جست‌وجوی استاد و پژوهشگر

• Secure Decentralized Systems
• Blockchain Technology
• Systems Security
• +۳ مورد دیگر

Prof. Bryan Ford leads the Decentralized/Distributed Systems (DEDIS) lab at EPFL. He focuses on secure decentralized systems, including blockchain technology, privacy, and systems security. He earned his Ph.D. from MIT and held faculty positions at Yale University and EPFL. His work spans distributed consensus protocols, peer-to-peer networking, and privacy-preserving systems. Key projects include QuePaxa (timeout-free consensus), UIA (global connectivity for mobile devices), and MedCo (secure healthcare data sharing). He advises numerous PhD students and contributes to open-source projects like Bitcoin collective signing and privacy networks like Riffle. Education: Ph.D., MIT; Postdoctoral work at Yale Research interests include blockchain scalability, consensus algorithms, and cryptographic privacy. His lab develops systems like TRIP for coercion-resistant voting and F3B to mitigate blockchain front-running. His work on NAT traversal and peer-to-peer protocols (e.g., STUN/ICE) remains foundational in network architecture. He emphasizes practical, auditable security solutions such as CertiKOS and atomic cross-chain transactions (Atom). Notable contributions: CoSi (collective signing), OmniLedger (sharded blockchain), and privacy-preserving protocols like PURBs (Protected Unsealable Recursive Boxes). His lab collaborates with Swiss Post to audit e-voting systems and designs democratic cryptocurrencies like PoPCoin.

Katsuro Inoueمشاهده پروفایل

استاد

• Software Engineering
• Program Analysis
• Code Clone Detection
• +۵ مورد دیگر

Katsuro Inoue is a Professor at Ritsumeikan University within the College of Information Science and Engineering. He holds a Dr. degree of Engineering from Osaka University (1984) and specializes in Software Engineering with a focus on Program Analysis , Code Clone Detection , Software Ecosystem Analysis , and Process Modeling . His work includes developing systems like CCFinder for code clone analysis and SPARS for software component significance ranking. Research Interests Program Analysis: Code Clone Analysis, Origin and Evolution Analysis, Software Ecosystems, Bug Detection, Analysis Tools and Algorithms Program Reuse: Code Search Engines, Program Archives, Searching Mechanisms Software Process: Process Modeling, Process Centered Environments, Process-Based Metrics, Quality Standards Key Publications Code Clone Analysis (2021), Library Dependency Updates (2018), Code Clone Tracking in Open Source (2012), Distributed Code Clone Detection (2007), Software Component Significance Ranking (2005), Compiler Garbage Collection (1991), Code History Tracking (2012) Professional Activities Program Committee Member in over 20 conferences (ICSE, IWPSE, PROFES) Editorial Board Member for IEEE Transactions on Software Engineering Co-Chair of multiple workshops (IWSC, IWPSE) Reviewer for SEC Journal Teaching Course: System Architect Course Developed course materials for Compiler Design and Language Processing Created exam problems and optimization examples for language processing courses

Zhiyuan Liمشاهده پروفایل

استاد

• Program Analysis
• Compiler Design
• Parallel Computing
• +۶ مورد دیگر

Zhiyuan Li is a Professor in the Department of Computer Sciences at Purdue University's College of Engineering. His primary research and teaching focus on program analysis, transformation, and run-time management for high-performance computing and multicore systems, as well as reliable software for networked embedded systems. Professor Li teaches graduate-level courses including CS502: Compiling and Programming Systems and CS591RS1: Research Seminar for First-year Graduate Students. Office: LWSN 3154H Contact: li@cs.purdue.edu Phone: +1 765-494-7822 Professor Li's research spans multiple areas within computer science, with particular emphasis on compiler design, program analysis, and parallel computing. His work addresses fundamental challenges in enabling efficient execution of applications on modern parallel architectures, including multicore processors and large-scale distributed systems. He has made significant contributions to techniques for data dependence analysis, loop parallelization, array privatization, and memory optimization in compilers. His research also extends to reliable software development for embedded and sensor network systems, where resource constraints and reliability requirements present unique challenges. Professor Li's publication record demonstrates consistent contributions to top-tier conferences and journals in computer science, particularly in the areas of parallel computing, compiler optimization, and high-performance numerical methods. His work shows a progression from foundational compiler techniques to applications in scientific computing domains such as computational fluid dynamics for jet engine noise simulation. This interdisciplinary approach connects low-level program analysis with real-world engineering applications requiring petascale computing resources. Principal Investigator for NSF/PetaApps project on jet engine noise simulation Principal Investigator for Intel-sponsored research on data dependence profiling Extensive service on program committees for major conferences including ICS, PPoPP, and LCTES Professor Li has been actively involved in mentoring graduate students through research projects and course instruction. His jet engine noise simulation project specifically mentions training three Ph.D. graduate students and involving undergraduate research assistants. As coordinator for the first-year graduate research seminar, he plays a significant role in guiding new students through the transition to graduate research work in computer science. His laboratory work focuses on developing compiler techniques and runtime systems for parallel and high-performance computing. The research infrastructure includes implementations in GCC for fast data dependence profiling and support for SIMD/SSE instructions, demonstrating practical applications of theoretical compiler techniques.

Phillip Raffeckمشاهده پروفایل

پژوهشگر

• Real-Time Systems
• Embedded Systems
• Energy-Aware Computing
• +۷ مورد دیگر

Phillip Raffeck is a researcher at the Department of Computer Science (INF) within the Chair of Computer Science 4 (System Software) at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU). His work focuses on real-time systems, embedded systems, and energy-aware computing, with a particular emphasis on worst-case execution time (WCET) and energy consumption (WCEC) analysis. He has contributed to projects like the Invasive Run-Time Support System (iRTSS) and tools for energy-neutral system design. Department: Department of Computer Science (INF) University: Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) Position: Researcher His research spans real-time systems , multi-core optimization , and power-aware computing . Key contributions include migrative synchronization protocols , energy-neutral operating systems , and code metrics for timing analysis . Recent work explores carbon-aware co-design and predictable migration in embedded environments. Publications highlight collaborations with teams across Germany and international symposia like RTSS, WCET, and EMSOFT. His article trends reflect advancements in intermittent execution models , transactional networking , and static analysis toolchains . He serves as a secondary reviewer for conferences including RTAS and ISORC. Phillip supervises graduate theses on topics such as DMA-based OS offloading , dynamic migration , and interrupt latency analysis . He contributes to teaching courses like Betriebsystemtechnik and Systemnahe Programmierung in C at FAU.

Sandro Bartoliniمشاهده پروفایل

دانشیار

• High-Performance Computing (HPC)
• Computer Architecture
• Embedded Systems
• +۵ مورد دیگر

Sandro Bartolini serves as Associate Professor in the Department of Information Engineering and Mathematical Sciences at the University of Siena, Italy, where he teaches advanced courses in computer architecture and parallel programming while leading cutting-edge research in high-performance computing systems. His academic journey began with a cum laude Laurea in Computer Engineering followed by a PhD in Computer Science and Engineering from Università di Pisa. Education: PhD in Computer Science and Engineering, Università di Pisa Laurea in Computer Engineering (cum laude), Università di Pisa Research Focus: His work centers on photonic interconnects for chip multiprocessors , energy-efficient software optimization for multi-core/GPU architectures, and performance-portable parallel programming models . Current investigations span cryptographic acceleration, blockchain algorithms, and hardware/software co-design for emerging computing paradigms, with strong emphasis on practical implementations bridging theoretical advances and real-world applications. Publication Trends: Recent publications (2019-2023) reveal three dominant threads: (1) Photonic network innovations addressing energy bottlenecks in chip multiprocessors, (2) The PHAST library ecosystem enabling seamless CPU/GPU programming across domains from autonomous vehicles to UAV navigation, and (3) Hardware accelerator designs for convolutional networks and cryptographic workloads. These works consistently target performance-portability challenges in heterogeneous computing environments. Grants and Collaborations: As principal investigator for the Italian Ministry-funded PHOTONICA project, he established international research partnerships with Murcia University, Columbia University, and Hong Kong University of Science and Technology, while securing industry collaborations with STMicroelectronics, Intel Munich, IBM, and IMEC. He has also managed complex IT system deployments for Siemens Italy, RAI (Italian public broadcasting), and SpaceDys. Academic Leadership: Bartolini serves as Associate Editor for the Eurasip Journal of Embedded Computing and actively contributes to the European HiPEAC network. His research group at Siena maintains strong industry ties for technology transfer, particularly in photonic interconnect validation and parallel programming frameworks for next-generation computing systems.

Binoy Ravindranمشاهده پروفایل

استاد

• Computer Systems
• Software Verification
• Concurrency
• +۷ مورد دیگر

Binoy Ravindran is a Professor at Virginia Tech’s College of Engineering, Department of Electrical and Computer Engineering, leading the Systems Software Research Group (SSRG). His research focuses on computer systems, emphasizing security, performance, concurrency, distributed systems, and real-time computing, with recent work in software verification and heterogeneous-ISA platforms. Key projects: Low-level Reasoning Machine (LLRM), Popcorn Linux, LibrettOS, Hyflow, HermiTux, SlimGuard, HydraVM, KairosVM. He has co-authored 15+ papers from 2025 to 2022, spanning venues like ASPLOS, POPL, PLDI, VEE, PPoPP, and MIDDLEWARE, with awards including ACM Distinguished Scientist and eight Best Paper Awards. Service roles: Editorial Boards (IEEE Transactions on Cloud Computing, ACM TECS), Program Co-Chair (ACM Systor 2025), Committee memberships across ASPLOS, PLDI, and more.

Steve Blackburnمشاهده پروفایل

استاد

• Memory Management
• Garbage Collection
• Virtual Machine Design and Implementation
• +۷ مورد دیگر

Steve Blackburn is a research scientist at Google DeepMind and professor of computer science at the Australian National University in the College of Engineering and Computer Science. His primary research focus is on programming language implementation, with expertise spanning memory management, virtual machines, and performance analysis. He has served in significant leadership roles including Associate Dean for Diversity and Inclusion (2016-2019) and as Program Chair for PLDI 2015 and General Chair for PLDI 2023. Blackburn's research interests center on making software run faster and more power-efficiently on modern hardware. His primary areas include microarchitectural support for managed languages, fast and efficient garbage collection, and the design and implementation of virtual machines. He maintains a strong interest in sound methodology and infrastructure for successful research innovation. His work bridges theoretical computer science with practical systems implementation, with particular focus on memory management frameworks and performance benchmarking. His publication record reveals a consistent focus on memory management systems, with recent work exploring garbage collection in modern contexts including CRuby, Julia, mobile devices, and memory-disaggregated datacenters. His research shows an evolution from foundational garbage collection algorithms toward practical implementations addressing real-world constraints in contemporary programming languages and hardware platforms. A notable trend is his increasing focus on quantifying and understanding the true costs of garbage collection in production environments. Fellow of the ACM Blackburn has supervised numerous doctoral students including Zhen He, John Zigman, Robin Garner, Ting Cao, and currently advises Wenyu Zhao, Zixian Cai, and others. He has also served on multiple program committees for major conferences including PLDI, ASPLOS, ISMM, and OOPSLA, demonstrating his significant contributions to the programming languages and systems research community. His service includes editorial roles for ACM Transactions on Programming Language Applications and Systems from 2017-2020. He leads two major research infrastructure projects: the MMTk memory management framework and the DaCapo benchmark suite, both of which have become foundational tools for researchers in programming languages and systems. These projects reflect his commitment to shared research infrastructure and reproducible methodology in systems research.

• Computer Engineering
• Reconfigurable Computing
• Embedded Systems
• +۴ مورد دیگر

Keyvan Shahin is a Professor in the Computer Engineering department at BTU Cottbus-Senftenberg. His work focuses on reconfigurable computing, embedded systems, robotics, and communication architectures. He advises multiple doctoral students including Amritha Premkumar and Muhammad Amin Qureshi. Education details are not explicitly listed in the provided text, but his research interests span adaptive UAV swarm systems, algorithm optimization for hardware architectures, and domain-specific processor design. His recent publications explore topics like modular UAV communication, polynomial connections in signal processing, and reconfigurable hardware acceleration techniques. Keyvan leads the Computer Engineering Group and contributes to projects such as the UBICO initiative. His technical expertise includes developing automated toolflows for CGRA (Coarse-Grained Reconfigurable Array) architectures and advancing adaptive processor design methodologies. He holds a Master of Science degree and can be reached at keyvan.shahin@b-tu.de . His office is located in Building 1C, Room 1.39.

• Biomedical Engineering
• Biomedical Signal Processing
• Entropy Analysis
• +۷ مورد دیگر

Georgios Manis is an Associate Professor in the Department of Computer Science and Engineering at the School of Engineering, University of Ioannina, Greece. He holds a PhD from the National Technical University of Athens and has been a faculty member at the University of Ioannina since 2002, progressing from Lecturer to Associate Professor in 2018. He has also served as temporary teaching staff at the University of Patras, University of Crete, and University of Ioannina in the late 1990s and early 2000s. Education: B.Sc. in Computer Engineering (Diploma), National Technical University of Athens (NTUA), 1987–1992 MSc in Advanced Methods in Computer Science (Distributed and Parallel Systems), Queen Mary, University of London, 1992–1993 PhD in Computer Engineering, NTUA, School of Electrical and Computer Engineering, 1993–1997 His research interests lie at the intersection of Biomedical Engineering and Computing Systems , with a strong emphasis on Biomedical Signal Processing , Entropy Analysis , and Machine Learning . He has pioneered work in Bubble Entropy —a parameter-free entropy measure—and developed fast algorithms for entropy computation. His work also extends to compiler design and parallel computing, particularly in the automatic parallelization of recursive functions and loops. The trends in his recent publications reflect a dual focus: (1) biomedical applications involving entropy, heart rate analysis, and disease diagnosis using machine learning (especially Random Forests and SVMs), and (2) high-performance computing, including parallelization techniques and compiler optimizations for multi-core and SVP architectures. His research is highly interdisciplinary, combining signal processing, algorithm design, and clinical applications. Scientific Leadership and Recognition: Guest Editor, Special Issue on “Entropy in Biomedical Engineering”, Entropy (MDPI) Member of the IPAN Laboratory, University of Ioannina Active contributor to IEEE, Elsevier, and MDPI journals He has supervised several graduate students and is involved in funded research projects such as Palimpsest and Homore , focusing on smart systems for cultural interaction and elderly monitoring. His advising contributions are evident in co-authored papers with students like Evanthia Tripoliti and Aristeidis Mastoras. He teaches both undergraduate and postgraduate courses, including Compilers I/II and Biomedical Data Analysis . Laboratories and Teams: He is a member of the IPAN lab at the University of Ioannina, which supports interdisciplinary research in informatics and biomedical applications. His collaborative network includes researchers from Greece and abroad, particularly in the fields of biomedical signal analysis and entropy-based methods.

• Programming Languages
• Concurrency
• Embedded Systems
• +۴ مورد دیگر

Dr. Emil Sekerinski is a Professor in the Department of Computing and Software at McMaster University. He holds the position of Undergraduate Advisor for Computer Science (Jan 1, 2025 – June 30, 2025). His expertise spans programming logic (verification, refinement), concurrency (components, implementation), embedded systems (modelling, analysis), and programming languages (run-time, compilation). He is actively involved in research clusters focused on Digital & Smart Systems. His research interests emphasize formal methods in computer science, concurrency theory, parallel algorithms, and embedded systems design. He has contributed to advancing methodologies for software quality assurance and system reliability through formal specifications and automated verification techniques. Recent work includes efficient synchronization mechanisms for object-oriented programming languages and formal development of delay-tolerant multicast protocols for wireless sensors. Dr. Sekerinski has organized and participated in major conferences such as FMTea'24 (Co-Chair) and ICTAC'24 (Program Committee). His teaching includes advanced courses like CAS 781 Advanced Topics: Advanced Compiler Design and Optimization and SFWR ENG 3BB4 Concurrent System Design . He maintains an active presence in academic outreach through LinkedIn, Instagram, and other platforms. His work bridges theoretical foundations with practical applications, including environmental sensor data analysis and holistic embedded system development. Despite no explicit mention of awards, his contributions to formal methods education and research are widely recognized in his field.

Joachim Falkمشاهده پروفایل

پژوهشگر

• Electronic System Level Design
• Hardware-Software Co-Design
• Data-Flow Graphs
• +۶ مورد دیگر

Joachim Falk is a researcher at the Department of Hardware-Software Co-Design (Computer Science 12) at Friedrich Alexander University Erlangen-Nuremberg. With over 20 years of experience since joining the department in 2004, he specializes in electronic system level design, dataflow programming, and hardware-software co-design, contributing significantly to the field through publications, teaching, and research leadership. His educational background includes: Doctorate degree (Dr.-Ing.) in Computer Science from FAU (2014) Diploma degree in electrical engineering (data processing) from Georg-Simon-Ohm University of Applied Science Nuremberg (2002) Falk's research focuses on Electronic System Level Design, Hardware/Software Code Generation for Data-Flow Graphs, Compiler Optimizations, and Parallel Architectures. His work bridges theoretical computer science with practical embedded systems implementation, particularly through the SystemC framework and his contributions to the SysteMoC language. He actively explores energy-efficient computing approaches for dataflow networks and embedded systems, with recent work emphasizing self-powering networks, clock and power gating techniques, and multi-reader buffer implementations for heterogeneous architectures. His recent publication trends reveal a consistent focus on optimizing dataflow networks for energy efficiency and performance. Key themes include self-powering dataflow networks, innovative clock and power management techniques, buffer management strategies for heterogeneous many-core systems, and invasive computing approaches. His research demonstrates a strong connection between theoretical models and practical implementation challenges in embedded systems design. Dr. Falk teaches courses including 'Entwicklung interaktiver eingebetteter Systeme' (Development of Interactive Embedded Systems) for Winter Semester 2024/2025 and 'SystemC' for Summer Semester 2024, supervising multiple theses on security modeling at the electronic system level and sleep/wake-up strategies for hardware implementations of dataflow networks. His research is conducted within the framework of projects like SysteMoC (representation of computational models in SystemC) and SystemCoDesigner (design space exploration for embedded systems).

Johannes Hölzlمشاهده پروفایل

پژوهشگر

• Formal Verification
• Probabilistic Programming
• Markov Chains
• +۷ مورد دیگر

Johannes Hölzl is a Post-doctoral Researcher in the Faculty of Science , specifically within the Department of Computer Science at Vrije Universiteit Amsterdam . He works in the Section of Theoretical Computer Science , focusing on formal verification and probabilistic systems. His research integrates higher-order logic with programming languages to model and verify complex computational processes. Position: Post-doctoral Researcher Institution: Vrije Universiteit Amsterdam Department: Computer Science Section: Theoretical Computer Science Hölzl's research spans formal verification, probabilistic programming, and concurrency. He has contributed extensively to the Isabelle/HOL proof assistant, formalizing mathematical structures like measure theory, Markov chains, and timed automata. His work bridges theoretical analysis with practical verification tools, ensuring rigorous proofs in automated reasoning. His publications highlight advancements in probabilistic systems, including formalizing Markov decision processes (2017), verifying compilers for probability density functions (2015), and analyzing expected running times of probabilistic programs (2016). The 2025 article on probabilistic timed automata indicates ongoing exploration of concurrent probabilistic models. Hölzl has no explicitly listed scientific awards in the provided texts. His collaborations with researchers like Tobias Nipkow and Andrei Popescu underscore interdisciplinary efforts in formal methods and security verification. He contributes to the Theoretical Computer Science Section at VU Amsterdam, advancing foundational research in logic-based programming and probabilistic modeling.

Diego Garbervetskyمشاهده پروفایل

دانشیار

• Static analysis
• Program verification
• Smart Contract analysis
• +۵ مورد دیگر

Diego Garbervetsky is an Associate Professor at the Computer Science Department, School of Sciences, University of Buenos Aires, and a Researcher at ICC/CONICET. He also serves as Director of the Institute of Research in Computer Sciences (ICC). His academic career spans multiple roles in software engineering research and education. His educational background is not explicitly stated in the provided texts, but his current position reflects extensive academic achievement. Garbervetsky's research focuses on static analysis techniques for Java-like programs and Smart Contracts, automated program verification , program understanding , and validation . His specific interests include program understanding, testing and verification of programs featuring rich protocols, static analysis for program verification, and automatic symbolic resource analysis (gas consumption, dynamic memory, energy, etc.). His research has significant implications for blockchain technology, particularly in smart contract verification. Analysis of his recent publications reveals a strong trend toward smart contract security and verification , with multiple papers on modal abstractions, predicate abstractions, and tools like VeriSol for Solidity smart contracts. His work bridges formal methods with practical software engineering challenges, particularly in the blockchain domain. His scientific contributions include the development of multiple research tools: Contractor: Automated tool for behavior validation Contractor.NET: Visual Studio extension for .NET validation JConsume2: Compositional analysis for Java heap memory Consume.Net: Compositional analysis for .NET heap memory BudaPest: Automated software verifier VInTime: Verification suite for Real Time systems Garbervetsky has supervised numerous PhD students including Daniel Wappner, Javier Godoy, and Alexis Soifer, with former students now working at companies like Microsoft, Veritran, and Dialpad. He has served on program committees for major conferences including ICSE, FSE, ASE, and ISSTA, demonstrating his standing in the software engineering research community. His service includes chairing workshops and serving on artifact evaluation committees, showing his commitment to research quality and reproducibility. He currently teaches Software Engineering 2 at the University of Buenos Aires, having previously taught courses in algorithms, automatic software validation, program analysis, programming paradigms, and computer organization.

Michelle Stroutمشاهده پروفایل

استاد

• High Performance Computing
• Compilers
• Run-time Systems
• +۴ مورد دیگر

Michelle Strout is a Professor in the Department of Computer Science at the University of Arizona, where she has been faculty since August 2015. Her research focuses on high-performance computing with particular expertise in compiler technologies and parallel systems. Her research interests span multiple domains within computer systems: High Performance Computing for scientific applications Compiler design and optimization techniques Run-time systems for parallel execution Scientific computing methodologies Software engineering for performance-critical systems Dr. Strout has made significant contributions to the field including the Universal Occupancy Vector (UOV) for storage mappings in stencil computations and the Sparse Polyhedral Framework (SPF) for inspector-executor loop transformations. Her work addresses fundamental challenges in parallelization of irregular applications like molecular dynamics simulations. Her scientific recognition includes: NSF CAREER Award (2008) DOE Early Career Award (2010) Dr. Strout is actively involved in the programming languages and high-performance computing communities, serving on program committees for major conferences including PLDI, SPLASH, and PPoPP. She has demonstrated commitment to mentoring through her involvement with PLMW (Programming Languages Mentoring Workshop), where she has served as organizer, session chair, and presenter.

• Abstract Interpretation
• Programming Language Semantics
• Formal Methods
• +۱۲ مورد دیگر

Giorgio Levi is a Full Professor in the Department of Computer Science at the University of Pisa, Italy. He works on theoretical aspects of programming languages and formal methods. Research includes interpreter design and abstract interpretation Teaches courses on Abstract Interpretation in Declarative Languages Contributed to projects like FIRB - Model B - Pisa Research Interests : His work focuses on abstract interpretation, programming language semantics, and code analysis. He has developed interpreters for functional languages, denotational semantics, operational semantics, and type inference systems. Teaching : He teaches a course on abstract interpretation in declarative languages, with materials including denotational interpreters, operational semantics, and run-time structures. Projects : Involved in the FIRB - Model B - Pisa research initiative, which relates to interpreter refinements and semantic evaluation functions.