جست‌وجوی استاد و پژوهشگر

Todd Mowryمشاهده پروفایل

استاد

• Computer Architecture
• Systems
• Databases
• +۳ مورد دیگر

Todd Mowry is a Professor in the Computer Science Department at Carnegie Mellon University, affiliated with the School of Computer Science. His research focuses on enhancing microprocessor-based system performance through parallelism exploitation, including single-chip multiprocessing and latency mitigation strategies. He leads initiatives like the STAMPede project, addressing challenges in compiler-driven parallelization and hardware-software co-design. His work spans computer architecture, systems, and databases, with a strong emphasis on compiler optimization, memory management, and scalable computing. Mowry has advised students including Sam Arch, Patrick Coppock, Hongyi Jin, Ruihang Lai, and Eliot Solomon. He teaches advanced courses such as 15745 (Fall 2025) and 15418 (Spring 2025), contributing to graduate-level education in computer systems. Recent research highlights include innovations in machine learning optimization (e.g., Relax framework), efficient LLM microservices, and architectural solutions for thread-safe metadata management. His publications address topics like UDF optimization, auto-batching in neural networks, and energy-minimal dataflow systems. Mowry's projects often involve collaboration across academic and industrial partners, driving advancements in both theoretical and applied computer systems. He has contributed to frameworks like CORA for tensor compilation and NVOverlay for non-volatile memory systems, emphasizing practical scalability and efficiency.

Daniel Sanchezمشاهده پروفایل

استاد

• Computer Architecture
• Systems & Networking
• Parallel Computing
• +۵ مورد دیگر

Dr. Daniel Sanchez is a Professor of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology (MIT), where he leads the Computation Structures Group within the Computer Science and Artificial Intelligence Laboratory (CSAIL). His research focuses on computer architecture, scalable systems, and memory hierarchies, with particular emphasis on multicore and many-core systems, quality-of-service guarantees, and runtime systems. Education: Ph.D. in Electrical Engineering, Stanford University (2012) M.S. in Electrical Engineering, Stanford University (2009) B.S. in Telecommunications Engineering, Technical University of Madrid (UPM) (2007) Research Interests: Dr. Sanchez’s work spans computer architecture innovations such as cache partitioning (KPart), software-defined caches (Jenga), and accelerators for sparse computing (Azul, Terminus). He designs systems that enhance performance, energy efficiency, and scalability in modern computing environments. His projects include the Swarm Architecture for ordered parallelism and architectures supporting fully homomorphic encryption. Articles Trends: Recent publications emphasize accelerators for sparse algorithms, cryptographic hardware (e.g., Fully Homomorphic Encryption), and high-performance computing. His work bridges hardware-software co-design to tackle challenges in irregular applications, memory hierarchies, and secure computing. Awards & Grants: No scientific awards explicitly listed, but his work has been recognized in top conferences (e.g., MICRO, ISCA). Advising & Teaching: He advises over 20 Ph.D. and master’s students, including current advisees Axel Feldmann and Hyun Ryong Lee. He teaches courses like 6.5900 Computer System Architecture and 6.191 Computation Structures at MIT. Labs & Teams: Leader of the Computation Structures Group at MIT CSAIL, collaborating with researchers like Joel Emer, Srini Devadas, and Armando Solar-Lezama. His team explores cutting-edge architectures and systems for next-generation computing.

Gerrit Jan Veltinkمشاهده پروفایل

استاد

• Concurrency Theory
• Distributed Systems
• Formal Verification
• +۴ مورد دیگر

Prof. Gerrit Jan Veltink is a Professor at the University of Applied Sciences Emden/Leer, affiliated with the Faculty of Technology, Electrical Engineering and Informatics and the Department of Media Informatics. He coordinates the Master's program in Industrial Informatics (since 2017) and co-initiated the Informatics program in collaboration with the Software Network Leer. He serves as scientific director of the Industry 4.0/IoT group within the Digital Hub Ostfriesland and is a founding member of the steering group for the IT-Achse (Ems-Achse). Education: Holds a doctoral degree (Dr.) in a relevant field. Teaching Roles: Teaches courses in Multimedia Programming, Concurrency Theory, Distributed Systems, Formal Process Verification, and Industrial Cyber-Physical Systems. Research Focus: Specializes in formal specification languages, parallel/distributed systems, Industry 4.0 integration, and cyber-physical systems education. His research emphasizes rigorous methodologies for system verification and industrial automation, particularly in domains requiring high reliability. Recent work includes pedagogical approaches to teaching cyber-physical systems and advancing tools for distributed system modeling. Notable contributions include the PSF formalism and toolkit, foundational to process specification and verification, with a legacy of over three decades of impactful academic output.

• Parallel Computing
• Multigrid Methods
• High-Performance Computing
• +۳ مورد دیگر

Christian Schmitt is a researcher affiliated with the University of Erlangen-Nuremberg, Germany. He holds a PhD in Computer Science from the same institution (2019). His work focuses on high-performance computing, multigrid methods, domain-specific languages, and parallel algorithms. Schmitt has contributed to the development of ExaSlang and ExaStencils frameworks for scalable solver generation and stencil-code engineering. His research emphasizes automating solver development and optimizing performance on multi-core and FPGA platforms. Key research interests include parallel computing paradigms, reconfigurable hardware design, and domain-specific language technologies for scientific computing. His publications span journals like Proc. IEEE and conferences such as ASAP and FCCM. Collaborators include Frank Hannig, Jürgen Teich, and Harald Köstler. Recent work explores SYCL-based code generation for multigrid methods and OpenCL acceleration of discontinuous Galerkin methods. He has also investigated Scala prototypes for multi-platform solver implementations and stencil-code optimization using SPL Conqueror.

Michael F. Spearمشاهده پروفایل

دانشیار

• Concurrency
• Programming Languages
• Computer Architecture
• +۵ مورد دیگر

Michael F. Spear is an Associate Professor and Master's Program Director in the Department of Computer Science & Engineering at Lehigh University. His research focuses on concurrency, programming languages, and computer architecture, with an emphasis on persistent memory, transactional memory, and concurrent data structures. He leads a lab supported by industry partnerships with Intel, Google, and Oracle, as well as grants from the National Science Foundation and the U.S. Army. Education: Ph.D. and M.S. in Computer Science, University of Rochester M.B.A., University of Alaska, Anchorage B.S. in Computer Science, U.S. Military Academy (West Point) Research Interests: Spear's work aims to simplify concurrent programming through innovative software and hardware designs. He develops open-source frameworks like libLOL/JetLag for mobile game development and contributes to C++ transactional memory standards. His lab explores cloud infrastructure optimization, memory management, and scalable algorithms. Collaborations & Awards: Active collaborations include Arizona State University, Penn State University, and industry leaders in tech. Notable awards include the University of Rochester's Outstanding Dissertation Award and leadership in NSF-funded research initiatives. Labs & Contributions: Spear directs a lab producing tools for persistent/transactional memory systems and advises on C++ technical specifications. His work bridges theoretical computer science with practical industry applications, emphasizing scalability and correctness in multi-core environments.

Jingnan Xieمشاهده پروفایل

دانشیار

• Formal Languages
• Automata Theory
• Computational Complexity
• +۵ مورد دیگر

Dr. Jingnan Xie is an Associate Professor of Computer Science at Millersville University, specializing in theoretical computer science. His research spans formal languages, automata theory, computational complexity, computable analysis, and quantum computing. Millersville University of Pennsylvania Ph.D. in Computer Science (2017) from University at Albany, SUNY His work explores computational parallels among automata theory, real function analysis, and quantum models, with a focus on bridging classical complexity theory and modern applications in AI/ML. Key contributions include foundational studies on multi-pattern languages, L-systems, and cellular automata. Recent research trends highlight collaborations at the intersection of vulnerability detection, large language models (LLMs), and quantum computing. Papers in Theoretical Computer Science , Acta Informatica , and Cluster Computing underscore his interdisciplinary impact. Awards include the 2025 PACISE Best Faculty Paper Award and the 2025–2026 PASSHE FPDC Grant for quantum computing research. He serves as a reviewer for journals like Natural Computing and Information and Computation . Dr. Xie mentors students like Emily Riley, who joined NC State’s Ph.D. program. He leads the TheoryX Lab, which investigates foundational questions in theoretical computer science, with funding from PASSHE and collaborations with Dr. Harry Hunt, Dr. Richard Stearns, and Dr. Ching-Sheng Lin.

• Computer Science Education
• Programming Education
• Computer Architecture
• +۴ مورد دیگر

Sohum Sohoni is a Professor in the School of Computing and Augmented Intelligence within the Ira A. Fulton Schools of Engineering at Arizona State University. His research spans computer science education, programming pedagogy, computer architecture, and image quality assessment with GPU acceleration. He has developed innovative educational approaches for computer architecture courses using the PLP instruction set architecture and has contributed significantly to understanding programming education through analysis of error messages and embedded questions. His research interests focus on Computer Science Education , particularly programming education techniques, computer architecture pedagogy, and engineering education methods. He has made substantial contributions to understanding how students learn programming concepts, develop effective debugging skills, and comprehend computer architecture principles. His work bridges theoretical computer science concepts with practical educational applications, emphasizing hands-on learning experiences and innovative assessment methods. His publication trends reveal a strong focus on computer science education research with particular emphasis on programming education (2015-2018), computer architecture education using PLP (2014-2017), and image quality assessment with GPU acceleration (2012-2018). His work consistently combines theoretical computer science concepts with practical educational applications, demonstrating his commitment to improving how computing concepts are taught and learned. His advising work includes mentoring students like Christopher Mar, Harsha B. M. Kadekar, Shaowen Lu, Thien D. Phan, and Vignesh Kannan, who have co-authored publications with him across various computing education topics. His research has been supported through various educational technology projects focused on online learning environments, software engineering education, and computer architecture instruction. He has been actively involved in developing virtualized learning environments for IoT education, creating innovative approaches for software engineering education, and designing effective methods for teaching computer architecture concepts. His work demonstrates a consistent commitment to improving computing education through evidence-based pedagogical approaches and technological innovation.

• High Performance Computing (HPC)
• Big Data
• Parallel Computing
• +۵ مورد دیگر

Cesar Alfredo Piñeiro Pomar is an Assistant Professor at the University of Santiago de Compostela, affiliated with the Department of Electronics and Computing within the Higher Technical School of Engineering. His research focuses on bridging High Performance Computing (HPC) and Big Data technologies, with a strong emphasis on parallel computing, heterogeneous programming frameworks, and bioinformatics applications. He holds a Doctorate from the University of Santiago de Compostela, awarded in 2022 for his thesis on 'New technologies to bridge the gap between High Performance Computing (HPC) and Big Data.' His academic contributions span the design of interoperability frameworks for HPC and Big Data, development of scalable Big Data toolkits (e.g., BigSeqKit for genomics data), and multilingual linguistic analysis tools like LinguaKit. He has also worked on distributed algorithms such as Fast Distributed kNN Graph Construction and optimized phylogeny estimation methods in Very Fast Tree. His publications reflect a focus on parallelization strategies, framework design, and cross-disciplinary applications of computing technologies. While no specific grants or awards are listed, his research demonstrates expertise in integrating computational paradigms to address large-scale data challenges in science and engineering.

Manuel Hermenegildoمشاهده پروفایل

استاد

• Constraint Programming
• Logic Programming
• Functional Programming
• +۷ مورد دیگر

Manuel Hermenegildo is a Full Professor at the Technical University of Madrid (UPM) and Director of the IMDEA Software Research Institute in Spain. He held the Prince of Asturias Endowed Chair at the University of New Mexico (2003-2008) and was previously a project leader at MCC (1986-1989) and Adjunct Associate Professor at the University of Texas at Austin (1987-1990). Education: M.S. and Ph.D. in Computer Engineering, University of Texas at Austin (1986) Engineer's Degree in Electrical and Telecommunications Engineering, Technical University of Madrid (1981) His research spans programming language design , abstract interpretation-based analysis , parallelizing compilers , and parallel/distributed processing . His work integrates theoretical advances with practical implementations like the Ciao system and PiLLoW library. Recent publications focus on parallelization , program verification , mobile code security , and distributed programming . Key methodologies include abstract interpretation , constraint logic programming , and compiler optimization . Scientific Awards: ACM Fellow Julio Rey Pastor Prize (highest Spanish national award in Mathematics and ICT) Aritmel Prize in Computer Science President of the Association for Logic Programming He has led numerous national and international projects, served as area editor for journals like Theory and Practice of Logic Programming , and participated in EU advisory committees (ISTAG, CREST). His work on the Abstraction Carrying Code (ACC) approach advances mobile code safety and trusted computing.

• Compilers
• Digital Imaging
• Hardware Architectures and Networking
• +۴ مورد دیگر

Hank Dietz is a Professor and James F. Hardymon Chair in Networking at the University of Kentucky, affiliated with the Department of Electrical and Computer Engineering within the Stanley and Karen Pigman College of Engineering. His research focuses on compilers, digital imaging, hardware architectures and networking, operating systems, and parallel processing. He holds a Ph.D., M.S., and B.S. in Computer Science from the Polytechnic University of New York. His career includes roles as Professor at the University of Kentucky (since 1999), Associate Professor at Purdue University (1992–2000), and visiting positions at Washington University and Stevens Institute of Technology. His work emphasizes parallel computing systems, compiler optimization, and high-performance architectures. Key publications explore GPU-based parallel processing, OpenMP hardware support, cluster design, floating-point accuracy, and network topology innovations. His research bridges theory and practical implementation in computational systems. Dr. Dietz has contributed to foundational advancements in parallel computing, compiler design, and hardware-software co-design, influencing both academic and industrial computing practices.

Aïna Linn Georgesمشاهده پروفایل

پژوهشگر

• Algorithms
• Theory & Logic
• Programming Languages & Verification
• +۳ مورد دیگر

Aïna Linn Georges is a researcher affiliated with the Max Planck Institute for Software Systems (MPI-SWS) in Saarbrücken, Germany. Her work focuses on formal methods, programming languages, and system security. She specializes in program verification, capability-based systems, and secure compilation. Her research addresses challenges such as concurrency, memory safety, and security in distributed and cyber-physical systems. Her research interests include separation logic, modular verification frameworks, and the mechanization of proofs for systems like WebAssembly and capability machines. She explores robust security properties under diverse attacker models and contributes to foundational aspects of capability-based architectures. Recent work highlights include advancements in non-frame-preserving updates for separation logic, formal verification of compartmentalized C programs, and secure compilation techniques. Her publications reflect a strong emphasis on practical formal methods for real-world systems, with applications in both theoretical and applied computer science.

Sven Karlssonمشاهده پروفایل

دانشیار

• Parallel Computing
• Computer Architecture
• Compilers
• +۴ مورد دیگر

Sven Karlsson is an Associate Professor in the Department of Applied Mathematics and Computer Science at the Technical University of Denmark (DTU). He is part of the Informatics and Mathematical Modelling faculty and affiliated with the Embedded Systems Engineering Center and the Center for Quantum Technologies. His expertise lies in parallel computer design, computer architecture, compilers, operating systems, and quantum computing infrastructure. Education: Civilingeniør from Lund University (LTH), Sweden (1997), and PhD in Teleinformatics from KTH Royal Institute of Technology, Sweden (2004). Postdoctoral research at FORTH-ICS, Greece, before joining DTU in 2007. Research interests include parallel computing systems, compiler optimization, quantum computing integration, and high-performance computing (HPC). His work spans application-specific hardware design, distributed quantum infrastructures, and autonomous HPC monitoring systems. Recent publications focus on quantum computing e-infrastructure (NordIQuEst), HPC-QC integration challenges, and optimizing parallel algorithms for multigrid solvers. He leads projects such as QUEX (Quantum Excellence Centre) and NordIQuEst, addressing quantum computing applications and cross-national collaboration. Teaching responsibilities include the course “Parallelle og tidstro systemer” and supervision of MSc/PhD projects. Current advisees include PhD candidates D. Guerrero Domínguez (Quantum Transport Applications), E.J. Fangel-Lloyd (Atmospheric Physics), and M. Gammelmark (Edge Computing for Renewable Energy).

Anirudh Mohan Kaushikمشاهده پروفایل

استادیار

• Cyber-Physical Systems
• High-Performance Computer Architecture
• Compiler Design
• +۱ مورد دیگر

Anirudh Mohan Kaushik is an Assistant Professor in the Electrical Engineering & Computer Science (EECS) department at York University's Lassonde School of Engineering. He holds a Ph.D. from the University of Waterloo (2021) and has prior industry experience at Intel, AMD, and IBM in research and design roles focused on software performance analysis, compiler design, and hardware micro-architecture. Research Interests : Cyber-physical systems, high-performance computer architecture, compiler design, and software performance analysis with a focus on timing predictability in multi-core systems. Key Publications : His work addresses predictable cache coherence (2021), shared cache optimization (2024), GPU wavefront splitting (2023), and hardware prefetching for graph analytics (2021). Industry Experience : Contributions to compiler design and hardware micro-architecture at Intel, AMD, and IBM prior to academia.

• High-performance computing
• Parallel computing
• Scientific computing
• +۷ مورد دیگر

David E. Bernholdt is a Researcher at Oak Ridge National Laboratory in Tennessee, USA. With a prolific publication record spanning from 1995 to 2025, he has established himself as a leading expert in high-performance computing and scientific software development. His work focuses on advancing computational methods and software infrastructure for scientific applications across multiple domains. Dr. Bernholdt's research interests center around high-performance computing, parallel computing, and scientific software engineering. He has made significant contributions to component-based software architecture, fault tolerance in extreme-scale applications, and sustainable software ecosystems for scientific computing. His work bridges the gap between theoretical computer science and practical scientific applications, with particular emphasis on making scientific software more reliable, efficient, and maintainable. His recent publications demonstrate a strong focus on research software engineering practices, sustainability, and productivity. He has been actively involved with the IDEAS Productivity Project and Better Scientific Software (BSSw.io) initiative, working to establish community best practices and improve the professional recognition of research software engineers in scientific computing. Dr. Bernholdt has collaborated extensively with researchers across multiple institutions and has contributed to significant projects in exascale computing, climate modeling, and quantum chemistry computations. His work on the Common Component Architecture and related frameworks has influenced software development practices in scientific computing.

• Parallel Computing
• High Performance Computing (HPC)
• Data Race Detection
• +۵ مورد دیگر

Joachim Jenke is a researcher at RWTH Aachen University, Germany, focusing on parallel computing and high performance computing (HPC). He has published extensively on topics related to data race detection, MPI correctness, OpenMP, and hybrid parallel programming approaches. His research includes developing tools and frameworks for runtime error detection in parallel applications, particularly for remote memory access (RMA) programs, CUDA-aware MPI applications, and hybrid MPI+OpenMP programs. He has contributed to projects like MUST, ThreadSanitizer, and DataRaceBench. Jenke's publications cover the full spectrum of parallel programming challenges, including benchmarking approaches for assessing MPI correctness tools, microbenchmark suites for evaluating race detection tools, and techniques for transparently adding metadata to MPI handles. He works closely with colleagues like Simon Schwitanski, Matthias S. Müller, Alexander Hück, and Christian H. Bischof, and his research has been presented at prestigious conferences such as SC, EuroMPI, and IWOMP.