High-Performance Computer Architectures Professors and Supervisors in Greece

Kyriazis Demosthenisمشاهده پروفایل

استاد

University of PiraeusGreece

Professor Kyriazis Demosthenis serves as a Professor in the Department of Digital Systems at the University of Piraeus and currently holds the position of Vice-Chancellor for Research and Lifelong Learning. His academic career spans over two decades with significant contributions to service-oriented architectures and cloud computing. His educational background includes: Diploma in Electrical and Computer Engineering from the National Technical University of Athens (NTUA) in 2001 Interdepartmental postgraduate diploma in "Techno-Economic Systems" in 2004 (NTUA, National Kapodistrian University of Athens, University of Piraeus) PhD in Electrical and Computer Engineering from NTUA in 2007, specializing in Service-Oriented Architectures Professor Kyriazis focuses on service-oriented, distributed and heterogeneous systems with particular expertise in software technologies and data analysis. His work bridges theoretical frameworks with practical implementations in cloud infrastructure management. His research has evolved to address emerging challenges in virtualization technologies for high availability of cloud computing infrastructures and management techniques in Internet of Things environments. He has demonstrated leadership in European research initiatives, coordinating multiple projects and serving in prominent research groups including the Future Internet Architecture Board and Cloud QoS&SLAs. His work has practical applications across multimedia, virtual reality, and health domains. Throughout his career, Professor Kyriazis has participated in numerous European and Greek research projects including BigDataStack, CrowdHEALTH, MATILDA, 5GTANGO, CYBELE, ORBIT, VISION Cloud, IRMOS, and 4CaaSt. His research leadership extends to coordinating relevant European projects in the IoT and cloud computing domains.

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Ioannis Skarmoutsosمشاهده پروفایل

استادیار

University of IoanninaGreece

Ioannis Skarmoutsos is an Assistant Professor at the Department of Chemistry, University of Ioannina , specializing in Theoretical-Computational Physical Chemistry . His research employs multi-scale molecular simulations and statistical engineering theories to investigate complex fluid systems. Focus on supercritical fluids, ionic liquids, and nanoporous materials Applications in green chemistry, energy storage, and environmental technology Expertise in molecular dynamics and computational modeling Recent publications highlight his work on electrolyte design for batteries, nanoporous material simulations for gas separation, and anomalous properties of water under extreme conditions. His computational approaches address challenges in solvation dynamics, dielectric properties, and structural transitions across diverse thermodynamic states.

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Ying Wangمشاهده پروفایل

دانشیار

National and Kapodistrian University of AthensGreece

Dr. Ying Wang is an Associate Professor and Assistant Dean at the Software College of Northeastern University in China, where she also serves as a doctoral supervisor. She received her PhD in Software Engineering from Northeastern University in January 2019 and joined the faculty in February 2019. Her academic career includes a postdoctoral fellowship at the Hong Kong University of Science and Technology (2022-2023) and a visiting scholar position at Microsoft Research Asia (2021) through the StarTrack Program. Her research focuses on dependency management, software ecosystem governance, software refactoring, and software supply chain security. She has made significant contributions to understanding cross-language dependencies, vulnerability propagation across ecosystems, and developing tools for dependency conflict detection and resolution. Her work spans multiple programming language ecosystems including Java, C#, Python, Go, JavaScript, Android, and Rust. Dr. Wang's publication record shows a consistent trajectory of high-impact research in top software engineering conferences (CCF-A level) including ASE, ICSE, ESEC/FSE, and ISSTA. Her recent work increasingly integrates large language models with traditional software engineering techniques, particularly in dependency analysis and software refactoring. The publications demonstrate a strong emphasis on practical tool development with industry applications. Microsoft Research Asia Star Program Scholar (2020) CCF Outstanding Doctoral Dissertation Award nomination (2020) Liaoning Province Outstanding Doctoral Dissertation Award (2021) ACM SIGSOFT Distinguished Paper Award (ICSE 2021 and ESEC/FSE 2023) Multiple CCF ChinaSOFT Software Prototype Competition awards (2020, 2023) OpenHarmony Community Security Governance Contributions (2024, 2025) Dr. Wang actively mentors a large group of graduate students working on various aspects of software engineering, with many graduates securing positions at major technology companies including Huawei, Microsoft, Alibaba, and Tencent. She serves on the editorial board of IEEE Transactions on Software Engineering and has held numerous program committee positions at top software engineering conferences. Her research has strong industry connections, with several tools developed by her team being integrated into commercial platforms at Huawei and Microsoft.

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Yufei Dingمشاهده پروفایل

دانشیار

National and Kapodistrian University of AthensGreece

Yufei Ding is an Associate Professor in the Computer Science & Engineering Department at the University of California, San Diego (UCSD), where she leads the PICASSO Lab. Her research spans domain-specific language design, architecture and compiler optimization, and hardware acceleration, with current focus on developing high-performance, energy-efficient, and high-fidelity programming frameworks for quantum computing and machine learning. Dr. Ding received her Ph.D. in Computer Science from North Carolina State University and a B.S. in Physics from the University of Science and Technology of China. Her interdisciplinary background bridges physics and computer science, enabling her to tackle challenges in emerging computing paradigms. Her research interests focus on Compiler Technology, Machine Learning, and Quantum Computing , with specific expertise in domain-specific language design, architecture and compiler optimization, and hardware acceleration. Dr. Ding's work addresses critical challenges in programming frameworks for emerging technologies, particularly in making quantum computing more accessible and efficient through innovative compiler techniques and runtime systems. Dr. Ding's scientific contributions have been recognized with prestigious awards including the NSF CAREER Award (2020) and the IEEE Computer Society TCHPC Early Career Researchers Award for Excellence in High-Performance Computing (2019) . As an active researcher and educator, Dr. Ding serves on program committees for major conferences including PLDI, PPoPP, and SPLASH. She currently has Ph.D. openings in quantum computing and machine learning systems research, as well as a postdoc position in quantum computing for physics Ph.D. candidates with relevant background. Dr. Ding founded and leads the PICASSO Lab at UCSD, which focuses on developing innovative solutions for programming emerging computing technologies. The lab's work bridges theoretical foundations with practical implementations to address real-world challenges in high-performance computing.

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Gilbert Bernsteinمشاهده پروفایل

استادیار

National and Kapodistrian University of AthensGreece

Gilbert Bernstein is an Assistant Professor in the Computer Science & Engineering department within the College of Engineering at the University of Washington. His research bridges computer graphics and programming languages, with a focus on high-performance domain-specific languages. Previously, he was a post-doctoral scholar at UC Berkeley and MIT working with Jonathan Ragan-Kelley, and received his PhD from Stanford University under Pat Hanrahan. His research interests span Computer Graphics, Programming Languages, High-Performance DSLs, Physical Simulation, Geometry & Topology, Differentiable Programming, Hardware DSLs, Tools for Artists, Fabrication, and Human-Computer Interaction. Bernstein develops languages and compilers that enable efficient computation for creative applications, physical simulations, and graphics rendering systems. His recent publications reveal strong trends in differentiable programming for graphics applications, domain-specific languages for hardware acceleration, and computational approaches to traditional crafts like quilting and knitting. His work consistently combines formal language theory with practical applications in graphics and fabrication. Bernstein actively mentors students across multiple institutions including current advisees Felix Hahnlein (UW Postdoc), Ryan Zambrotta (UW PhD), Haoran Peng (UW PhD), and previous students including Alex Reinking (UC Berkeley PhD 2022, now at Qualcomm) and MacKenzie Leake (Stanford PhD 2021, now at Adobe Research). His lab works on diverse projects including debugging CAD programs, compilers for finite element methods, semantics for knitting machines, algebraic scheduling of tensor programs, and exocompilers for hardware accelerators. Bernstein also collaborates on DSLs for networking, Counterstrike bots, gradient-based optimization, memory management, hardware design, and garment design tools.

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Adam Chlipalaمشاهده پروفایل

استاد

National and Kapodistrian University of AthensGreece

Adam Chlipala is a Professor at the Massachusetts Institute of Technology working at the intersection of programming languages, formal methods, and computer systems. His research focuses on building practical verified systems with end-to-end machine-checked proofs, particularly using the Coq proof assistant. His educational background includes a Computer Science undergraduate degree from Carnegie Mellon University (2003) and a PhD in Computer Science from the University of California, Berkeley (2007). Following a postdoctoral position at Harvard University through 2011, he joined MIT as faculty. Chlipala's research spans multiple domains with strong emphasis on dependent types , verified compilation , and hardware-software co-verification . His work consistently bridges theoretical foundations with practical implementation, as evidenced by his development of the Ur/Web programming language and his focus on creating clean-slate hardware-software stacks with formal guarantees. Key research thrusts include cryptographic constant-time verification, side-channel security, and verified tensor compilation. His recent publications (2020-2025) reveal a clear trajectory toward increasingly complex verified systems, with growing emphasis on hardware-software integration, cryptographic implementations, and performance-critical applications. The work consistently leverages Coq for machine-checked proofs while addressing real-world constraints like timing channels and hardware interfaces. Chlipala is the author of the influential textbook Certified Programming with Dependent Types , which serves as a primary educational resource for Coq at numerous institutions worldwide. His professional activities include significant service to the PL community through program committees for major conferences including PLDI, POPL, ICFP, and CPP. He leads research initiatives connecting hardware and software verification, most notably through the DeepSpec project which aims to build fully verified computing stacks. His current work focuses on practical applications of dependent types for business applications through Ur/Web and verified cryptographic implementations.

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Rajiv Guptaمشاهده پروفایل

استاد

National and Kapodistrian University of AthensGreece

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.

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Konstantinos Kallasمشاهده پروفایل

استادیار

National and Kapodistrian University of AthensGreece

Konstantinos Kallas serves as Assistant Professor of Computer Science at the University of California, Los Angeles (UCLA), commencing his appointment in January 2025. Previously affiliated with the University of Pennsylvania as evidenced by his 2020 PLDI contribution, his research bridges theoretical formal methods with practical systems engineering across multiple high-impact conferences including PLDI, POPL, and SPLASH. His research program centers on enhancing computational efficiency and correctness in systems software, with three flagship projects defining his trajectory: PaSh for automatic shell script parallelization, Durable Functions for stateful serverless computing semantics, and DiffStream for differential testing of stream processing. These efforts consistently target the intersection of programming language theory and real-world systems constraints, particularly in parallelism, concurrency, and cloud-native environments where correctness guarantees are challenging to implement. Analysis of his publication history since 2020 reveals a methodological pattern: developing formal semantic models to enable practical optimizations in distributed systems. His work increasingly focuses on serverless architectures and data-intensive pipelines, with recent contributions emphasizing automated verification techniques. The evolution from shell script optimization (2020-2021) to serverless state management (2021-2022) demonstrates strategic expansion into cloud computing's hardest problems. Dr. Kallas actively contributes to the academic community through program committee service for PLDI (2022, 2025), POPL (2021, 2022, 2023), and SPLASH (2020-2023), including leadership roles as Publicity Co-Chair for PLDI 2025 and 2026. His June 2024 announcement confirms recruitment for Fall 2025 students at UCLA, targeting researchers interested in systems, compilers, and programming languages who can advance his work on correctness-preserving parallelization and serverless computing.

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Fredrik Kjolstadمشاهده پروفایل

استادیار

National and Kapodistrian University of AthensGreece

Fredrik Kjolstad is an Assistant Professor in the Department of Computer Science at Stanford University, specializing in compilers and programming models for sparse computing and performance engineering. His research focuses on separating algorithms from data representations to enable portable applications across diverse hardware platforms. His research interests span compilers, programming models, performance engineering, and computer architecture, with particular emphasis on sparse tensor algebra, compiler design for heterogeneous systems, and high-performance computing. He has pioneered frameworks like TACO, Simit, and Distal that enable efficient sparse computations across CPUs, GPUs, and specialized accelerators. Dr. Kjolstad's publications demonstrate expertise in compiler optimization techniques for sparse data structures, tensor algebra, and distributed systems. His work consistently addresses the challenge of bridging high-level programming abstractions with efficient hardware execution across diverse architectures. MIT EECS First Place George M. Sprowls PhD Thesis Award NSF CAREER Award Rosing Award Adobe Fellowship Google Research Scholarship Best Paper Awards at EuroMPI 2013, OOPSLA 2017, and OOPSLA 2021 ISCA Distinguished Artifact Award PLDI and OOPSLA Distinguished Paper Awards He advises multiple PhD students including James Dong, Olivia Hsu, and Rohan Yadav, while leading research on compiler technologies that have received significant grant support. His group develops practical tools like the TACO compiler and Legate Sparse that are used in both academic and industrial settings. Current projects focus on programmable accelerators for sparse tensor algebra, distributed sparse computing, and compiler support for emerging hardware architectures.

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Anil Madhavapeddyمشاهده پروفایل

استاد

National and Kapodistrian University of AthensGreece

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.

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Stefano Markidisمشاهده پروفایل

استاد

National and Kapodistrian University of AthensGreece

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.

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Kunle Olukotunمشاهده پروفایل

استاد

National and Kapodistrian University of AthensGreece

Kunle Olukotun is a Professor of Electrical Engineering and Computer Science at Stanford University's School of Engineering, where he has been faculty since 1991. He directs the Stanford Pervasive Parallelism Lab (PPL) and co-leads the Transactional Coherence and Consistency (TCC) project. His research focuses on computer architecture, parallel programming environments, and scalable parallel systems. Key areas include chip multiprocessors (CMPs), transactional memory systems, domain-specific languages (DSLs) for heterogeneous computing, and hardware-software co-design for machine learning workloads. His work bridges theoretical foundations with practical systems implementation. Notable contributions include the Stanford Hydra research project (one of the first chip multiprocessors with thread-level speculation), founding Afara Websystems (acquired by Sun Microsystems), and developing the Niagara processor architecture. His DSL frameworks like Green-Marl and Spatial enable efficient graph analysis and hardware acceleration. His publications reveal strong trends in parallel systems evolution: from foundational CMP research (2000s) to transactional memory (2004-2010), then DSLs for heterogeneous computing (2010-2015), and currently foundation model systems (2023-2025). Subfield analysis shows consistent focus on hardware-software co-design, sparse computation, and compiler techniques across decades. ACM Fellow (2006) for contributions to multiprocessors on a chip and multi-threaded processor design Best Paper Award at IEEE International Symposium on Workload Characteristics (IISWC '10) for EigenBench Olukotun actively mentors researchers through the Stanford Pervasive Parallelism Lab (PPL), which seeks to proliferate parallelism across application domains. His projects have secured significant industry partnerships, including the acquisition of his startup Afara Websystems by Sun Microsystems. Current research focuses on compiler frameworks for foundation model systems and hardware acceleration for sparse machine learning workloads, supported by collaborations with major tech companies. He leads the Stanford Pervasive Parallelism Lab (PPL), which develops compiler and runtime systems for heterogeneous architectures. The lab's work spans DSLs, hardware acceleration, and parallel programming models, with strong industry ties to companies like NVIDIA and Google. Current initiatives include the Mosaic compiler framework and Stardust architecture for sparse tensor computation.

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Fernando Magno Quintão Pereiraمشاهده پروفایل

دانشیار

National and Kapodistrian University of AthensGreece

Fernando Magno Quintão Pereira is an Associate Professor at the Federal University of Minas Gerais (UFMG), Brazil, specializing in compiler design and program analysis. His academic journey began with a Ph.D. from UCLA in 2008 under Jens Palsberg's supervision, establishing his foundation in compiler research. His research focuses on compilers , with core expertise in code generation , compiler optimizations , and static program analyses . Recent work explores quantum compilation, binary analysis, and security-aware compilation techniques. His publications reveal consistent contributions to major conferences including PLDI, CGO, and SPLASH, with emphasis on practical optimization frameworks and theoretical compiler advancements. Analysis of his 15 most recent publications (2020-2026) shows dominant themes in binary optimization (e.g., AnghaBench), security-aware compilation (e.g., Memory-Safe Elimination of Side Channels), and emerging architecture support (e.g., Quantum Computing Compilation). His work bridges theoretical compiler principles with real-world systems challenges. He actively contributes to the academic community through: Program committees for PLDI (2020-2025), CGO (2021-2026), and SPLASH conferences Leadership roles including CGO Finance Chair (2026) and PLDI Diversity & Inclusion Co-Chair (2023-2024) Organizing JENSFEST 2024 and serving on multiple conference steering committees Pereira maintains an active research group evidenced by continuous publication output and conference leadership, with his personal website ( homepages.dcc.ufmg.br/~fernando/ ) serving as a hub for his academic activities.

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