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Piotr LuszczekView profile

Research Professor

• High-Performance Computing
• Numerical Linear Algebra
• Benchmarking
• +3 more

Piotr Luszczek is a Research Professor and Adjunct Associate Professor at the University of Tennessee, Knoxville's Tickle College of Engineering, affiliated with the Department of Computer Science and the Innovative Computing Laboratory. He holds a Ph.D. and M.S. from the University of Tennessee, Knoxville, and a B.S. from AGH University of Science and Technology in Kraków, Poland. Affiliations : Innovative Computing Laboratory (ICL), Tickle College of Engineering. Roles : Research and teaching in high-performance computing, numerical linear algebra, and performance optimization. Research Interests focus on benchmarking, numerical linear algebra for HPC, automated performance tuning for modern hardware, and stochastic models for performance analysis. His work emphasizes scalable algorithms, GPU acceleration, and efficient use of hybrid architectures. Grants and Collaborations include projects on batched linear algebra, sparse matrix operations, and energy-efficient AI frameworks. He contributes to software libraries like PLASMA and MAGMA, optimizing for exascale computing. Labs/Teams : Active in the Innovative Computing Laboratory (ICL), developing tools for HPC benchmarking (e.g., HPCG) and parallel linear algebra libraries. Engaged in international collaborations for exascale computing initiatives.

Jack MarquezView profile

Academic

• High Performance Computing (HPC)
• Cloud Computing
• Heterogeneous Storage Systems
• +3 more

Jack Marquez is a Research Assistant Professor at the University of Tennessee, Knoxville, affiliated with the College of Engineering and the Department of Electrical Engineering and Computer Science. He is a member of the Global Computing Laboratory directed by Michela Taufer. PhD in Software Engineering (2022), Universidad Autónoma de Occidente, Colombia BS in Software Engineering (2013), Universidad Autónoma de Occidente, Colombia His research focuses on High Performance Computing (HPC) and Cloud Computing, with a particular emphasis on heterogeneous storage systems, scientific workflows, and performance optimization techniques. He has developed scalable algorithms for motif counting, dynamic simulation management, and data fabric integration, bridging computational efficiency with data-intensive science. His recent publications highlight expertise in: Optimizing HPC performance in cloud environments In-situ analysis for molecular dynamics simulations Machine learning-driven resource allocation Checkpointing and fault tolerance mechanisms Community-driven scientific data infrastructure Previously, he served as a researcher and adjunct professor at Universidad Autónoma de Occidente (2013–2016), contributing to software engineering pedagogy and industry collaboration as a software developer. He is based in the Min H. Kao Building, Room 351, and can be reached at jmarque4@utk.edu .

Gerald Quentin Maguire Jr.View profile

Professor

• Data Communications
• Medical Image Processing
• Mobile Computing and Communication
• +3 more

Gerald Quentin Maguire Jr. is a Professor (emeritus) at KTH Royal Institute of Technology, Sweden, specializing in Computer Science and Communication Systems. He holds a Ph.D. in Computer Science from the University of Utah and a B.A. in Physics from Indiana University of Pennsylvania. His academic roles include Professor of Computer Communication at KTH since 1994, and prior positions at Columbia University and the U.S. National Science Foundation. He has contributed to fields like data communications, medical imaging, and mobile computing. Education: Ph.D. in Computer Science, University of Utah, 1983 M.S. in Computer Science, University of Utah, 1981 B.A. in Physics (magna cum laude), Indiana University of Pennsylvania, 1975 Research Interests: Focuses on network protocols, mobile computing, medical imaging integration, and high-performance computing. His work includes cognitive radio systems, GPU-centric networking, and CT/PET fusion for medical diagnostics. Awards: IEEE Fellow (2013) Teacher of the Year (2006/2007, KTH) Giovanni DiChiro Award (1997) Multiple honors in medical imaging and network research Advising & Grants: Supervised 8 doctoral students and over 75 master's students. Authored 5 books and numerous papers, with over 200 invited lectures globally. His research has been supported by grants from Swedish and international funding bodies. Labs & Teams: Formerly led the Computer Communication Systems Lab (CCSlab) at KTH and collaborated with Karolinska Institutet on medical imaging projects.

Elena KakoulliView profile

Lecturer

• Computer Architecture
• On-Chip Interconnection Networks
• Photonics
• +5 more

Dr. Elena Kakoulli is a Lecturer in Information Systems and Coordinator of the MSc in Information Systems and Digital Innovation at the University of Nicosia. She holds a Ph.D. in Computer Engineering from Cyprus University of Technology (2015), following a Master’s in Computer Science (2009) and B.Sc. (2007) from the University of Cyprus. Her research focuses on computer architecture, photonics-based interconnection networks, cybersecurity, and AI-driven educational technologies. Notable contributions include work on resilient NoC architectures, distributed storage systems (OctopusFS), and silicon photonics integration for high-performance computing. Dr. Kakoulli’s research interests span network-on-chip (NoC) design, IoT security, and adaptive learning frameworks. She has collaborated on projects such as distributed tiered storage for cluster computing with Dr. Herodotou. Recognitions include awards from the University of Cyprus and Marfin Laiki Bank Foundation for academic excellence during her postgraduate studies. She has also contributed to teaching roles as a Teaching Assistant at the University of Cyprus and lecturer at Ctl Eurocollege, covering courses like computer architecture, compilers, and operating systems. Her publications highlight advancements in cybersecurity models, AI-integrated education tools, and next-generation computing architectures. She actively participates in academic conferences, including the 21st European, Mediterranean, and Middle Eastern Conference on Information Systems (EMCIS 2024), and has served as a Technical Program Committee member.

David CuttingView profile

Associate Professor

• Software Engineering
• Legacy Systems
• Computing Education
• +3 more

Dr. David Cutting is a Reader (Education) / Associate Professor at Queen's University Belfast's School of Electronics, Electrical Engineering and Computer Science. He holds a PhD from the University of East Anglia and is a National Teaching Fellow (2024), Eaton Fellow, and Senior Fellow of the Higher Education Academy. His research focuses on software engineering (legacy systems, mining repositories) and computing education (project-based learning, VR/AR integration). Teaching roles include modules on Cloud Computing, Parallel/Distributed Systems, and Systems Administration. Key achievements include developing tools for authentic educational experiences, early academic success prediction systems, and bridging industry-academia gaps. Awards span teaching excellence, innovation, and support, with external roles as an examiner and governor of South West College since 2023.

Giles RegerView profile

Senior Lecturer

• Automated Theorem Proving
• Runtime Verification
• Formal Methods
• +3 more

Giles Reger is a Senior Lecturer in the School of Computer Science at the University of Manchester, where he leads research in the Formal Methods Group. His academic background includes a BA in Computer Science from the University of Cambridge (2009), an MSc in Advanced Computer Science from the University of Manchester (2010, Highest Achiever Award), and a PhD from Manchester (2014) on Automata-based monitoring and mining of execution traces . Research interests focus on: Theorem Proving : Core developer of the Vampire first-order ATP system, working on performance extensions and collaborative proving techniques Runtime Verification : Creator of the MarQ monitoring tool and organizer of the International Runtime Verification Competition Formal Methods : Applications in program verification, specification mining, and temporal logic Publications emphasize automated reasoning, verification tools, and temporal specification languages, with recent work exploring neural-guided theorem proving and higher-order unification. His group consistently publishes at top venues like CADE, TACAS, and RV. Awards include: Multiple division wins in SMTCOMP/CASC theorem proving competitions (2016-2020) FLoC Olympic Games medals for Vampire contributions (2018) Advises PhD students including Michael Rawson (neural-guided proving) and Joshua Dawes (runtime verification). Leads the £1.3M EPSRC-funded SCorCH project (Secure Code for Capability Hardware) with Oxford/ARM/AWS. Coordinates the COST Action on Runtime Verification Beyond Monitoring.

José Luís de Azevedo Quintino RogadoView profile

Associate Professor

• Digital Identity
• Identity Management
• Blockchain
• +9 more

José Luís de Azevedo Quintino Rogado is an Associate Professor at the School of Communication, Arts, Architecture and Information Technologies (ECAATI/ULHT) of Universidade Lusófona in Lisbon, Portugal. He serves as Director of the Department of Computer Engineering and Information Systems and teaches in areas including Operating Systems, Computer Networks, Identity Management, and Parallel Computing. His educational background includes a degree in Electronic Engineering from Instituto Superior Técnico (Lisbon), a Doctorat d'Université in Information Systems from Université Pierre et Marie Curie (Paris VI), and a Ph.D. in Computer Engineering from Universidade Técnica de Lisboa. He has held research positions at INRIA (France) and the Open Software Research Institute, focusing on operating systems and system performance. His research lies at the intersection of computer science and social impact, particularly in Digital Identity , Identity Management , Blockchain , Interoperability , and Digital Rights . A significant portion of his work explores how children’s rights can be protected in digital environments, combining technical solutions with ethical and societal considerations. His research integrates user-centric computing with robust system architectures. The analysis of his recent publications reveals a strong focus on decentralized digital identity systems, privacy-preserving technologies, and the development of reference architectures for complex software systems. His work increasingly bridges technical innovation with human rights, especially in the context of youth digital presence and security awareness through game-based learning. Actively involved in research on digital identity and blockchain applications Focus on children's rights and digital environments Published in top-tier computer science conferences such as SEMANTiCS and IEEE WoWMoM Contributed to foundational work in ground segment software architecture José Rogado has supervised at least 13 research works or students, indicating a strong commitment to academic mentorship. While specific grant details are not listed, his sustained research output and leadership in departmental and technical domains suggest active involvement in funded projects and collaborative research. He is affiliated with COPELABS (Cognitive and People-centric Computing), a research lab focusing on human-centered technological innovation.

Tobias WrigstadView profile

Professor

• Type Systems
• Reference Capabilities
• Programming Languages
• +2 more

Tobias Wrigstad is a faculty member at Uppsala University, Sweden, with research interests spanning type systems, reference capabilities, programming language design, scripting languages, and concurrent/parallel programming. His work focuses on memory management, concurrency safety, and language extensions for performance optimization. Education: Not explicitly mentioned in provided data Research Interests: Designing type systems to enforce concurrency safety and memory correctness Reference capabilities for manual and automatic memory management Actor model programming and garbage collection co-design Cache locality optimization without program restructuring Formal verification of language designs using Dafny Recent Publications (2025-2015): Explore concurrency safety through region ownership Develop parallel array programming models in Kappa Investigate energy-efficient garbage collection Design capability-based dynamic languages for data race freedom Create formal models for heap invariants and incorrectness Optimize memory allocation via load barriers Conference Involvement: 2025: IWACO Committee Member, OOPSLA Associate Chair 2024: Program Co-Chair for IWACO, Author in VIMPL, MPLR, ISMM 2023: SPLASH Steering Committee, ECOOP PC Member 2022-2015: Active in PLDI, ECOOP, ICFP, and related workshops

• Cloud Computing
• Distributed Systems
• High-Performance Computing
• +5 more

Raja Appuswamy is an Assistant Professor in the Department of Data Science at EURECOM, focusing on data management on modern hardware and molecular information storage. His research integrates cutting-edge storage technologies with bioinformatics, particularly in DNA-based data storage. He teaches courses in cloud computing, distributed systems, and databases. His work spans Optimizing storage hierarchies with DNA archival systems Hardware-conscious algorithms for GPUs and heterogeneous architectures Error correction in molecular storage Long-term database preservation strategies Key research interests include Cross-architecture data joins (e.g., OneJoin, XJoin) Cold storage innovation with CMOSS and OligoArchive Integration of bio-inspired storage with traditional computing and explores interdisciplinary challenges at the intersection of computer science and molecular biology. Publications emphasize scalable solutions for DNA storage density, error tolerance, and archival systems. Awards highlight contributions to DNA-based image encoding, storage reliability, and page cache checksums. Current projects focus on enzymatic DNA ligations for storage density improvement, motif-based error correction, and hardware acceleration for knowledge graphs. His work targets both theoretical advancements and practical implementations in storage systems.

Thrasyvoulos SpyropoulosView profile

Adjunct Professor

• Distributed Storage/Caching
• Recommendation Systems
• 5G/5G+ Networks
• +5 more

Thrasyvoulos Spyropoulos is an Adjunct Professor at EURECOM, focusing on cutting-edge research in telecommunications and network systems. His work spans distributed storage, recommendation systems, 5G/6G networks, and network slicing. He has made significant contributions to optimizing network performance through techniques like stochastic modeling, applied machine learning, and decentralized resource allocation. His research interests include: Distributed Storage/Caching, Recommendation Systems, 5G/5G+ Networks, Network Slicing, Social/Complex Network Analysis, Network Optimization, and Stochastic Modeling. These areas reflect his expertise in balancing technical innovation with practical network challenges. Key achievements include Best Paper Awards at IEEE WoWMoM 2012 and IEEE Sensor Networks 2008, as well as a Best-in-Session Presentation at INFOCOM 2016. His recent work emphasizes AI-driven solutions for network orchestration, edge computing, and QoS-aware recommendation systems. Publications highlight advancements in federated learning, DNN-based resource scaling, and combinatorial optimization for slice orchestration. His work on D2D relaying and spatial unfairness addresses critical mobile network challenges. Collaboration through platforms like Google Scholar and ResearchGate underscores his active role in the global academic community.

John TaylorView profile

Professor

• Climate Modeling
• Machine Learning
• Image Analysis
• +3 more

Prof. John Taylor is a prominent academic at The Australian National University (ANU), affiliated with the School of Computing. His research focuses on interdisciplinary areas spanning climate science, machine learning, and high-performance computing. He has made significant contributions to atmospheric modeling, GPU-accelerated algorithms, and data-driven environmental predictions. Research Interests Climate Modeling and Regional Climate Simulations Machine Learning Applications in Meteorology Deep Learning for Image Analysis and Semantic Segmentation High-Performance Computing and GPU Optimization Statistical Downscaling of Climate Variables Cloud-Based Scientific Workflows Collaborations Prof. Taylor collaborates extensively with institutions globally, including work on projects like the Earth Virtualization Engines (EVE) and the PAUNet precipitation prediction framework. His research often bridges computational methods with real-world environmental challenges, such as heat extremes and hydrological modeling. Key Achievements Over 5000 citations and an h-index of 50 Developed innovative frameworks for climate data assimilation and GPU-accelerated algorithms Leader in applying machine learning to environmental monitoring and prediction Labs/Teams He leads research groups at ANU focused on computational climate science and advanced imaging techniques. His team has developed platforms like the Cloud-Based Image Analysis Toolbox and the DCM software for 3D materials modeling.

John OusterhoutView profile

Professor

• Distributed Systems
• Operating Systems
• Storage Systems
• +5 more

John Ousterhout is the Leonard Bosack and Sandy K. Lerner Professor of Engineering and Professor of Computer Science at Stanford University. He also holds a courtesy position in Electrical Engineering. His research focuses on infrastructure for software systems, including distributed systems, operating systems, storage systems, development frameworks, and programming languages. He is renowned for creating the Tcl scripting language and pioneering work in distributed operating systems and file systems. Education: Ousterhout earned a BS in Physics from Yale University (1975) and a PhD in Computer Science from Carnegie Mellon University (1980). He spent 14 years at UC Berkeley before moving to industry, founding Scriptics and Electric Cloud. He returned to academia at Stanford in 2010. Research Interests: Current projects emphasize granular computing—optimizing datacenter task execution at microsecond scales. This includes innovations in thread management, network communication, and logging systems. His past work includes RAMCloud (a low-latency storage system) and foundational contributions to distributed systems and file systems like Sawmill and Zebra. Scientific Awards: He is a member of the National Academy of Engineering and has received prestigious honors such as the ACM Software System Award, ACM Grace Murray Hopper Award, NSF Presidential Young Investigator Award, and U.C. Berkeley’s Distinguished Teaching Award. Industry Impact: As a serial entrepreneur, he co-founded Scriptics (Tcl/Tk) and Electric Cloud. His work on Tcl revolutionized scripting in software development and web frameworks. He has also contributed to AJAX-driven web components and program build architectures.

Raluca Ada PopaView profile

Associate Professor

• Computer Security
• Systems Security
• Applied Cryptography
• +4 more

Raluca Ada Popa is an associate professor in the Department of Electrical Engineering and Computer Science at UC Berkeley, holding the Robert E. and Beverly A. Brooks Endowed Chair. She leads the Frontier Security team at Google DeepMind and co-founded the RISELab, SkyLab, and DARE diversity program. Her research focuses on systems security, cryptographic computing, and privacy-preserving machine learning. She received her PhD from MIT in 2014, alongside BS and MS degrees in Computer Science and Mathematics from MIT. Education: PhD in Computer Science, MIT (2014) MS in Computer Science, MIT (2010) BS in Computer Science and Mathematics, MIT (2009) Research Interests: Popa designs systems that compute securely on encrypted data, enabling confidentiality in cloud computing, AI, and collaborative analytics. Her work bridges cryptography and systems, with contributions to secure multi-party computation, hardware enclaves, and decentralized trust mechanisms. Key innovations include CryptDB, Opaque, and Helen, which have influenced industry standards like Microsoft SQL's Always Encrypted service. Publications & Awards: Over 50+ peer-reviewed papers, including influential work at top venues like USENIX Security, SOSP, and IEEE S&P. Notable awards include the ACM Grace Murray Hopper Award (2021), Sloan Research Fellowship (2018), and MIT Technology Review's TR35 (2019). Her work has been recognized for advancing secure computing and privacy-preserving technologies. Advising & Grants: Advisor to over 20 PhD students and postdocs, many of whom hold faculty positions or lead industry research. Recipient of major grants including NSF CAREER Award (2020), Bakar Fellowship (2019), and a $10M NSF Expedition for RISELab. Co-founded Opaque Systems (2021) and PreVeil (2015), with significant industry impact. Labs & Teams: Co-director of RISELab (Real-time, Intelligent, Secure Systems) and SkyLab (secure cloud and edge computing). Founded DARE to promote diversity in EECS research, connecting undergraduates with faculty mentors.

Sophia ShaoView profile

Associate Professor

• Computer Architecture
• Integrated Circuits
• Domain-Specific Accelerators
• +5 more

Sophia Shao is an Associate Professor in the Department of Electrical Engineering and Computer Sciences (EECS) at the University of California, Berkeley. She was promoted to Associate Professor with tenure in July 2024 after serving as an Assistant Professor from August 2019 to June 2024. Previously, she worked as a Senior Research Scientist at NVIDIA from October 2018 to July 2019. Her academic journey began with a Bachelor of Electrical Engineering from Zhejiang University, China (2005-2009), followed by a Master of Science (2009-2014) and Ph.D. (2009-2016) in Computer Science from Harvard University. Shao's research focuses on computer architecture, with special emphasis on domain-specific accelerators, heterogeneous architecture, and agile VLSI design methodology. Her work bridges the gap between hardware and software through systematic approaches to accelerator design and evaluation. She leads research efforts in the Agile Design of Efficient Processing Technologies (ADEPT), Berkeley Emerging Technologies Research (BETR), Berkeley Wireless Research Center (BWRC), and SpeciaLIzed Computing Ecosystems (SLICE) centers. Her recent publications reveal a strong trend toward holistic hardware-software co-design for machine learning acceleration, with particular focus on efficient neural network accelerators, multi-tenant execution environments, and automated design methodologies. Her research spans from low-level circuit design to system-level architecture, demonstrating expertise across the entire computing stack. Notably, her work on Gemmini, Stellar, and Virgo represents significant contributions to the field of domain-specific accelerator design and integration. Sloan Research Fellowship (2024) Anita Borg Early Career Award (2024) NSF CAREER Award (2023) Google Research Scholar Award (2023) IEEE TCCA Young Computer Architect Award (2022) Intel Rising Star Faculty Award (2022) ISCA Distinguished Artifact Award (2023, 2024) Best Paper Award at DAC 2021 Professor Shao actively mentors a large group of graduate and undergraduate students, with several former students now at leading technology companies including NVIDIA, Microsoft, and Apple. Her research has been supported by multiple grants from NSF, Google, Intel, and other organizations. She leads several open-source research projects including Gemmini, Stellar, Chipyard, and RoSÉ, which have gained significant traction in both academic and industrial research communities. Her lab, part of the SLICE ecosystem, focuses on creating next-generation computing platforms through vertically integrated hardware-software approaches.

• Machine Learning
• Artificial Intelligence
• Speech Processing
• +6 more

Saeed Amizadeh is a prominent researcher specializing in artificial intelligence and machine learning, currently affiliated with Microsoft's research division. His work spans multiple domains of AI including speech processing, natural language understanding, computer vision, and time series analysis, with a particular focus on developing novel frameworks that bridge symbolic reasoning with neural approaches. Over the past decade, he has established himself as a significant contributor to the field through publications in top-tier conferences including ICASSP, ICLR, AAAI, KDD, and IJCAI. Dr. Amizadeh's research interests primarily center around advancing the theoretical foundations and practical applications of machine learning systems. His work on neuro-symbolic visual reasoning has contributed to understanding how to effectively disentangle visual perception from logical reasoning in AI systems. He has made significant contributions to differentiable programming, particularly in making classical machine learning pipelines fully differentiable, which enables end-to-end optimization of complex ML workflows. His research on speech enhancement using GANs represents cutting-edge work in audio processing, while his time series anomaly detection frameworks have practical applications in numerous industry settings. Analysis of his publication trends reveals a consistent trajectory from theoretical machine learning foundations toward increasingly applied research with practical industrial relevance. His early work (2010-2015) focused on fundamental algorithms and probabilistic modeling approaches, while his more recent publications (2019-2025) demonstrate a shift toward practical AI systems with direct applications in speech processing, audio separation, and enterprise machine learning. A notable theme throughout his career is the development of frameworks that enable more efficient, scalable, and interpretable AI systems. As a key contributor to Microsoft's ML.NET framework, Dr. Amizadeh has played an important role in developing tools that make machine learning more accessible to enterprise developers. His collaborative work spans academia and industry, with notable partnerships with researchers from various institutions as well as within Microsoft Research.