Find Academic Supervisors

Ryan GrantView profile

Assistant Professor

• Cloud Computing
• High Performance Networks
• Low-level Hardware-Software Interfaces
• +6 more

Dr. Ryan Grant is an Assistant Professor in the Department of Electrical and Computer Engineering at Queen’s University, Canada. He leads the Computing at Extreme Scale Advanced Research (CAESAR) lab and is affiliated with the Ingenuity Labs Research Institute. His expertise spans cloud computing, high-performance networks, low-level hardware-software interfaces, and energy-efficient supercomputing systems. Dr. Grant holds a PhD from Queen’s University (2012) and previously worked at Sandia National Laboratories (2012–2021), where he contributed to critical supercomputer communication protocols now deployed globally. He has authored over 80 peer-reviewed articles and received prestigious awards including the R&D100 Award and Queen’s University’s 125th Engineering Alumni Award. His research emphasizes advancing Canada’s supercomputing infrastructure to support AI, climate science, and national security applications. Education: PhD in Computer Engineering, Queen’s University (2012) MSc in Computer Engineering, Queen’s University (2005) BSc in Computer Engineering, Queen’s University (2004) Research Interests: Dr. Grant’s work focuses on optimizing supercomputing architectures for extreme-scale systems, with an emphasis on: High-performance networking and MPI communication protocols Power/energy management in HPC systems AI-driven network traffic prediction and resource disaggregation GPU-accelerated computing and cloud infrastructure integration National sovereignty in supercomputing for sensitive applications (e.g., defense, healthcare) Awards & Recognition: R&D100 Award (Oscars of Research) U.S. Defense Programs Awards Public Good Innovator Award Queen’s University 125th Engineering Alumni Award Grants & Labs: Dr. Grant directs the CAESAR lab, one of the world’s leading supercomputing architecture research groups. His work is supported by grants from Canadian and international agencies, focusing on sovereign supercomputing and HPC-AI convergence. Labs/Teams: CAESAR Lab (Queen’s University) Ingenuity Labs Research Institute

Biagio CosenzaView profile

Associate Professor

• High-performance computing
• Compiler technology
• Software optimization
• +7 more

Biagio Cosenza is an Associate Professor at the Department of Computer Science, University of Salerno, Italy. He leads research in high-performance computing, compiler technology, and software optimization. Previously, he was a Senior Researcher at TU Berlin (2015-2019) and a Post-Doctoral Researcher at the University of Innsbruck, Austria (2011-2015). His educational background includes: Ph.D. from University of Salerno (2011), supervised by Prof. Vittorio Scarano Dr. Cosenza's research focuses on creating efficient programming models for heterogeneous computing systems. His work spans compiler technology, automatic performance tuning, and energy-efficient computing approaches. He has made significant contributions to SYCL-based programming models and MPI implementations, with emphasis on portability across diverse hardware platforms including GPUs and accelerators. His research often bridges theoretical computer science with practical applications in scientific computing and bioinformatics. His recent publications demonstrate a strong trend toward heterogeneous and distributed computing, with particular emphasis on energy efficiency, performance portability, and SYCL-based programming models. Many papers focus on applications in drug discovery and scientific simulations, showing how his theoretical work translates to real-world scientific problems. Dr. Cosenza has received several prestigious recognitions: Best Paper Award at the 14th BenchCouncil International Symposium (2022) Elevated to Senior Member of the IEEE (2022) Recognized as ACM Senior Member (2022) He leads multiple significant research projects including the PRIN 2022 project "LibreRT" and the EuroHPC project "LIGATE." His work has secured substantial funding from sources including the German Research Foundation (DFG), the Italian Ministry of Education, University and Research, and EuroHPC. He actively mentors students and collaborators on advanced topics in high-performance computing. Dr. Cosenza is a member of the ISIS Lab at the University of Salerno and contributes to open standards through his work with the Khronos Group and SYCL Working Group. His research group develops tools like CELERITY, a C++ SYCL-based programming model for accelerator clusters, and EMPI, an enhanced message passing interface in modern C++.

Jannek SquarView profile

Researcher

• High-Performance Computing
• Parallel Computing
• Code Transformation
• +5 more

Dr. Jannek Squar is a researcher affiliated with the University of Hamburg and the German Climate Computing Centre (DKRZ). His work focuses on high-performance computing (HPC) infrastructure, code transformation, and parallelization techniques. Academic Rank: Researcher Key Projects: i_SSS (Integrated Support System for Sustainability), HLRE-5 Supercomputer Procurement His research spans automatic code transformation using LLVM , parallelization via OpenMP/MPI , and high-performance I/O optimization . Recent publications highlight applications in sustainable agriculture and compiler-assisted HPC performance analysis. He has supervised multiple theses on topics including elastic cloud solutions, MPI communication modeling, and LLVM-based code verification. No scientific awards are explicitly mentioned in the provided text.

• Parallel Computing
• Java Virtual Machine (JVM) Optimization
• Performance Profiling
• +5 more

Walter Binder is a Full Professor in the Faculty of Informatics at the Università della Svizzera italiana (USI). He holds a MSc, PhD, and venia docendi from Vienna University of Technology. Previously, he was a senior researcher at the Artificial Intelligence Laboratory, EPFL. His research focuses on program transformations, virtual execution environments, aspect-oriented programming, profiling, and resource management. Education: MSc from Vienna University of Technology PhD from Vienna University of Technology Venia docendi (Habilitation) from Vienna University of Technology Research Interests: His work spans JVM optimization, parallel computing, and dynamic program analysis. Notable contributions include tools like Renaissance (a JVM benchmark suite), S2S (SQL-to-Stream translator), and Akkaprof (profiler for actor-based systems). He explores topics such as thread management, vectorization, and performance profiling in distributed systems. Articles Trends: Recent work emphasizes JVM performance (e.g., Java Vector API, Native Image optimizations), parallel execution policies (NAS benchmarks), and adaptive runtime systems (e.g., MPR framework). He also investigates big data systems (Spark, Node.js) and runtime verification tools. Grants & Labs: Leads projects on JVM profiling, polyglot runtimes, and large-scale program analysis. His lab develops tools like NodeMOP for Node.js and AccStream for stream processing systems.

Bengisu ElisView profile

Researcher

• High-Performance Computing (HPC)
• Parallel Computing
• GPU Programming
• +5 more

Bengisu Elis is a researcher at the Chair of Computer Architecture & Parallel Systems at the Technical University of Munich . Her work focuses on High-Performance Computing (HPC) , GPU programming, and parallel systems. Email: bengisu.elis@tum.de Room: 01.04.037, Garching near Munich Research Interests : Elis specializes in GPU-CPU parallelism , MPI profiling , and performance modeling for HPC systems. Her work addresses challenges in: Optimizing synchronization mechanisms Reducing memory access overhead Enhancing task scheduling Scientific Awards : HPCAsia '24 Best Paper Award Winner Teaching & Advising : Elis has supervised multiple master's theses and internships, including: Jakob Schäffeler (2025) - Comparing GPU Programming Models Tizian Leonhardt (2024) - Low-overhead Sampling Techniques

• High-Performance Computing
• Parallel Computing
• Distributed Systems
• +6 more

Marc Snir is a Professor at the University of Illinois’s Siebel School of Computing and Data Science. He has led significant research contributions in high-performance parallel computing, including work on the Message Passing Interface (MPI) and IBM’s SP scalable parallel system. As Department Head from 2001–2007, he oversaw the transition to the Siebel Center and expanded the department’s capabilities. He later served as the first director of the Illinois Informatics Institute, chief software architect for the Blue Waters supercomputer, and co-director of the Universal Parallel Computing Research Center (UPCRC). His research focuses on parallel computing systems, fault resilience, and I/O optimizations. He has been recognized with the 2014 Distinguished Alumni Service Award. His work spans exascale computing, distributed systems, and machine learning applications in HPC. He has contributed to projects like Argo (an exascale OS/runtime), Aluminum (a GPU-aware communication library), and LCI (Lightweight Communication Interface). His research emphasizes improving scalability, energy efficiency, and reliability in high-performance systems. He has advised numerous students (names not listed here) and led teams in advancing HPC tools and methodologies. His involvement in initiatives like UPCRC and the Blue Waters project underscores his commitment to bridging theoretical research and practical applications in computing.

• High-Performance Computing
• Parallel Computing
• Distributed Systems
• +4 more

George Bosilca is a Professor at the University of Tennessee, Knoxville, specializing in high-performance computing and parallel systems. With over two decades of research contributions, he has established himself as a leading expert in task-based runtime systems, distributed computing, and MPI implementations. His research focuses on developing and optimizing task-based runtime systems for extreme-scale computing environments, with particular emphasis on fault tolerance, performance optimization, and scalability. Bosilca's work spans multiple domains including scientific computing, climate modeling, and deep learning applications. He has made significant contributions to the PaRSEC runtime system and has extensively researched MPI optimization techniques for modern HPC architectures. The trend in Bosilca's recent publications demonstrates a strong focus on addressing challenges in exascale computing, including fault tolerance in distributed systems, GPU acceleration for scientific workloads, and energy-efficient computing techniques. His work bridges theoretical computer science with practical implementations for real-world scientific applications across various domains. Bosilca maintains extensive collaborations with leading researchers in the HPC community, most notably with Jack J. Dongarra (103 co-publications), Aurelien Bouteiller (60 co-publications), and Thomas Hérault (54 co-publications). These collaborations have resulted in numerous publications at top-tier conferences including SC, IPDPS, and EuroMPI, as well as in prestigious journals such as IEEE Transactions on Parallel and Distributed Systems and the International Journal of High Performance Computing Applications.

• Computer Vision
• Image Processing
• Lighting Technology
• +4 more

Géza Várady is an Associate Professor at the University of Pécs (PTE), holding roles such as Vice Dean for Scientific Affairs at the Faculty of Engineering and Information Technology. He has served as Head of the Department of Technical Informatics and has held various academic leadership positions. His career spans over two decades, with research focusing on computer vision, image processing, and lighting technology. He holds a PhD from the Doctoral School of Informatics at the University of Pannonia. Education includes a Master’s degree in Computer Engineering and a PhD in Informatics. He has also held research positions internationally, such as a Leonardo Fellowship at Schefenacker GmbH in Stuttgart, Germany. His research interests include mesopic vision models, color correction systems, 3D depth sensing using monocular cameras, and drone-based applications. He leads the drone research team and has supervised doctoral students in areas like image data correction and 3D modeling. Notable achievements include the 2024 Publication Excellence Award, IBM Faculty Awards for adaptive lighting systems, and the Walsh Weston Award for contributions to lighting science. He actively participates in academic governance, serving on national committees like the Hungarian Academy of Sciences’ Engineering Sciences Committee and the John von Neumann Computer Society. Publications span over 100 articles in journals like Lighting Research and Technology and Technical Gazette , focusing on topics ranging from photogrammetry to autonomous drone control. He has authored textbooks on MPI programming and computer architecture.

• Distributed Computing
• High-Performance Computing
• Distributed Shared Memory
• +7 more

Tore Brox-Larsen is an Associate Professor in the Department of Informatics at UiT The Arctic University of Norway. His work centers on distributed computing, high-performance systems, and large-scale visualization technologies. He is actively engaged in research involving sensor networks, Arctic observatories, and remote visualization of scientific data. His research interests span distributed shared memory systems, MPI performance, tiled display walls, and networked visualization. He has made significant contributions to improving communication efficiency in cluster computing and enabling scalable interactive visualization environments. His work bridges computer systems engineering with applications in genomics and environmental monitoring. The most recent publications reflect a strong trend toward real-world deployment of large-scale systems, particularly in Arctic observation and healthcare informatics. His work emphasizes practical system design, latency optimization, and cross-platform interoperability in distributed environments. Tore Brox-Larsen has collaborated extensively with researchers such as Otto Anshus, John Markus Bjørndalen, and Brian Vinter. While no formal advising or grant history is listed, his sustained publication record indicates active research leadership and team-based scientific inquiry. He has contributed to major projects including the development of a large-scale Arctic observatory sensor system and interactive tiled display walls. His work supports both academic research and societal applications in health and environmental science.

• High Performance Computing
• Parallel Computing
• Message Passing Interface
• +3 more

William D Gropp is a Professor of Computer Science at the University of Illinois at Urbana-Champaign holding the Thomas M. Siebel Chair, and serves as Acting Director and Chief Scientist of the National Center for Supercomputing Applications (NCSA). His career spans foundational contributions to parallel computing infrastructure and scientific computation. Gropp pioneered the Message Passing Interface (MPI) standard and developed MPICH—the reference implementation that became the global lingua franca for parallel programming. His work enables portable scientific applications across supercomputing platforms, driving advances in fluid dynamics, nanosimulations, biology, and fusion research through tools like the Portable, Extensible Toolkit for Scientific Computation (PETSc). His major honors include: ACM Software System Award (2024) for MPICH's 30-year impact ACM-IEEE CS Ken Kennedy Award (2016) for programmability contributions SIAM/ACM Prize (2015) for computational science engineering ACM, IEEE, and SIAM Fellowships Election to the National Academy of Engineering Gropp co-founded ACM SIGHPC in 2011 and authored 187+ publications including the seminal book Using MPI . His NCSA leadership advances supercomputing infrastructure for nationwide scientific discovery.