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Matthew HicksView profile

Associate Professor

• Software Security
• Hardware Security
• Embedded System Security
• +5 more

Matthew Hicks is an Associate Professor in the Department of Computer Science at Virginia Tech, serving as the CACI Faculty Fellow in Cyber Security. His research focuses on software, hardware, and embedded system security, particularly in energy harvesting and IoT systems. He holds a Ph.D. from the University of Illinois Urbana-Champaign (2013), an M.S. from the same institution (2008), and a B.S. from the University of Central Florida (2006). His research interests emphasize hardware security mechanisms, defensive routing against malicious designs, and resilient computing in energy-constrained environments. Notable contributions include work on FPGA fingerprinting, compiler-assisted fuzzing, and intermittent computing paradigms. Recent publications explore countermeasures against hardware trojans, energy-efficient buffering, and secure checkpointing in batteryless systems. Dr. Hicks has no listed academic awards but maintains an active publication record in top-tier conferences. His work bridges theoretical computer science with practical hardware implementations, addressing vulnerabilities at both software and physical layers. While no student advisees or grants are explicitly mentioned, his research portfolio demonstrates sustained engagement with cutting-edge cybersecurity challenges.

Rudolf EigenmannView profile

Professor

• Optimizing Compilers
• High-Performance Computing
• Parallel Programming Methodologies
• +3 more

Rudolf Eigenmann is a Distinguished Professor at the University of Delaware, where he leads research in optimizing compilers, parallel programming methodologies, and high-performance computing. Previously, he served as a Professor at Purdue University and Program Director at the National Science Foundation’s Office of Advanced Cyberinfrastructure (2013–2017). He holds a Ph.D. in Electrical Engineering/Computer Science from ETH Zurich, Switzerland. Research Focus: His work centers on compiler optimization, parallelization techniques, and cyberinfrastructure design. Notable projects include the iCetus parallel programming assistant, the Portal for High-Precision Atomic Data and Computation, and advancements in automatic and interactive parallelization using the Cetus compiler infrastructure. Awards & Recognition: IEEE Fellow (202?) NSF CAREER Award (1997) Best Student Paper Award (ACM International Conference on Supercomputing, 2010) IEEE Distinguished Visitor (2003–2005) Professional Contributions: Dr. Eigenmann has advised national initiatives like the Xpert Network (exchanging best practices for computational research) and served on advisory boards for XSEDE, MolSSI, and IACS. His recent publications explore AI-driven code optimization, compiler infrastructure, and high-precision computational tools. Labs & Projects: Key projects include the Portal for Atomic Data (supporting precision computation in physics) and the iCetus tool, which semi-automates parallel programming tasks. His work bridges theoretical compiler research with practical high-performance applications.

• Formal Verification
• Parallel Programming
• Programming Languages
• +3 more

Frédéric LOULERGUE is a Full Professor at the University of Orléans, affiliated with the LIFO (Laboratoire d'Informatique Fondamentale d'Orléans) laboratory and part of the LMV research team (Languages, Models, and Verification). His work focuses on formal methods for programming languages, parallel computing, and cybersecurity. He leads research in verified parallel frameworks, distributed systems reconfiguration, and TPM software stack validation. Contact him at frederic.loulergue@univ-orleans.fr or visit his homepage at https://www.univ-orleans.fr/lifo/Members/loulergu/ . Research interests include formal verification of parallel algorithms, deductive program analysis with tools like Frama-C and Coq, and the development of formally verified distributed systems. Recent work emphasizes combining deductive verification with shape analysis, runtime monitoring for security properties, and formalizing decentralized reconfiguration languages in Maude. His publications span topics from verified parallel functional programming (SyDPaCC framework) to cybersecurity in Trusted Platform Modules (TPM). He collaborates on frameworks like WhyBSML for scalable parallel computing and Concerto-D for distributed reconfiguration. No scientific awards are listed, but his contributions are highlighted through extensive peer-reviewed publications and conference activities. Labs/Teams: Member of LIFO's LMV team, contributing to the formal methods research group. Involved in cross-disciplinary projects on cloud computing security and high-performance parallel programming.

• Computer Security
• Operating Systems
• Hardware Security
• +3 more

C Giuffrida is an Associate Professor at the Faculty of Science, Vrije Universiteit Amsterdam, with affiliations to the Network Institute and the Systems and Network Security group. His research focuses on computer systems security, hardware vulnerabilities, and software reliability. Giuffrida holds a PhD in Computer Systems from Vrije Universiteit Amsterdam (2014). His academic contributions span multiple areas including transient execution attacks, fuzzing techniques, and hardware-software co-design for security. Research Interests: Hardware Security: Investigating vulnerabilities like Spectre, Rowhammer, and speculative execution risks. Software Security: Focusing on memory safety, compiler optimizations, and exploit mitigation strategies. Systems Research: Developing tools like BinRec for binary analysis and VPS for C++ vulnerability protection. His work has been recognized with awards such as the Distinguished Paper Award in 2021. Giuffrida supervises advanced courses in operating systems and hardware security, and has guided 16 PhD theses to completion.

• Bioinformatics
• Theoretical Computer Science
• Computational Biology
• +3 more

Atze van der Ploeg is an Assistant Professor at the Vrije Universiteit Amsterdam's Faculty of Science, within the Theoretical Computer Science department. He is also affiliated with the Network Institute. His research focuses on interdisciplinary topics at the intersection of computer science and computational biology, with expertise in algorithm design, bioinformatics tools, and programming languages. He holds an MSc and a PhD, though specific academic details about his degrees are not provided in the text. His teaching responsibilities include courses such as Introduction to Programming (PYTHON), Object-Oriented and Functional Programming, and Systems Programming Project. These courses reflect his commitment to foundational programming skills and advanced software development practices. Key research interests include developing tools for bioinformatics (e.g., the PRALINE alignment toolkit), functional reactive programming, and visualization systems. His work emphasizes practical, principled approaches to solving complex computational problems. Though no specific grants or awards are listed, his publications span topics like type-safe dynamic typing, modular language implementation, and algorithm optimization, showcasing contributions to both theoretical and applied computer science.

Antony HoskingView profile

Professor

• Programming Languages
• Software Systems
• Software Assurance
• +7 more

Antony Hosking is a Professor and School Director of the School of Computing at the Australian National University (ANU). He holds a BSc in Mathematical Sciences from the University of Adelaide (1985), MSc with First Class Honours in Computer Science from the University of Waikato (1987), and a PhD in Computer Science from the University of Massachusetts Amherst (1995). Prior to ANU, he served for over 20 years at Purdue University as Assistant Professor and later tenured Associate Professor of Computer Science. He is also an Honorary Professor at the University of Massachusetts Amherst. His research focuses on programming languages, software systems, and software assurance, with particular expertise in garbage collection, memory management, compiler optimizations, and architectural support for programming languages. He co-authored the seminal reference text *The Garbage Collection Handbook*, now in its second edition (2023), and has contributed extensively to conferences like ACM SIGPLAN. He has held leadership roles in professional organizations, including the Executive Committee of ACM SIGPLAN and the International Symposium on Memory Management. Hosking’s accolades include being a Distinguished Scientist of the Association for Computing Machinery (ACM), an elected member of Association Internationale pour les Technologies Objets (AITO), and a Professional Member of IEEE. His consulting work involves intellectual property litigation in US courts and the US Patent and Trademark Office. He has advised on high-performance garbage collectors, concurrency, and real-time systems, with a focus on energy-aware and persistent storage solutions. His recent work addresses foundational assurance in systems software, aiming to build trustworthy systems. He collaborates on projects like the Single-Chip Cloud Computer and explores portable performance for parallel managed languages across multi-core architectures.

Jonathan CookView profile

Professor

• Software Process
• Reliable Component-Based Systems
• Software Engineering Environments
• +5 more

Jonathan Cook is a Professor in the Department of Computer Science at New Mexico State University (NMSU). He specializes in software process improvement, reliable component-based systems, and high-performance computing (HPC) performance analysis. His work includes developing tools and methodologies for monitoring HPC applications, optimizing memory systems, and validating proxy applications against real-world software. Education: Cook holds a Ph.D. in Computer Science from the University of Colorado at Boulder (1996), an M.S. in Computer Engineering from Case Western Reserve University (1991), and a B.S. in Computer Engineering from the same institution (1988). Research Interests: His expertise spans HPC performance analysis, runtime monitoring systems, compiler optimization, and software engineering environments. He focuses on improving the reliability and efficiency of large software systems through empirical methods and tool development. Recent Work Trends: His articles emphasize HPC monitoring (e.g., heartbeat data analysis, proxy application validation), novel memory architectures (scratchpad memory, 3D PIM NoCs), and compiler-driven performance optimization. His work bridges theoretical models with practical deployment in production environments. Grants and Advising: While specific grants or student advisees are not listed, his research actively involves experimental validation through collaborative projects with institutions like the Exascale Computing Project (ECP). Labs/Teams: His contributions align with NMSU’s broader efforts in HPC and software engineering, though no specific lab names are mentioned in the provided text.

• High-performance computing
• Decimal arithmetic
• Parallel programming
• +4 more

Alvaro Vazquez Alvarez is an Assistant Professor at the Higher Technical School of Engineering, University of Santiago de Compostela. He holds a PhD in Computer Engineering (2009) from the same institution, focusing on High-performance decimal floating point units under the supervision of Dr. Elisardo Antelo Suárez. His research interests span high-performance computing, decimal arithmetic hardware design, parallel programming models, and LiDAR data processing. His work emphasizes FPGA implementation of arithmetic units, numerical algorithms optimization, and compiler/runtime systems for parallel environments. He leads the CograDe Research Group (Computer Graphics and Data Engineering), exploring advanced topics in parallel computing and data engineering applications. Key contributions include universal MPI binding frameworks for new languages and efficient LiDAR point cloud processing algorithms. Notable technical expertise includes: digit-by-digit algorithms, redundant number systems, CORDIC-based computations, and multi-operand decimal arithmetic implementations. His publications bridge theoretical numerical methods with practical hardware/software co-design solutions. Current research focuses on extending parallel programming interfaces, improving decimal arithmetic precision in modern architectures, and applying advanced geometric processing techniques to 3D data challenges.

• 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.

• High Performance Computing
• Parallel Programming
• OpenMP
• +2 more

Matthias S. Müller is affiliated with RWTH Aachen University's IT Center, with additional associations to TU Dresden's Center for Information Services and High Performance Computing and the University of Stuttgart's High Performance Computing Center. His research focuses on parallel computing paradigms, OpenMP optimizations, and energy-efficient high-performance computing. Recent publications demonstrate specialization in parallel pattern compilers, OpenMP runtime optimizations, and energy-aware computing benchmarks. His team develops tools for performance analysis and optimization in heterogeneous computing environments, with applications in computer vision and scientific computing.

• High-Performance Computing
• Energy Efficiency
• Parallel Computing
• +3 more

Ananta Tiwari is a researcher specializing in High-Performance Computing (HPC), energy efficiency, and parallel system optimization. His work focuses on optimizing HPC applications, workload management, and resource allocation strategies to enhance both performance and energy efficiency. Tiwari has collaborated extensively with institutions like the University of Maryland, UC San Diego, and Lawrence Livermore National Laboratory through his research activities. Education: PhD in Computer Science, University of Maryland, College Park (2011) Research Interests: Energy-efficient HPC systems Parallel application auto-tuning frameworks Workload characterization and extrapolation Node-sharing and resource pricing models ARM architecture optimization for HPC Key Contributions: Tiwari's research spans energy optimization techniques for large-scale MPI applications, colocation strategies for HPC workloads, and binary instrumentation tools for program analysis. His work on auto-tuning frameworks and multi-objective modeling with machine learning addresses critical challenges in balancing performance, power consumption, and scalability in modern HPC environments.

Todd AustinView profile

Professor

• Computer Architecture
• Hardware Security
• Secure System Design
• +4 more

Todd Austin is the S. Jack Hu Collegiate Professor of Electrical Engineering and Computer Science at the University of Michigan's College of Engineering. His research focuses on secure computer architecture and hardware-software co-design for security-critical systems. His primary research interests include computer architecture , hardware security , secure system design , and side-channel protection . Austin's work emphasizes practical solutions for real-world security challenges through hardware-software co-design and formal verification techniques. Recent publications (2022-2025) demonstrate a strong focus on data-oblivious execution , moving target defenses , and hardware-based security primitives . Key themes include eliminating side-channel leakage through program transformations, sequestered encryption techniques, and architectural support for vulnerability-tolerant systems. Austin maintains active research engagement through his Austin-Lab and open-source contributions, including the widely-forked bringup-bench repository for CPU and system validation. Contact: austin@umich.edu | Office: 4637 BBB, 2260 Hayward Avenue, Ann Arbor, MI 48109-2121 | Phone: 734-936-0370

Christos-Efthymios KotselidisView profile

Associate Professor

• Computer Architecture
• Parallel and Distributed Computing
• High-Performance Computing
• +4 more

Christos-Efthymios Kotselidis is an Associate Professor in the Department of Computer Science at the University of Manchester. His work focuses on runtime systems, heterogeneous computing, and high-performance computing. He leads research in optimizing Java programs using frameworks like TornadoVM and explores GPU acceleration for cryptography (FHE). His contributions include advancements in vectorization for RISC-V architectures and memory analysis of Java benchmarks. Education: PhD in Computer Science (2011) from the University of Manchester, supervised by Prof. Steve Furber and Dr. Chris Kirkham, with a thesis on Distributed Software Transactional Memory. Research Interests: Runtime environments, parallel programming models, compiler optimization, and hardware-software co-design. His work aligns with UN SDG 9 (Industry, Innovation, and Infrastructure) through digital futures research. Notable Achievements: Recipient of the Best Paper Award (2017) Principal Investigator in the Centre for Digital Trust and Society (2021–present) Over 49 peer-reviewed publications, including books and conference contributions on topics like FHE acceleration and runtime systems Lab/Team Affiliations: Member of the Advanced Processor Technology group and collaborates on the Digital Futures research beacon at the University of Manchester.

• High-Performance Computing
• Performance Modeling
• Parallel Computing
• +3 more

Alexandru Calotoiu is a Researcher in the Department of Computer Science at ETH Zürich, affiliated with the Professorship for Scalable Parallel Computing. His work focuses on performance modeling, high-performance computing (HPC), serverless systems, and cloud computing. He leads research in empirical performance modeling for complex applications, optimization of parallel algorithms, and scalable cloud architectures. Key research areas include noise-resilient performance models, serverless computing frameworks, and compositional parallel programming. He has contributed to benchmarking tools like SeBS and developed techniques for loop scheduling, static analysis, and resource disaggregation in HPC environments. His publications from 2023–2025 emphasize serverless systems (e.g., FaaSKeeper, Cppless), performance embeddings for optimization, and specialized supercomputing for climate science. These studies address scalability, reproducibility, and cross-platform performance portability in data-centric workloads. No scientific awards are explicitly listed, but his work has been presented at leading conferences such as ISCA and IEEE/ACM events. He collaborates on projects like rFaaS (RDMA-enabled serverless platforms) and Process-as-a-Service frameworks. His research bridges theoretical models with practical implementations in distributed systems and cloud infrastructure.

• Programming Languages
• Type Theory
• Formal Methods
• +3 more

James McKinna is an Associate Professor in the School of Mathematical & Computer Sciences at Heriot-Watt University. His research focuses on foundational aspects of programming languages, type theory, and formal methods. He has contributed extensively to areas such as syntax with bindings, type systems, and formal verification. His work often explores the interplay between theoretical computer science and practical programming language implementations. Key research interests include: Type Theory & Dependent Types Syntax & Binding Mechanisms Formal Semantics of Programming Languages Automated Reasoning & Proof Systems Functional Programming & Compiler Design Recent research trends show a focus on advancing foundational techniques for syntax manipulation, type-safe programming constructs, and bidirectional transformations. His publications span topics like blame tracking in hybrid types, structural subtyping, and coalgebraic approaches to bidirectional systems. While not explicitly listed, his work demonstrates engagement with grant-funded research through collaborative projects and international publications. No specific grants or awards are mentioned in the provided texts.