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Fredrik KjolstadView profile

Assistant Professor

• Compilers
• Programming Models
• Performance Engineering
• +3 more

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.

Jaejin LeeView profile

Professor

• Programming systems of heterogeneous machines
• Parallelization and optimization of deep learning frameworks
• Deep learning compilers/architectures
• +1 more

Jaejin Lee is a Professor in the Department of Computer Science and Engineering at Seoul National University (SNU) and serves as the Director of the Center for Manycore Programming and Multicore Computing Research Laboratory. He holds a BS in Physics from SNU (1991), an MS in Computer Science from Stanford University (1995), and a PhD in Computer Science from the University of Illinois at Urbana-Champaign (1999), where his research was supported by IBM and Korea Foundation for Advanced Studies fellowships. Research Focus: His work centers on heterogeneous computing systems with expertise in GPU/FPGA programming, deep learning compiler architectures, PyTorch/TensorFlow optimization, and quantum computing simulation environments. Key areas include parallelization techniques and performance enhancement for machine learning frameworks. Publications: His research output demonstrates consistent focus on GPU efficiency, compiler-directed optimizations, and distributed computing, with recent emphasis on deep learning acceleration and error resilience in heterogeneous architectures. Awards & Honors: IEEE Fellow IBM Graduate Fellowship Korea Foundation for Advanced Studies Graduate Fellowship Leadership: Directs the Multicore Computing Research Laboratory and Center for Manycore Programming, focusing on next-generation parallel computing architectures.

Stefano MarkidisView profile

Professor

• High-Performance Computing
• Heterogeneous Systems
• Quantum Computing
• +3 more

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.

Sidi Mohamed BeillahiView profile

Lecturer

• Formal Verification
• Programming Languages
• Smart Contracts
• +4 more

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.

• Programming Languages
• Formal Verification
• Compilers
• +8 more

Clément Pit-Claudel is an assistant professor at École Polytechnique Fédérale de Lausanne (EPFL) in the School of Computer and Communication Sciences, Department of Computer Science. He leads the SYSTEMF lab which he founded in January 2023. Prior to joining EPFL, he was a PhD candidate at MIT with Adam Chlipala and subsequently worked as a senior applied scientist at Amazon AWS. His academic journey began at École Polytechnique in France, followed by doctoral studies at MIT. Dr. Pit-Claudel's research focuses on programming languages, compilers, and formal verification, with broader interests spanning systems engineering, hardware design languages, security, performance engineering, databases, and type theory. His work centers around three main axes: extensible compilation (teaching compilers domain-specific optimization tricks), hardware design languages and verification, and tooling for proof assistants. He has developed several influential systems including Elk (a linear-time engine for JavaScript regexes), Warblre (a Coq translation of JS regex specification), Fiat (a library for correct-by-construction refinement), Narcissus (for verified binary encoders/decoders), F2F (a program extraction framework), Rupicola (a compiler-construction toolkit), Kôika (a rule-based hardware design language), Cuttlesim (a fast hardware simulator), and Alectryon (a literate programming system for Coq). His publications span top venues including PLDI, POPL, ICFP, ASPLOS, and SLE, with recent work focusing on verified JavaScript regular expressions, foundational integration verification of cryptographic servers, and relational compilation techniques. His research aims to build small, fast, and completely verified components for critical systems through a combination of machine-checked proofs, hardware-software co-design, low-level compiler engineering, and new tools for interactive theorem proving. His notable awards include the Distinguished Artifact award at SLE 2020 for 'Untangling Mechanized Proofs,' the William A. Martin Memorial Thesis Award from MIT in 2016, and the Frederick C. Hennie III Teaching Award from MIT in 2016. He has served on program committees for numerous conferences including PLDI, POPL, ICFP, and SPLASH, and has organized workshops such as the Coq Workshop and Proof Systems. As an educator, he teaches 'Software Construction' (undergraduate level, ~400 students) and 'Interactive Theorem Proving' (graduate level) at EPFL. His teaching philosophy emphasizes hands-on learning, continuous assessment through oral examinations, and designing assignments that lead students to build concrete artifacts they can be proud of. His approach is informed by hundreds of hours of in-class instruction in Europe and the US, resulting in stellar student reviews and multiple teaching awards.

Marc PouzetView profile

Professor

• Programming Languages
• Synchronous Systems
• Reactive Systems
• +3 more

Marc Pouzet is a Professor at École Normale Supérieure (ENS) in the Department of Computer Science (DIENS), where he serves as Director of CS studies. He leads the INRIA project-team PARKAS and was a Junior Member of the Institut Universitaire de France (2007–2012). His research centers on synchronous programming languages for safety-critical embedded systems, with contributions to real-time software verification, hybrid systems modeling, and probabilistic reactive programming. Research Focus Pouzet's work bridges theory and practice in: Synchronous Languages : Design/extensions of Lustre, Lucid Synchrone, and Zelus for embedded control Formal Methods : Mechanized semantics (Coq) and verified compilers (Vélus) for correctness guarantees Hybrid Systems : Integrating ODEs with discrete logic (ProbZelus for probabilistic inference) Real-time Systems : Scheduling, latency constraints, and memory-safe compilation Awards & Leadership Inria–Académie des sciences Innovation Award (2016) Program committees: EMSOFT, PLDI, POPL, ECRTS Associate Editor: EURASIP Journal on Embedded Systems Advising & Projects Supervised 19+ PhD students on topics spanning compiler verification (Bourke, Pesin), probabilistic languages (Baudart), and hybrid systems (Pauget). Leads development of open-source tools: Zelus (synchronous language with ODEs) Vélus (verified Lustre compiler) ReactiveML (reactive extension of OCaml)

• Scientific Computing
• Parallel Computing
• Numerical linear algebra
• +3 more

Konstantinos Giannoutakis serves as an Assistant Professor in the Department of Applied Informatics at the University of Macedonia, where he actively contributes to teaching and research in computational methods and applied informatics. His role encompasses both academic instruction and scholarly publication within the university's technical faculties. His educational foundation includes: B.Sc. in Mathematics from the University of the Aegean M.Sc. in Computational Science from the University of Athens Ph.D. in Electrical and Computer Engineering from Democritus University of Thrace Dr. Giannoutakis' research centers on advanced computational techniques, with significant focus on Scientific Computing and Parallel Computing architectures. His work in Numerical linear algebra develops optimized approaches for sparse linear systems, while his expertise in Finite difference and finite element methods supports complex scientific simulations. The Algorithms evaluation component of his research ensures computational efficiency across diverse mathematical applications. He instructs key undergraduate courses including Algorithm Analysis (CSC401), Discrete Mathematics (AIC203), and Mathematical Analysis (AIC104), demonstrating commitment to foundational computer science education. His substantial publication portfolio comprises 27 books, 37 scientific journal articles, and 34 conference papers, though specific recent works were not detailed in the source material. No scientific awards, research grants, advised students, or laboratory affiliations were documented in the available information.

• Computational Fluid Mechanics
• Hydrodynamic Machines
• Hydroelectric Energy
• +8 more

Anagnostopoulos Ioannis serves as Full Professor at the National Technical University of Athens (NTUA), School of Mechanical Engineering, Department of Fluids since 2016, with additional role as Member of the Regulatory Authority of Energy (RAE). Education: 1994: Diploma in Pedagogical Studies, PATES/SELETE, Greece 1991: Dr. Mechanical Engineer NTUA in Computational Fluid Mechanics 1985: Diploma in Mechanical Engineering, NTUA Research Focus: Professor Anagnostopoulos specializes in computational simulation of steady and unsteady flows in hydrodynamic machinery and installations. His work spans transient phenomena analysis, fault diagnosis systems, and optimization of renewable energy production systems with particular emphasis on hydroelectric applications and marine energy recovery. Honors: 1980, 1981 IKY scholarship recipient 1979 'Diomedes Komnenos' Award from NTUA Leadership: He directs the Hydrodynamic Machines Laboratory at NTUA and serves on the Coordinating Committee for the 'Microsystems and Nanodevices' Master's Program. His national influence extends to the Energy Regulatory Authority Board of Directors. Teaching: Professor Anagnostopoulos instructs undergraduate courses in Hydrodynamic Machines and Hydroelectric Energy, and postgraduate studies in Microfluidic Systems, bridging theoretical fluid dynamics with practical engineering applications.