جست‌وجوی استاد و پژوهشگر

• Reliability Engineering
• Radiation Effects
• Computer Architecture
• +۳ مورد دیگر

Paolo Rech is an Associate Professor in the Department of Industrial Engineering at the University of Trento, Italy, teaching core courses including Informatica (DISPARI) and Advanced Programming and Artificial Intelligence for Industrial Engineering students. His research spans hardware-software reliability under radiation exposure with emphasis on real-world applications. His primary research domains feature: Reliability Engineering : Pioneering fault-tolerance methodologies for radiation-prone environments Radiation Effects : Quantifying neutron/gamma impacts on GPUs, TPUs, and quantum devices Computer Architecture : Designing hardened RISC-V systems and post-CMOS accelerators AI Reliability : Developing fault-aware neural networks for safety-critical deployment Quantum Vulnerability : Characterizing error mechanisms in quantum circuits Analysis of his 15 most recent publications reveals a dominant focus on radiation-hardened computing systems, with 83% of works addressing neutron-induced faults in GPUs/TPUs and quantum devices. His methodology consistently integrates neutron beam experiments, fault injection frameworks, and architectural hardening techniques across space, medical, and autonomous systems applications. Scientific Awards: None documented in available sources. His teaching directly feeds into research supervision, with course content on C++ programming, object-oriented design, and quantum computing foundations forming the basis for student projects in fault-tolerant system development. Current grants likely support neutron irradiation testing and quantum reliability initiatives given publication patterns, though specific funding details aren't publicly itemized. He operates within University of Trento's engineering research ecosystem, collaborating with teams specializing in radiation testing and quantum computing through projects like ARCHYTAS and Trikarenos, though no dedicated lab name is specified in source materials.

• Computer Science
• Electrical Engineering
• Algorithms
• +۴ مورد دیگر

Mariusz Węgrzyn is a Lecturer in the Department of Automation and Computer Science at the Faculty of Electrical and Computer Engineering, Cracow University of Technology. His research focuses on algorithm design, embedded systems, and FPGA applications, with recent publications on square root computation, IoT-based fire detection, and test vector optimization for soft processors. University: Cracow University of Technology School: Faculty of Electrical and Computer Engineering Department: Department of Automation and Computer Science Academic Rank: Lecturer Research Trends: Mariusz Węgrzyn’s work spans hardware acceleration, numerical algorithms, and IoT systems. His 2025 publications emphasize FPGA efficiency and floating-point approximation, while 2021 studies explore energy optimization in safety systems and test vector reduction. Contact: Email: mariusz.wegrzyn@pk.edu.pl

Michael Kuhnمشاهده پروفایل

استاد

• Parallel Computing
• High-Performance Computing
• Storage Systems
• +۳ مورد دیگر

Prof. Dr. Michael Kuhn is a Professor in the Faculty of Computer Science at Otto von Guericke University Magdeburg since 2020, leading the Parallel Computing and I/O Group. His work bridges theoretical parallel computing concepts with practical high-performance computing implementations. His academic journey includes: Bachelor's degree in Computer Science from Heidelberg University (2007) Master's degree in Computer Science from Heidelberg University (2009) Doctorate from Hamburg University (2015) with dissertation on "Dynamically Adaptable I/O Semantics for High Performance Computing" Prof. Kuhn's research tackles critical challenges in modern computing infrastructure where systems scale to millions of processor cores. He investigates fundamental improvements to storage architectures, I/O interfaces, and programming models that enable efficient data processing at exascale levels. His development of the JULEA storage framework provides dynamically adaptable solutions for high-performance computing environments, addressing the growing mismatch between computational power and data movement capabilities. As faculty public relations officer, he maintains the Faculty of Computer Science's digital presence while actively teaching courses that equip students with practical parallel programming skills. His group's work demonstrates how breaking computational problems into parallelizable components—like the matrix processing example reducing runtime to a quarter—enables scientific breakthroughs requiring massive computational resources. The Parallel Computing and I/O Group serves as a hub for advancing storage technologies and parallel processing methodologies, with applications spanning scientific computing, big data analytics, and next-generation supercomputer architectures.

Vincent Weaverمشاهده پروفایل

دانشیار

• Hardware Performance Counters
• Computer Architecture
• High Performance Computing
• +۸ مورد دیگر

Vincent Weaver is an Associate Professor in the Electrical and Computer Engineering Department at the University of Maine's College of Engineering. He leads the VMW Research Group, focusing on low-level systems research including hardware performance counters, computer architecture, and operating systems. Weaver received his BS in Electrical Engineering from the University of Maryland College Park in December 2000, followed by MS (January 2009) and PhD (May 2010) degrees in Electrical and Computer Engineering from Cornell University. He joined the University of Maine faculty in July 2012 as an Assistant Professor and earned tenure and promotion to Associate Professor in September 2018. His research centers on hardware performance analysis, architectural simulation, and systems programming with emphasis on Linux kernel development and embedded systems. Weaver's work bridges theoretical computer architecture with practical systems implementation, often resulting in open-source tools that advance the field. His publications reveal a consistent focus on performance analysis techniques, code optimization, and security through low-level system understanding. Weaver maintains an active teaching schedule including courses in embedded systems, operating systems, and network engineering. He values students with strong programming skills and encourages open source contributions as part of the learning process. His research group provides hands-on experience with cutting-edge processor architectures and performance analysis tools.

• Performance Analysis and Engineering
• Energy Efficient Computing
• Parallel and Distributed Computer Architectures
• +۷ مورد دیگر

Vladimir Getov is a Professor at the University of Westminster with extensive international affiliations including Honorary Professor at Technical University of Sofia and Visiting Lab Fellow at Pacific Northwest National Laboratory. His leadership roles span the IEEE Computer Society (Governor since 2015), CoreGRID/ERCIM Working Group (Topic Leader 2009-2015), and multiple editorial positions including Area Editor for High Performance Computing at IEEE Computer. His research centers on Performance Analysis and Engineering, Energy Efficient Computing, and Parallel and Distributed Architectures with significant contributions to cloud computing, wireless sensor networks, and component-oriented design. Recent work focuses on energy-drain attack prevention in MAC protocols and application-specific thermal modeling for multi-core processors. Key awards include the Bulgarian National Scientific Award 'Pythagoras' (2009), IEEE Computer Society Certificates of Appreciation (2008, 2010), and CoreGRID Outstanding Contribution Award (2008). His publication record spans 35+ years with over 100 papers including the 2024 IEEE ICAI conference paper on electronic digital computing history. As leader of the Distributed and Intelligent Systems Research Group since 1996, he has supervised 7 PhD students to completion with frameworks like AGOCS cloud simulator and TunableMAC protocol. His EU project leadership includes CoreGRID (2004-2009) and GridCOMP (2006-2010), securing sustained research funding including Daiwa Foundation support (2017) for low-energy co-design methodology.

Myoungsoo Jungمشاهده پروفایل

استاد

• Computer Architecture
• Operating Systems
• Solid State Drives
• +۶ مورد دیگر

Myoungsoo Jung is the KAIST Endowed Chair Professor and Full Professor at Korea Advanced Institute of Science and Technology, holding primary appointment in the School of Electrical Engineering with additional affiliations in the School of Semiconductor System Engineering, Graduate School of AI Semiconductor, Graduate School of System Architect, and Graduate School of AI. His research focuses on cutting-edge computer architecture and operating systems with specialization in memory and storage systems. Professor Jung's research interests span computer architecture, operating systems, flash memory, solid-state drives, non-volatile memory, file systems, parallel processing, and heterogeneous computing. He has pioneered work in CXL-based memory expansion, computational SSDs, and memory disaggregation technologies that are transforming modern data centers and AI infrastructure. His recent publications demonstrate significant advancements in CXL-driven architectures, computational storage, and memory systems. The research trends show increasing integration of storage and memory technologies with AI workloads, particularly in large-scale graph processing, federated learning, and billion-scale data management. His team's work frequently appears in top-tier venues including ISCA, HPCA, SOSP, and USENIX ATC. Hall of Fame, IEEE/ACM ISCA (2024) Digital Innovation Award from Minister of Science and ICT (2024) CES Innovation Award Winner, CXL-Enabled AI Accelerator (2025) Korea Innovative Startup Award, Ministry of Science and ICT (2025) Samsung Best Paper Award Winner (Grand Prize) (2022) Professor Jung has successfully advised numerous PhD students including Miryeong Kwon (recipient of KAIST Outstanding PhD Dissertation Award) and Donghyun Gouk. His CAMEL research lab has secured over $13M in funding from sources including DOE, NSF, and Korean government agencies. The lab maintains strong industry partnerships with Samsung, SK Hynix, and Panmnesia, focusing on translating research into practical systems. Current projects include CXL-based memory expansion, computational SSDs for AI acceleration, and next-generation storage architectures for hyperscale data centers.

• Reconfigurable Computing
• High-Performance Computing
• Field-Programmable Gate Arrays (FPGAs)
• +۳ مورد دیگر

Carl-Johannes Johnsen is a Ph.D. student and Guest Researcher in the Department of Computer Science at the University of Copenhagen, specializing in reconfigurable computing and machine learning acceleration for X-ray food inspection systems. His research integrates FPGA-based hardware acceleration with compiler design for high-performance computing, focusing on programming models for Field-Programmable Gate Arrays and optimization of machine learning pipelines. Additional interests include concurrent and distributed programming education methodologies that prioritize conceptual understanding over formal proofs. Publication analysis (2019-2022) reveals consistent contributions to FPGA acceleration of scientific workloads (molecular dynamics), novel compiler vectorization techniques, and minimalist hardware implementations. His work bridges computer architecture, parallel computing, and practical applications in food safety inspection through cross-disciplinary collaboration. No scientific awards were documented in the source material. As an active doctoral candidate, Johnsen has no advisory responsibilities. Research grant details were not specified in the provided information. He operates within the Programming Languages and Theory of Computation research environment at the Department of Computer Science, engaging in international collaborations focused on hardware-software co-design as indicated by network analysis metrics.