including A. Capobianco and P. Tengnér, and collaborates internationally, notably through the Pencil Code project. His work bridges computational astrophysics and theoretical physics, addressing challenges in high-performance computing and numerical simulation. Education: Doctoral degree in Natural Sciences (Newcastle University, 2012). Research interests include magnetic field dynamics in galaxies, supernova-driven turbulence, and the interplay between magnetic fields and interstellar medium structures. His computational methods leverage advanced numerical models to simulate astrophysical phenomena, such as magnetic buoyancy instabilities and dynamo transitions. Recent studies examine the destruction of supernova dust in magnetized environments and the transition from small- to large-scale dynamos in multiphase media. Scientific awards include the 2018 Grand Challenge Award for interdisciplinary dynamo research. He actively participates in conferences and workshops, notably organizing the Pencil Code User Meeting (2024) and presenting invited talks on galactic dynamo models. Gent’s advising roles include co-supervising doctoral students alongside Prof. Shukurov and mentoring visiting researchers at Nordita and Newcastle University. Labs/Teams: Pencil Code Collaboration (software developer), Korpi-Lagg Maarit Research Group (visiting fellow), and Nordic Institute for Theoretical Physics (primary affiliation).

• High Performance Computing
• Parallel Computation
• Novel Architectures
• +۳ مورد دیگر

Dr. Steven Wright is a Senior Lecturer in Computer Science at the University of York, specializing in High Performance Computing (HPC), Parallel Computation, and Novel Architectures. He joined the Department of Computer Science in 2018 and is a member of the Real-Time and Distributed Systems research group. His research focuses on optimizing supercomputers and scientific applications for performance, energy efficiency, and programmability. He collaborates with national laboratories, universities, and industry partners such as the UK Atomic Energy Authority and Intel. Prior to York, he was a Research Fellow at the University of Warwick, working on projects involving fusion physics and Rolls-Royce collaborations. Dr. Wright holds a Ph.D. (2014) and M.Eng. from the University of Warwick, where his doctoral thesis addressed I/O optimization in parallel applications. His teaching responsibilities include leading the High-Performance Parallel and Distributed Systems (HIPC) module and serving as Programme Lead for on-campus Undergraduate CS Programmes. He has also contributed to the Software Testing (SOTE) module and departmental roles such as Chair of the Board of Examiners. Research interests span HPC, energy-efficient computing, and application optimization. Recent work emphasizes performance portability, fusion simulations, and parallel I/O systems. His projects, such as the P3 Explorer database and EMPIRE-PIC framework, highlight contributions to HPC software and simulation tools. Collaborations with institutions like Sandia National Laboratories and industry partners like NVIDIA reflect his interdisciplinary approach to advancing computational science.