جست‌وجوی استاد و پژوهشگر

Kevin Holstمشاهده پروفایل

استاد پژوهشی

• Computational Fluid Dynamics
• Turbulence Modeling
• Finite-Element Method
• +۳ مورد دیگر

Kevin Holst is a Research Professor at the University of Tennessee, Knoxville, specializing in Computational Fluid Dynamics (CFD) and high-performance computing. He is a core developer of the Kestrel CFD solver, part of the DoD-funded CREATE-AV program. His work focuses on turbulence modeling, finite-element methods, and GPU-accelerated simulations for aerospace applications. Previously, he worked as a data analyst at Arnold Engineering Development Complex on propulsion systems testing. Holst holds a PhD in Aerospace Engineering from the University of Tennessee Space Institute (2019), an MS from the same institution (2012), and a BS from the University of Tennessee Knoxville (2007). His research emphasizes high-order discretization techniques, hybrid RANS/LES methods, and time-accurate simulations of unsteady flows. Key projects include contributions to the High-Fidelity CFD Verification Workshop and development of performance-portable mesh data models for multi-physics simulations. Holst’s work aligns with the Department of Defense’s HPC Modernization Program, addressing critical needs in aerospace engineering and computational tools. He has no listed scientific awards but has authored numerous peer-reviewed articles on CFD methodology, solver development, and turbulence modeling. His advising and grants focus on advancing Kestrel’s capabilities within the CREATE-AV ecosystem. Holst is affiliated with the Computational Research and Engineering Acquisition Tools & Environments (CREATE) program and collaborates with national labs and industry partners.

Xingfu Wuمشاهده پروفایل

استاد پژوهشی

• High-performance computing
• Performance modeling and analysis
• Energy and power modeling and analysis

Xingfu Wu is a Research Professor of Computer Science affiliated with Argonne National Laboratory (ANL). He holds a Ph.D. in Computer Science from Beijing University of Aeronautics and Astronautics and M.S. and B.S. degrees in Mathematics from Beijing Normal University. His research focuses on high-performance computing, performance modeling and analysis, and energy-efficient computing. Education: Ph.D. in Computer Science, Beijing University of Aeronautics and Astronautics, Beijing, China M.S. in Mathematics, Beijing Normal University, Beijing, China B.S. in Mathematics, Beijing Normal University, Beijing, China Research Interests: Xingfu Wu's research is centered around high-performance computing, performance modeling and analysis, and energy and power modeling. His work emphasizes optimizing parallel systems, developing frameworks for performance prediction (e.g., MuMMI), and enhancing energy efficiency in high-performance computing environments. Scientific Awards: Best Paper Award, 14th IEEE International Conference on Computational Science and Engineering (CSE-2011), 2011 Second Place, Beijing Science and Technology Advancement Awards, 1997 Labs/Teams: Wu contributes to research at Argonne National Laboratory, particularly through initiatives like the MuMMI framework for performance modeling and analysis.

Yunqing Xuanمشاهده پروفایل

دانشیار

• Hydrology
• Hydrometeorology
• Flood Risk Management
• +۵ مورد دیگر

Dr Yunqing Xuan is an Associate Professor in Civil Engineering at Swansea University's School of Aerospace, Civil, Electrical and Mechanical Engineering. His research focuses on interdisciplinary hydro-meteorological processes, extreme event modeling, flood risk management, and climate change impacts. He leads projects integrating advanced computer modeling, remote sensing, and weather radar technologies to address water sector challenges. Roles & Affiliations: Vice Chair of the Welsh Local Centre, Royal Meteorological Society Review Editor, Weather Journal (Wiley) Board Member, Conference Committee of the Institute of Mathematics and its Applications Research Interests: Dr Xuan specializes in hydrological modeling interfacing with atmospheric and societal systems. Key areas include: - Extreme hydrological events under climate change - GIS/remote sensing applications in flood risk management - Weather radar and numerical weather prediction (NWP) for hydrological forecasting - Compound flooding analysis and early warning systems Grants & Projects: PI - HPC & Welsh Extreme Weather Initiative (£600K, TSB/Welsh Government) PI - GCRF Knowledge Network for Vietnam Flood Resilience (£24K) PI - Urban Flood Early Warning System in China (£69K, Royal Academy of Engineering) Awards: FRMetS, FIMA, FIHE fellowships reflect his contributions to meteorology, mathematics, and environmental engineering.

Hartwig Anztمشاهده پروفایل

استاد

• High-Performance Computing
• Sparse Linear Algebra
• Iterative Methods
• +۶ مورد دیگر

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.

• Cloud Computing
• High-Performance Computing (HPC)
• Energy-Efficient Systems
• +۴ مورد دیگر

Ivona Brandić is a University Professor for High Performance Computing Systems at TU Wien's Institute of Software Engineering and Interactive Systems. Born in Gradačac, Bosnia and Herzegovina, she moved to Austria in 1992 as a refugee during the Bosnian War. She earned a master's degree (2002) and doctorate (2007) in business computer science from TU Wien and completed her habilitation in applied computer science there in 2013. Her career includes roles as an assistant professor (University of Vienna, 2002–2007) and postdoctoral researcher (University of Melbourne, 2008). She transitioned to a tenure-track position at TU Wien in 2014 and became a full professor in 2016. Brandić’s research focuses on cloud computing, energy-efficient ultra-scale systems, and hybrid quantum-classical computing. She has been recognized with the MiA Award (2011), the Austrian Science Fund's Start-Preis (2015), and membership in the Austrian Academy of Sciences' Young Academy (2016). Her work emphasizes sustainable computing, edge systems, and optimizing resource management for distributed applications. Education: Bachelor's degree in Business Informatics (University of Vienna/TU Wien) Master's in Business Computer Science (University of Vienna, 2002) PhD in Applied Computer Science (TU Wien, 2007) Habilitation in Practical Computer Science (TU Wien, 2013) Research Interests: Brandić’s work spans cloud computing, energy efficiency in HPC systems, edge computing, and quantum-classical hybrid systems. She explores autonomic resource management, distributed system resilience, and sustainability in ultra-scale infrastructures. Her projects often address real-world applications like drug design, environmental monitoring, and smart energy grids. Publications: Her 2009 paper Cloud Computing and Emerging IT Platforms is a seminal work in the field. Recent publications focus on quantum-edge integration, energy optimization in AI models, and adaptive edge analytics frameworks. These contributions highlight trends toward sustainable, distributed, and hybrid computational paradigms. Awards: 2011: MiA Award for distinguished contributions by international backgrounds 2015: Austrian Science Fund’s Start Prize 2016: Austrian Academy of Sciences Young Academy Membership Advising & Grants: Brandić leads research groups and has secured grants for projects like NESSUS (energy-efficient cloud systems) and CHIST-ERA’s SDCDN (distributed networks). She mentors students in HPC, edge computing, and quantum systems. Advised topics include workload scheduling, fault tolerance, and energy-aware algorithms. Labs & Teams: She directs research on autonomic cloud management, edge intelligence frameworks (e.g., Sea-LEAP, FRESCO), and quantum-classical workflow systems (RIGOLETTO). Her teams collaborate internationally, integrating academia and industry for scalable, sustainable solutions.

Suresh S. Muknahallipatnaمشاهده پروفایل

استاد

• Medical Image Segmentation
• Deep Learning
• High Performance Computing
• +۷ مورد دیگر

Suresh S. Muknahallipatna is a Professor in the Department of Electrical Engineering and Computer Science at the University of Wyoming, College of Engineering and Physical Sciences. His research spans interdisciplinary domains, integrating deep learning, high-performance computing, and augmented reality technologies. Research Interests: His work focuses on Medical Image Segmentation using Deep Learning , where he applies Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), and Generative Adversarial Networks (GAN) to segment organs and tumors in MRI, CT, and Ultrasound images. He also investigates Transient Stability and Contingency Analysis of Modern Power Grids using GPGPU-based High Performance Computing (HPC) and machine learning. In climate research, he uses HPC to accelerate models like MPAS and WRF. A significant part of his research involves Augmented Reality (AR) for Medical Applications , using devices like Microsoft HoloLens and Meta2 to visualize medical images as 3D holograms for real-time collaboration and training in procedures such as epidural injections with haptic feedback. Scientific Awards: Samuel D. Hakes Outstanding Graduate Research and Teaching Award, 2009 Microsoft Most Valuable Professional Award (2004, 2005, 2006) IEEE Senior Member (Computer Society), 2005 Tau Beta Pi Engineering Honor Society Phi Kappa Phi Honor Society 1st Rank, Master of Engineering, University of Bangalore, India Advising and Grants: While specific student names and grant details are not listed in the text, his academic experience and ongoing research projects suggest active graduate student mentoring and external funding in areas of HPC, medical imaging, and AR. His long tenure and award record reflect strong contributions to research and teaching. Labs and Teams: Dr. Muknahallipatna leads research efforts involving interdisciplinary teams working on GPU-accelerated computing, deep learning applications in healthcare, and AR-based medical visualization systems, likely operating within specialized labs at the University of Wyoming focused on computational engineering and biomedical technology.

Kishwar Ahmedمشاهده پروفایل

استادیار

• High Performance Computing
• Cyber-Physical Systems
• Parallel Computing
• +۳ مورد دیگر

Kishwar Ahmed is an Assistant Professor in the Department of Electrical Engineering and Computer Science at the University of Toledo . Her research focuses on High Performance Computing (HPC) and Cyber-Physical Systems , with emphasis on energy-efficient modeling, resource allocation, and scalable simulation frameworks. Her recent work explores trends in parallel computing education , edge device optimization , and power-aware HPC systems . She has secured a $600K NSF grant for collaborative research with NMSU. Scientific Awards NSF CRII Award Service Roles TPC Member, HiPC 2024 Workshop Organizer, EduHiPC 2023-2024 Program Committee Member, ACM SIGSIM PADS 2019-2024 Journal Reviewer (IEEE TCC, ACM TOMACS, etc.)

• Supercomputing
• Data Processing Systems
• Scientific Software
• +۳ مورد دیگر

Bob Dröge is a researcher specializing in computational infrastructure and astronomical data systems. His work focuses on optimizing scientific software stacks for high-performance computing (HPC) environments, particularly through collaborations like the Euclid Mission and the EESSI project . He has contributed to distributed data processing systems, GPU-accelerated simulations, and mission-critical archival infrastructures. Research Interests Supercomputing and HPC architecture Scientific software deployment and optimization Astronomical data distribution networks Dark matter cosmological surveys Key Collaborations include the Euclid Mission (European Space Agency) and EESSI (European Environment for Scientific Software Installations). His publications span conferences like ADASS (Astronomical Data Analysis Software and Systems) and journals such as Software - Practice and Experience .

• Software Engineering
• Formal Methods
• Software Testing
• +۵ مورد دیگر

Milos Gligoric is an Associate Professor in the Department of Electrical and Computer Engineering at The University of Texas at Austin. His research focuses on software engineering and formal methods, particularly in software testing (test generation and regression testing), proof engineering, systems-supported software engineering, and software engineering for scientific computing. He holds a Ph.D. from the University of Illinois at Urbana-Champaign (2015) and M.Sc./B.Sc. degrees from the University of Belgrade. Research Interests: Improving software quality and developer productivity through automated testing techniques, compiler optimizations, and formal verification methods. Recent work explores applications of large language models in test generation and code evolution. Publication Trends: Recent articles (2023-2025) show strong emphasis on LLM applications for test generation, JIT compiler testing, Python/C++ performance optimization, parallel computing, and innovative testing tools. Work frequently appears at top venues like ICSE, FSE, ISSTA, and OOPSLA. Scientific Awards: ACM SIGSOFT Outstanding Doctoral Dissertation Award David J. Kuck Outstanding PhD Thesis Award Multiple ACM SIGSOFT Distinguished Paper Awards Best Paper Award nominations (ICST 2012, ICS 2021) New Ideas and Emerging Results Distinguished Paper Award Research Support & Advising: Funded by Army Futures Command, Cisco, DOE, Google, Huawei, NSF, Runtime Verification, and Samsung. Mentors 7 PhD students and has graduated 12 PhD/MS students. Maintains industry collaborations with DBT (part-time contractor), Katana Graph, and Samsung. Labs & Tools: Leads UT Austin's software engineering research group. Developed multiple open-source tools including Ekstazi (regression test selection), mCoq (mutation analysis for Coq), Roosterize (lemma suggestion for Coq), and JAttack (JIT compiler testing).

Ayesha Afzalمشاهده پروفایل

پژوهشگر

• High Performance Computing
• Parallel Computing
• Performance Modeling
• +۵ مورد دیگر

Ayesha Afzal is a researcher and PhD student at the Erlangen National High Performance Computing Center (NHR@FAU), part of Friedrich-Alexander University Erlangen-Nuremberg. She holds a master's degree in computational engineering from FAU and a bachelor's degree in electrical engineering from the University of Engineering and Technology, Lahore, Pakistan. Her research focuses on high-performance computing with expertise in analytic performance models, parallel simulation frameworks, and first-principles performance modeling of distributed-memory parallel programs. She investigates multi-core and parallel architectures, parallel computing algorithms, programming models, and domain-specific languages to understand and optimize parallel application performance through advanced modeling techniques. Dr. Afzal's publication record demonstrates consistent innovation in understanding parallel program dynamics, particularly around idle waves, desynchronization phenomena, and performance bottlenecks. Her research has pioneered approaches like the physical oscillator model for supercomputing and developed frameworks such as DisCostiC for simulating MPI applications without code execution, revealing novel insights into hardware-software interactions in HPC systems. ISC PhD Forum Award (1st place, 2021) IEEE TPDS Best Paper Runner-up Award (2023) SC PMBS Best Short Paper Award (2023) SC Best Research Poster Finalist (2024) ISC Best Research Poster Award (1st place, 2025) Top 100 Future Leaders Role Model List (2022-2025) WeAreTheCity's Global Award for Achievement (2023) Dr. Afzal actively contributes to the HPC community through teaching and mentorship. She teaches courses on parallel programming of high-performance systems and supervises multiple bachelor's and master's theses on topics ranging from energy consumption analysis to MPI collective implementation. As vice chair of the IEEE Computer Society Germany Section Chapter and founder of the NHR Women in HPC chapter, she plays a significant leadership role in advancing the field and promoting diversity. She is deeply involved in major HPC initiatives including KONWHIR with the Leibniz Supercomputing Centre on performance optimization and NHR's EEC project focused on enhancing energy efficiency and managing operational costs across NHR centers, demonstrating her commitment to addressing real-world challenges in high-performance computing infrastructure.

Anna Kahlerمشاهده پروفایل

پژوهشگر

• Molecular Dynamics
• High Performance Computing
• Computational Biophysics
• +۳ مورد دیگر

Dr. Anna Kahler is a computational researcher at the National High Performance Computing Center Erlangen (NHR@FAU) at Friedrich Alexander University Erlangen-Nuremberg. She specializes in optimizing molecular dynamics simulations on high-performance computing infrastructure, with primary focus on GROMACS performance across diverse hardware architectures including GPUs and CPUs. Her research centers on computational biophysics and high-performance computing, specifically: Runtime parameter optimization for molecular dynamics software GPU acceleration strategies for biomolecular simulations Performance benchmarking across CPU and GPU architectures Support for complex simulation setups including multi-GPU configurations and replica exchange molecular dynamics Dr. Kahler's publication history demonstrates consistent expertise in protein structure modeling and molecular dynamics, particularly regarding G-protein coupled receptors and amyloid-beta oligomerization. Her recent work has shifted toward practical HPC optimization challenges rather than fundamental biological questions. She maintains an active technical blog documenting performance characteristics across modern hardware platforms and provides user support through the NHR@FAU HPC Café initiative. Her current work focuses on hardware-specific optimization for molecular simulation workloads, with recent publications analyzing GROMACS performance on ARM architectures, AMD CPUs, and next-generation GPU hardware. She actively supports researchers with challenging simulation configurations through documented case studies on multi-GPU setups and non-standard REMD implementations.

Christian Stemmerمشاهده پروفایل

استاد

• Hypersonic Aerodynamics
• Fluid Mechanics
• Thermal and Chemical Nonequilibrium Flows
• +۳ مورد دیگر

Prof. Christian Stemmer is a Professor of High-Speed Aerodynamics at the Technical University of Munich (TUM), affiliated with the TUM School of Engineering and Design and the Department of Aerodynamics and Fluid Mechanics. His research focuses on hypersonic flows, boundary layer transition, thermal and chemical nonequilibrium phenomena, and research data management. Stemmer holds a Dr.-Ing. habil. and has extensive international experience, including postdoctoral work at Stanford University and NASA Ames. Career highlights: Appointment as extraordinary professor in 2019, leadership roles in the Collaborative Research Center TRR40 (SFB/TRR40), and membership in editorial boards such as Advances in Aerodynamics . Awards: 2020 NATO AVT Panel Excellence Award for contributions to hypersonic flow research. Key projects: Investigation of hypersonic boundary layer transition under high-enthalpy conditions, development of numerical models for rocket combustion chambers, and leadership in national and international research consortia. His work bridges fundamental fluid mechanics with aerospace engineering applications, emphasizing high-performance computing and data-driven methodologies. Recent contributions include studies on roughness-induced instabilities, shock-wave interactions, and metadata extraction frameworks for HPC workflows.

• High Performance Computing
• Bioinformatics
• Scheduling Algorithms
• +۳ مورد دیگر

Gerald Lirk is a Professor at Fachhochschule Campus Hagenberg, specializing in interdisciplinary research spanning High Performance Computing, Bioinformatics, and Medical Diagnostics. His work integrates computational methods with healthcare applications, including studies on epigenetic mutations, driver distraction systems, and brain connectivity analysis. Research interests focus on optimizing computational frameworks for biomedical applications, such as scheduling algorithms for HPC environments and analyzing genetic markers in hematologic disorders. He has led projects like Lingohub (2013–2014) and WIMAKS (2012–2013), funded by EFRE Regio 13. Recent contributions include peer-reviewed studies on mutational burden impacts and feasibility of adolescent health programs. He actively engages in public discourse on topics like vaccine mechanisms and NGS data analysis, delivering over 20 talks and presentations since 2013.

Jean-Francois Lalandeمشاهده پروفایل

استاد

• Operating System Security
• Embedded Software Security (Smart Cards)
• Android Application Security
• +۴ مورد دیگر

Jean-Francois Lalande is a Professor at CentraleSupélec, affiliated with the Inria CIDRE project within the IRISA laboratory. Previously, he served as Associate Professor at INSA Center Val de Loire (LIFO laboratory) from 2005 to 2017. His research focuses on cybersecurity, particularly in operating systems, embedded systems (smart cards), and Android applications. He has defended his Habilitation to Supervise Research (HDR) in 2016. Research interests include malware analysis, access control policies, intrusion detection systems, and software code analysis. He has contributed to projects like Mascopt (network optimization library) and developed frameworks for analyzing Android malware behavior (e.g., GroddDroid, Kharon dataset). Key achievements include work on isolating malicious code in Android malware, preventing serialization vulnerabilities, and debiasing malware datasets. He also focuses on teaching mobile security, developing educational tools and curricula. His collaborations span institutions like INSA, Inria, and international researchers. Current research emphasizes network security optimization, covert channel detection in mobile systems, and privacy-preserving protocols for smart environments.

• Vascular Fluid Dynamics
• Biomedical Engineering
• Hemodialysis
• +۳ مورد دیگر

Professor Tracie Barber is a faculty member in the Department of Mechanical and Manufacturing Engineering at the University of New South Wales (UNSW), within the Faculty of Engineering . Her primary role is as a Professor , focusing on vascular fluid dynamics with clinical collaborations at hospitals like Prince of Wales and Royal Hospital for Women. She leads a research group investigating cardiovascular systems, hemodialysis, and medical device design using computational and experimental methods. Specializes in fluid-structure interaction, bioprinting, and vascular flow dynamics. Utilizes advanced facilities including Trentino and Leonardi HPC clusters for simulations. Experimental lab equipped with PIV systems, high-speed cameras, and microfluidic setups. Research interests span vascular stents, arteriovenous fistulae mechanics, and biomedical engineering applications . Key projects include optimizing hemodialysis devices and modeling cerebral venous hemodynamics in multiple sclerosis. Collaborates with medical companies and clinical partners to translate engineering innovations into clinical solutions. Publications focus on CFD applications in vascular systems, microbubble dynamics, and 3D bioprinting. Recently explored hydrodynamic impacts on cell properties and stent implantation effects. Active in international conferences and interdisciplinary research, bridging engineering and medical fields. Supervises graduate students in vascular fluid dynamics and bioprinting. Funds include grants for renal research and medical device development. A leader in translating fluid dynamics principles to clinical and industrial applications.