جست‌وجوی استاد و پژوهشگر

• Parallel Computing
• Distributed Systems
• Multiprocessor Operating Systems
• +۵ مورد دیگر

Vasilios Mamalis is a Professor at the Department of Informatics and Computer Engineering, University of West Attica, and a member of the Collaborating Scientific Staff at the Hellenic Open University's Informatics program. His academic career spans decades with significant contributions to parallel and distributed computing, wireless sensor networks, and cloud technologies. Education: Diploma in Computer Engineering and Informatics, University of Patras (1993) PhD in Computer Engineering and Informatics, University of Patras (1998) Research Interests focus on parallel algorithms, distributed systems, wireless sensor networks, cloud computing, and information retrieval. His work addresses energy efficiency in ad-hoc networks, optimization techniques, and educational technology applications. Publication Trends show extensive work on WSN clustering, cloud task scheduling, parallel simplex methods, and fog computing applications in education and urban systems. He combines metaheuristics with infrastructure optimization in large-scale networks. Scientific Contributions include editorial roles in the Journal of Balkan Libraries Union and program committee memberships in international conferences. He actively reviews for journals and conferences in computing. Teaching Expertise covers operating systems, parallel computing, distributed systems, and cloud technologies at both undergraduate and postgraduate levels. His Research Leadership involves EU/Greek-funded projects on communication protocols, parallel content-based retrieval, and wireless sensor networks.

• Star formation
• Interstellar medium physics
• MHD simulations
• +۳ مورد دیگر

Kostas Tassis serves as Professor in the Department of Physics at the University of Crete, Greece, having joined in 2012 as Assistant Professor, promoted to Associate Professor in 2018, and to full Professor in 2023. He leads the PASIPHAE project (Polar-Areas Stellar-Imaging in Polarization High-Accuracy Experiment), an ERC Consolidator Grant awarded in 2018, and maintains active affiliations with Skinakas Observatory and the Institute of Theoretical and Computational Physics. His academic background includes: BSc in Physics from the University of Thessaloniki (1999) PhD in Theoretical Astrophysics from the University of Illinois at Urbana Champaign (2005) His research centers on star formation processes, interstellar medium physics, and magnetohydrodynamic simulations, with particular emphasis on cosmic magnetic fields and their role in astrophysical systems. He employs both theoretical modeling and observational polarimetry to investigate phenomena ranging from molecular cloud dynamics to cosmological-scale magnetic field effects. Analysis of his recent publications reveals dominant focus on LiteBIRD mission simulations, interstellar dust polarization, and magnetic field strength estimation techniques. Key thematic clusters include cosmic microwave background polarization analysis, blazar variability studies, and computational approaches to non-ideal magnetohydrodynamics in star-forming regions, demonstrating strong integration of observational data with theoretical modeling. Notable recognitions include: ERC Consolidator Grant for PASIPHAE project (2018) His research program involves extensive international collaboration, particularly through the PASIPHAE survey and LiteBIRD mission consortia. Current work emphasizes polarimetric instrumentation development and large-scale cosmic magnetometry, with significant contributions to understanding magnetic field roles in galaxy evolution and star formation processes. He maintains active involvement with multiple University of Crete research units including the Crete Center for Theoretical Physics (CCTP) and Skinakas Observatory, where observational components of his PASIPHAE work are conducted.

George Papadimitriouمشاهده پروفایل

استادیار

• Computer Architecture
• Energy-Efficient Architectures
• Microprocessor Reliability
• +۷ مورد دیگر

George Papadimitriou is an Assistant Professor in the Computer Engineering & Informatics Department at the University of Patras , Greece, hosted within the School of Engineering . His primary affiliation lies with the Computer Hardware and Architecture division, where he leads research and teaching activities focused on dependable, energy-efficient computer architectures. Education: PhD in Computer Science, Department of Informatics & Telecommunications, National and Kapodistrian University of Athens (2019) Post-doctoral researcher, Computer Architecture Lab, National and Kapodistrian University of Athens Research Interests: Dr Papadimitriou’s research lies at the intersection of computer architecture , energy efficiency , and microprocessor reliability . His work specifically targets: Robust and energy-efficient CPU/GPU/accelerator architectures Post-silicon validation techniques for catching elusive hardware bugs Silent data corruption detection and mitigation across the compute stack Characterization of voltage margins and power consumption in modern microprocessors Modeling and simulation of domain-specific accelerators for low-power, dependable operation More recently, his team has been extending these methodologies to RISC-V and neuromorphic photonic accelerators within large European consortia. Scientific Awards & Recognition: Eight HiPEAC Paper Awards for top-tier conference publications (MICRO, HPCA, ISCA) between 2017–2024 IEEE Transactions on Computers 2022 Best Paper Award for the article “Anatomy of On-Chip Memory Hardware Fault Effects Across the Layers” TTTC/ITC Gerald W. Gordon Student Award 2023 Research Funding & Projects: Dr Papadimitriou is principal investigator or key technical contributor in multiple Horizon Europe and industry-backed projects that collectively exceed €50 M in funding. Current leadership roles include: DARE (Digital Autonomy for RISC-V in Europe) NEUROPULS (Neuromorphic Energy-Efficient Secure Accelerators) REBECCA (Reconfigurable Heterogeneous Highly Parallel Processing Platform) Vitamin-V (Virtual Environment & Tool-boxing for Trustworthy RISC-V Cloud Services) Intel, IBM, and Thales bilateral research contracts on energy-efficient and resilient microarchitectures Laboratory & Team: He leads the Energy-Efficient and Dependable Architectures (EEDA) research group at University of Patras, operating laboratory facilities for silicon measurement, FPGA emulation, and full-system simulation (gem5, MARSS, custom tools). The team currently comprises 3 PhD candidates, 2 post-docs, and several MSc thesis students collaborating with European and US partners.

Chao Pengمشاهده پروفایل

مدرس پاره‌وقت

• Software Testing
• Program Analysis
• Programming Languages
• +۵ مورد دیگر

Chao Peng is a Principal Research Scientist at ByteDance where he leads the Trae Research team (ByteDance Software Engineering Lab), conducting cutting-edge research on AI agents for software engineering. He also serves as a Part-time Postgraduate Student Mentor at Fudan University's School of Computer Science, bridging industry research with academic mentorship. PhD in Informatics (2021), University of Edinburgh, UK MSc in High Performance Computing and Data Science (2017), University of Edinburgh, UK BEng in Computer Science and Technology (2016), Xuzhou University of Technology, China Dr. Peng's research focuses on the intersection of software testing, program analysis, and large language models. His work explores how AI agents can revolutionize software engineering practices, with particular emphasis on automated bug detection, code generation, and testing frameworks. He has pioneered approaches for evaluating LLM performance in software engineering contexts and developing agent-based systems that enhance developer productivity while maintaining code quality and security. His recent publications demonstrate a clear trend toward integrating large language models with traditional software engineering practices. The research spans code generation evaluation, security vulnerability detection, automated bug reproduction, and issue localization. These works collectively advance the field of AI-assisted software development by addressing practical challenges in reliability, security, and efficiency of AI-generated code. Distinguished Reviewer for FSE'25 School of Informatics Scholarship (fully-funded PhD scholarship) Outstanding Graduate Scholarship at Xuzhou University of Technology Multiple China National Scholarships Honours Spot Bonus at ByteDance Certificate of Achievement for HPCAC Student Cluster Competition Dr. Peng actively mentors students through his role at Fudan University and previously at the University of Edinburgh, where he served as sub-supervisor for MSc projects and teaching assistant for software testing courses. His research has attracted significant industry attention, leading to multiple collaborations between ByteDance and academic institutions. He frequently serves on program committees for major software engineering conferences including ASE, FSE, and ICSE, demonstrating his leadership in the field. As leader of the Trae Research team at ByteDance Software Engineering Lab, Dr. Peng oversees research on AI agents for software engineering, including the application and evaluation of AI agents and training LLMs for agent-based systems. The lab's work focuses on practical systems that predict, detect, diagnose, and fix bugs across various software systems, with particular emphasis on real-world applications and measurable impact on developer productivity.

Rajiv Guptaمشاهده پروفایل

استاد

• Parallel Computing
• Compilers
• Computer Architectures
• +۴ مورد دیگر

Rajiv Gupta is a Distinguished Professor and the Amrik Singh Poonian Professor of Computer Science at the University of California, Riverside (UCR), where he serves as Associate Dean for Academic Personnel in the Bourns College of Engineering (BCOE). He is a member of the RIPLE research group and has co-authored 327 papers with an h-index of 69 and over 16,600 citations. His extensive service includes chairing major conferences such as FCRC 2015, PPoPP 2020, ASPLOS 2011, and PLDI 2008. Professor Gupta's research focuses on Programming, Compiler, Runtime & Architectural Support for Parallel & Distributed Heterogeneous Systems and Software Tools for Monitoring and Managing Runtime Behavior . His work spans graph analytics with scalability and performance, understanding and managing the dynamic behavior of parallel programs, software speculation for irregular parallelism, dynamic program analysis for secure and reliable computing, and compiler optimizations with architectural support. His research has significant applications in high-performance computing, GPU programming, and distributed systems. Analysis of his recent publications reveals a strong focus on graph processing systems, with particular emphasis on evolving and streaming graph analytics. His work addresses critical challenges in memory management for large-scale graph processing, hardware acceleration for graph algorithms, and optimization techniques for concurrent and distributed graph computations. The research demonstrates a progression from foundational compiler and architecture work to increasingly sophisticated systems for handling modern data-intensive computing challenges. Fellow of the ACM (2009) Fellow of the IEEE (2008) Fellow of the AAAS (2011) NSF Presidential Young Investigator Award (1991) UCR Doctoral Dissertation Advisor/Mentor Award (2012) Multiple best paper awards across major conferences Two students won ACM SIGPLAN Outstanding Doctoral Dissertation Award Five advisees received NSF CAREER Award Professor Gupta has supervised 42 PhD students to completion and currently advises several doctoral candidates. His advising success is reflected in his students' achievements, including multiple award-winning dissertations and significant career accomplishments in academia and industry. His research has been supported by numerous grants from NSF, DARPA, and industry partners, enabling sustained investigation into parallel computing systems. The RIPLE research group under his leadership has produced influential work that bridges theoretical foundations with practical system implementations. As the leader of the RIPLE research group at UC Riverside, Professor Gupta oversees a vibrant team focused on innovative approaches to parallel and distributed computing. The group maintains strong collaborations with industry partners and other academic institutions, contributing to the development of next-generation computing systems. Current projects include GRASP (Graph Analytics with Scalability & Performance) and research on understanding and managing the dynamic behavior of parallel programs, reflecting the group's continued focus on cutting-edge computing challenges.

Sang-Hoon Kimمشاهده پروفایل

دانشیار

• Operating Systems
• Memory Systems
• Storage Systems
• +۴ مورد دیگر

Sang-Hoon Kim is an Associate Professor in the Department of Software and Computer Engineering and Department of Artificial Intelligence at Ajou University, South Korea. He leads the Systems Software Lab (Paldal Hall 1004-2) and maintains active collaborations with Virginia Tech as a Visiting Scholar since August 2024. His academic journey includes a Ph.D. in Computer Science from KAIST (2016) under advisors Seungryoul Maeng and Jin-Soo Kim, and a B.S. in Computer Science from KAIST (2002). His research spans operating systems, memory management, and storage systems with focus on mobile platforms, heterogeneous architectures, and SSD technologies. Key interests include memory fragmentation control , distributed thread execution , key-value storage optimization , and resource disaggregation . His work bridges theoretical innovation with practical system implementations, particularly for mobile and datacenter environments. Kim's publication portfolio shows consistent output in top-tier venues including USENIX FAST, VLDB, ICDCS, and ASPLOS. His research demonstrates evolution from mobile memory management (2015-2017) toward distributed systems and hardware-aware software (2019-present), with recent emphasis on resource-disaggregated environments and heterogeneous-ISA computing. The 2024 Best Paper Award at USENIX FAST highlights his impact in storage systems research. Best Paper Award at USENIX FAST'24 Multiple patents including US-9588912B2 for memory control He directs significant research projects funded by ETRI, NRF, and US ONR, including current work on memory-centric computing systems (2020-2023) and disaggregated non-volatile memory systems using RDMA (2018-2020). His Systems Software Lab maintains strong industry partnerships with Samsung Electronics and NHN, with prior projects improving Android memory management and developing SSD-based storage systems for large-scale internet services.

Anil Madhavapeddyمشاهده پروفایل

استاد

• Planetary Computing
• Computer Systems
• Programming Languages
• +۷ مورد دیگر

Anil Madhavapeddy is the Professor of Planetary Computing at the University of Cambridge Computer Laboratory, where he co-leads the Energy & Environment Group and is a member of the Systems Research Group. He is also a Fellow at Pembroke College where he serves as Director of Studies in Computer Science. Madhavapeddy completed his PhD from the University of Cambridge in 2003 and his BEng in Information Systems Engineering from Imperial College in 1999. He holds a JM Keynes Fellowship since 2022 for his work combining computer science with economics, and serves on the management committee of the Cambridge Conservation Initiative where he co-directs 4C (Cambridge Centre for Carbon Credits) and the Centre for Earth Observation. His research spans computer systems and programming languages with a strong focus on applying these technologies to global conservation, biodiversity, and climate change challenges. He leads the OCaml Labs group and has made significant contributions to open-source projects including OCaml, Docker, Xen, and OpenBSD. His work often bridges computer science with environmental science, developing computational approaches to address planetary-scale challenges. Madhavapeddy's recent publications demonstrate a clear trajectory toward integrating programming language research with environmental monitoring and conservation. His work spans from foundational programming language techniques to applied geospatial computing systems, with increasing emphasis on biodiversity measurement, carbon credit systems, and planetary-scale environmental monitoring. JM Keynes Fellowship (2022-present) As an educator, Madhavapeddy teaches undergraduate courses including Foundations of Computer Science, Software & Security Engineering, and Cloud Computing. He mentors MPhil and PhD students and co-founded the award-winning book 'Real World OCaml' (2nd Edition, 2022). He has co-founded several companies including Unikernel Systems, High Energy Magic, Segfault, and Tarides to translate research into real-world impact. Madhavapeddy leads the OCaml Labs group at Cambridge and works closely with the Energy & Environment Group, collaborating with colleagues from Plant Sciences, Zoology, Economics, and NGOs including UNEP-WCMC and the IUCN. His current efforts are primarily focused on conservation technology through partnerships with organizations like Canopy PACT.

Stefano Markidisمشاهده پروفایل

استاد

• High-Performance Computing
• Heterogeneous Systems
• Quantum Computing
• +۳ مورد دیگر

Stefano Markidis is a Professor of Computer Science specializing in high-performance computing systems at KTH Royal Institute of Technology in Sweden. He works in the Division of Computational Science and Technology, focusing on supercomputers, quantum computers, and computational methods for scientific simulations. His research spans multiple domains including plasma physics, computational fluid dynamics, and quantum computing. Markidis holds an MS degree from Politecnico di Torino and a PhD in Nuclear Engineering from the University of Illinois at Urbana-Champaign. Prior to joining KTH, he was a graduate research assistant at Los Alamos National Laboratory and Lawrence Berkeley National Laboratory, followed by a postdoc at KU Leuven. His academic journey reflects a strong foundation in both engineering and computational science. His primary research interests include High-Performance Computing , Heterogeneous Systems , and Quantum Computing . Markidis develops computational methods for plasma physics, particle-in-cell simulations, and fluid dynamics. His work bridges theoretical physics and practical computing, with applications in space physics, fusion energy, and materials science. He is particularly known for contributions to parallel computing, GPU acceleration, and the development of scalable simulation frameworks like Neko for computational fluid dynamics. His research increasingly integrates machine learning techniques with traditional numerical methods. Analysis of Markidis' recent publications reveals a strong focus on quantum-classical hybrid computing, advanced particle-in-cell methods, and high-fidelity computational fluid dynamics. His work demonstrates expertise in programming models for heterogeneous architectures including GPUs and quantum processors, with growing emphasis on AI-enhanced scientific computing. R&D100 award (2005) for the CartaBlanca project R&D100 award (2017) for the SHIELDS project Markidis teaches multiple courses at KTH including Applied GPU Programming, Quantum Computing for Computer Scientists, and High-performance Computing for Computational Scientists. He has supervised numerous degree projects across various specializations in computer science and electrical engineering. His research has been supported by various grants related to high-performance computing and quantum technologies, with applications spanning from space physics to medical treatments. Markidis leads research in computational science with a focus on developing frameworks like Neko for extreme-scale computational fluid dynamics. His team works on integrating traditional HPC methods with emerging technologies including quantum computing and AI, contributing to advancements in scientific simulation across multiple disciplines.