High-Performance Computing Professors and Supervisors in Greece

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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Sidi Mohamed Beillahiمشاهده پروفایل

مدرس

National and Kapodistrian University of AthensGreece

Sidi Mohamed Beillahi is a Lecturer in the Department of Computer Science at the University of Toronto's Faculty of Arts and Science. He teaches courses including Principles of Programming Languages (CSC324H1S) and Algorithms and Data Structures (ECE345H1F). Previously, he served as a Teaching Assistant at both University of Paris and Concordia University for courses ranging from Automata Theory to Hardware Functional Verification. Dr. Beillahi's research focuses on developing formal verification and programming languages techniques to ensure the correctness of software systems, particularly distributed systems, concurrent programs, blockchain, and smart contracts. His work bridges theoretical computer science with practical security applications in decentralized finance. His publication record shows a clear progression from quantum circuit verification during his Master's to blockchain and smart contract security in his doctoral and postdoctoral work. Recent publications demonstrate expertise in authenticated data structures for blockchain storage, flash loan attack analysis, and formal verification of decentralized applications. Scientific Awards: ACM SIGSOFT Distinguished Paper Award (ICSE '24) ICBC Distinguished Paper Award (ICBC '22) Dr. Beillahi has advised multiple research projects in blockchain security and verification, often collaborating with Professor Fan Long and Professor Andreas Veneris at the University of Toronto. His research has been supported by prestigious fellowships including an NSERC Postdoctoral Fellowship and a Mitacs Accelerate Fellowship.

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Mayur Naikمشاهده پروفایل

استاد

National and Kapodistrian University of AthensGreece

Mayur Naik is the Misra Family Professor in the Department of Computer and Information Science at the University of Pennsylvania's School of Engineering and Applied Science. He holds office in Room 642B, Amy Gutmann Hall and maintains an active research program focused on the intersection of programming languages and artificial intelligence. Before joining UPenn, he was faculty at Georgia Institute of Technology and a researcher at Intel Labs, Berkeley. Naik received his PhD in Computer Science from Stanford University in 2008 under Alex Aiken, a Masters from Purdue University in 2003 under Jens Palsberg, and a Bachelors from BITS Pilani in 1999. He grew up in Goa, India. His primary research interests center around neurosymbolic programming, which combines symbolic reasoning with machine learning to create more accurate, interpretable, and domain-aware AI systems. His group develops language design, learning algorithms, and compiler optimizations in this space, with their most mature effort being the Scallop neurosymbolic programming language and compiler toolchain. He also conducts research in trustworthy AI for healthcare applications and AI-enabled programming tools that improve programmer productivity. Analysis of his recent publications shows a strong trend toward neurosymbolic programming frameworks (Scallop, TorchQL), LLM-assisted program analysis (IRIS), and applications of these techniques to security, healthcare, and computer vision. His work consistently bridges theoretical foundations with practical implementations, often releasing open-source systems. Misra Family Professor (endowed chair, effective July 2024) Multiple distinguished paper awards (PLDI 2019, FSE 2015, PLDI 2014) Test-of-Time Paper Awards (FSE 2013, FSE 2012, EuroSys 2011) His student Elizabeth Dinella won the 2025 ACM SIGSOFT Outstanding Dissertation award Naik has advised numerous PhD students who have gone on to faculty positions at top institutions including Peking University, University of Toronto, Ashoka University, Bryn Mawr College, and Johns Hopkins University. His research is supported by grants from NSF, Google, Amazon, and other industry partners. His lab maintains active collaborations with clinicians and bioinformatics researchers to apply neurosymbolic programming to healthcare problems. His research group, which includes current PhD students and postdocs, develops practical open-source systems and applies them to diverse domains including computer vision, cybersecurity, medicine, and bioinformatics. The group maintains strong industry connections with Google, Microsoft, Amazon, and other tech companies.

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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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Bryan Parnoمشاهده پروفایل

استاد

National and Kapodistrian University of AthensGreece

Bryan Parno is the Kavčić-Moura Professor of Electrical & Computer Engineering and Computer Science at Carnegie Mellon University, where he leads the Secure Foundations Lab within CyLab, CMU's Security & Privacy Institute. His research combines theory and practice to provide formal, rigorous security guarantees about concrete systems, with emphasis on creating solid foundations for practical solutions. His research spans secure systems , formal software verification , applied cryptography , data privacy , and usable security . Current work focuses on protocols for verifiable computation and zero-knowledge proofs, building practical formally verified secure systems, and developing next-generation application models. His lab maintains a strong commitment to reproducibility, open-sourcing code under permissive licenses, and avoiding patenting results to maximize public benefit. His recent publications demonstrate a clear trend toward practical verification of real-world systems, particularly through the Verus project for verifying Rust code, Everest for building verified HTTPS stacks, and Ironclad for provably secure systems. These works bridge the gap between theoretical security guarantees and practical implementation, with applications ranging from blockchain protocols to verified cryptographic libraries deployed in the Linux kernel. His scientific achievements include multiple Distinguished Paper/Artifact Awards (USENIX Security, SOSP, PLDI), the IEEE Cybersecurity Award for Practice , the Sloan Fellowship , and the ACM Doctoral Dissertation Award . His work on verifiable computation protocols has influenced blockchain systems, while his research on secure code execution environments contributed to Intel's SGX and TDX technologies. As an advisor, Parno has mentored numerous PhD students including Aymeric Fromherz (recipient of the ACM SIGSAC Doctoral Dissertation Award) and Jay Bosamiya. His lab receives funding from diverse sources including NSF, industry partners, and security foundations. Notably, his work has been incorporated into Windows 8+, iOS 13+, and the Linux kernel. He also serves in leadership roles including Chair of IEEE Computer Society's Technical Committee on Security & Privacy. The Secure Foundations Lab maintains strong industry connections, with alumni joining Microsoft Research, Inria, Northeastern University, and other leading institutions. Recent projects like Verus, Everest, and Ironclad represent the lab's commitment to building end-to-end verified systems that provide rigorous security guarantees while maintaining practical performance.

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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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Angelo Sifalerasمشاهده پروفایل

استاد

University of MacedoniaGreece

Angelo Sifaleras is a Full Professor at the Department of Applied Informatics, School of Information Sciences, University of Macedonia (Thessaloniki, Greece). He also serves as an Adjunct Professor of Quantitative Methods at the Hellenic Open University. His academic credentials include a Ph.D. in Applied Informatics (University of Macedonia, 2007) and a B.Sc. in Mathematics (Aristotle University of Thessaloniki, 1999). Research Focus: Professor Sifaleras specializes in Mathematical Programming , Network Optimization , and Heuristic Methods . His work integrates computational optimization with real-world logistics, supply chains, and sustainable systems. Key research themes include metaheuristic algorithms for vehicle routing, pollution-aware logistics, and parallel computing solutions for network analysis. Publication Trends: His 15 most recent articles emphasize hybrid metaheuristics (e.g., combining reinforcement learning with Variable Neighborhood Search), sustainable supply chain modeling, and high-performance computing applications. Dominant domains include operations research, environmental optimization, and educational algorithm visualization. Teaching & Service: He instructs courses in Combinatorial Optimization, Linear Algebra, and Heuristic Methods, employing tools like CPLEX, Gurobi, and SageMath. As an editor for Operations Research Forum and the Yugoslav Journal of Operations Research , he supports academic discourse in optimization. A Senior ACM member, he contributes to conferences like ICVNS and ITS.

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Nikolaos Bakasمشاهده پروفایل

استادیار

The American College of GreeceGreece

Dr. Nikolaos Bakas serves as an Assistant Professor in the Information Technology Department at the School of Liberal Arts and Sciences, The American College of Greece, Deree. His academic profile centers on bridging theoretical mathematics with practical machine learning implementations through rigorous algorithmic development. His research program focuses on fundamental mathematical modeling of machine learning systems , with specialized expertise in Numerical Methods and High-Performance Computing (HPC) . Key contributions include stochastic optimization algorithms (notably the ITSO framework), gradient-free neural network training techniques, and computational mechanics applications. This interdisciplinary work connects theoretical mathematics with engineering solutions in structural analysis and environmental risk assessment. Analysis of his 2019-2023 publications reveals a clear trajectory toward practical HPC implementations of machine learning frameworks, with increasing emphasis on domain-specific applications. His research consistently addresses computational efficiency challenges while maintaining mathematical rigor, particularly in stochastic search methods and partition-based approximation systems. As Principal Investigator for multiple industry and academic projects, Dr. Bakas demonstrates active research leadership with direct organizational consulting experience. His project portfolio indicates strong translation of theoretical research into real-world AI and HPC adoption, though specific grant details remain undisclosed.

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