جست‌وجوی استاد و پژوهشگر

Danfeng Zhangمشاهده پروفایل

استاد

• Programming Languages
• Security
• Differential Privacy
• +۵ مورد دیگر

Danfeng Zhang is a faculty member at Duke University whose research sits at the intersection of programming languages and security. Active across the premier PL conferences since 2015, Zhang has served on more than two-dozen program committees and currently co-chairs the POPL Student Research Competition. Education & Affiliation: Home page: users.cs.duke.edu/~dz132 Affiliation: Duke University, United States Research Interests: Zhang’s work spans programming-language design, static and dynamic analysis, formal verification, and security. A recurring theme is developing language-based techniques that guarantee strong security and privacy properties—ranging from side-channel resistance and constant-time execution to differential-privacy proofs—while preserving performance and usability. His recent projects combine type systems, program logics, and automated reasoning to build practical verification tools for concurrent, speculative, and approximate software. Publication Trends: Across nine representative papers (2015-2024) Zhang has advanced static detection of cache side channels, automated proofs of differential privacy, and relaxed concurrency models. The trajectory shows deepening integration of security concerns into language infrastructure, with tool-building (CtChecker, SpecSafe, LightDP) that bridge formal guarantees and real-world systems. Service & Leadership: 2024 POPL Student Research Competition Co-Chair 2025 POPL Program Committee member Repeated reviewer/PC member: PLDI, SPLASH/OOPSLA, ISSTA, ECOOP, APLAS, PriSC, PASS Zhang regularly mentors student researchers through SRC sessions and workshop panels, fostering diversity and early-career participation in the programming-languages community.

• Computer Architecture
• Programming Models
• Parallel Computing
• +۵ مورد دیگر

Marc Gonzalez Tallada is a researcher at the Universitat Politècnica de Catalunya (UPC), affiliated with the Department of Computer Architecture within the Barcelona School of Informatics (FIB). He is a member of the MGT Research Group, focusing on Programming Models and high-performance computing systems. His research interests lie in the domain of computer architecture and programming models, with a strong emphasis on parallel and distributed computing, performance optimization, and system-level software. His work contributes to the design and implementation of efficient programming models that exploit modern parallel architectures. The recent publications (2010–2024) reflect a consistent focus on programming models, particularly in the context of high-performance computing. Key themes include task-based programming, runtime systems, compiler optimization, memory management, and performance analysis. The research spans computer architecture, system software, and compiler design, demonstrating a multidisciplinary approach to solving challenges in parallel computing. Scientific Awards and Recognitions: Premi o reconeixement Advising and Grants: While specific student names are not listed, his involvement in competitive R&D+i projects indicates active participation in funded research. These projects suggest leadership or collaboration in grant-supported initiatives related to programming models and computer systems. His role in innovation and research projects highlights contributions to both academic and applied domains. Labs and Research Teams: He is a core member of the MGT (Programming Models) research group at UPC, which focuses on advancing the state-of-the-art in programming models for parallel and distributed systems.

Tiark Rompfمشاهده پروفایل

استادیار

• Compiler Design
• Programming Languages
• Runtime Code Generation
• +۸ مورد دیگر

Tiark Rompf is an Assistant Professor at Purdue University , with research spanning programming languages, compilers, and systems. His work bridges domains including architecture, databases, machine learning, and AI through projects like Reachability Types and Rhyme. Co-director of the Purdue Center for Programming Principles and Software Systems (PurPL) Scientific Advisor at SambaNova Systems Previously a member of the Scala team at EPFL His research focuses on: Runtime code generation and advanced compiler technology Expressive data-centric query languages (Rhyme, Datalog) Reachability type systems for memory safety and effect handling Metaprogramming and logical relations for formal verification Recent publications highlight contributions to Datalog compilation (Flan), nested data structures (Rhyme), and polymorphic reachability types. He leads projects exploring: Compiler optimizations for emerging architectures (GPU, TPU, FPGA) ML-driven compiler improvements Secure multi-party computation via metaprogramming Scientific awards include: NSF CAREER Award (2016) Google Faculty Research Awards (2017, 2018) DOE Early Career Research Award (2017) ACM SIGPLAN PL Software Award (2019) GPCE Test of Time Award (2020) Students and alumni from his group have joined institutions like Databricks, DeepMind, Galois, and Meta. He teaches advanced compiler courses including: CS 590 - Advanced Topics in Compilers CS 352 - Compilers CS 502 - Graduate Compilers

• Computer Architecture
• Programming Models
• Parallel Computing
• +۴ مورد دیگر

Daniel Jimenez Gonzalez is a faculty member at the Universitat Politècnica de Catalunya (UPC), affiliated with the Department of Computer Architecture within the School of Informatics (FIB). He is an active researcher in programming models and high-performance computing, contributing extensively to the field through publications, projects, and academic supervision. Research Interests: His work focuses on Computer Architecture , Programming Models , and Parallel Computing . He investigates task-based programming, runtime systems, compiler optimizations, and performance modeling for multi-core and heterogeneous architectures. His research addresses challenges in scalability, energy efficiency, and resilience in modern computing environments. His recent publications show a consistent trend in task-based programming models , runtime scheduling , and performance optimization across diverse architectures, including NUMA and GPU-accelerated systems. The work spans from theoretical modeling to practical implementation, often targeting real-world HPC applications. Scientific Awards: No awards explicitly mentioned in the provided text. Advising and Grants: While specific students are not listed, his involvement in doctoral theses and R&D projects suggests an active role in mentoring graduate students. He has participated in both competitive and non-competitive R&D+i projects, indicating grant acquisition and project leadership experience in areas related to programming models and computer architecture. Labs and Teams: He is a member of the UPC PM - Programming Models research group, which focuses on the design, analysis, and optimization of modern programming paradigms for high-performance systems.

Jesper Cockxمشاهده پروفایل

استادیار

• Type Theory
• Dependently Typed Programming
• Pattern Matching
• +۶ مورد دیگر

Jesper Cockx is an Assistant Professor in the Programming Languages group at Delft University of Technology . His research focuses on the theory and implementation of dependently typed languages , particularly Agda , and he is a core contributor to Agda's development. His work bridges Type Theory , Pattern Matching , and practical Compiler Design through tools like agda2hs . Research Interests : Type Theory and Dependently Typed Programming Pattern Matching and Unification Agda and Compiler Implementation Erasure Annotations for Verified Compilation Generic Programming and Language Design Formal Verification of Functional Code Scientific Awards : NWO Veni Grant (2020) for a Trustworthy and Extensible Core Language for Agda Conference Contributions : He serves on program committees for CPP , WITS , POPL , and ICFP . Recent publications analyze erasure annotations , correct-by-construction compilers , and dependent (co)pattern matching in Agda. His work often intersects with Haskell and functional programming education in the Netherlands.

Jacques-Henri Jourdanمشاهده پروفایل

پژوهشگر

• Formal Verification
• Rust Programming Language
• Coq Proof Assistant
• +۵ مورد دیگر

Jacques-Henri Jourdan is a CNRS researcher at the Laboratoire Méthodes Formelles (LMF) , Université Paris-Saclay. His work focuses on formal verification and programming language design , particularly for Rust and OCaml , using proof assistants like Coq and the Iris framework. Current academic rank: Researcher (CNRS) Affiliation: LMF, Université Paris-Saclay Research highlights include: Developing Creusot , a deductive verification tool for Rust Contributing to the Iris concurrent separation logic Formalizing RustBelt for Rust's type system soundness Building a statistical memory profiler for OCaml Scientific awards: GdR GPL 2016 Thesis Prize for his PhD on formal verification Notable contributions to academia: Co-teacher of Advanced Programming at ENS Paris-Saclay Co-development of OCaml's runtime library and parser Active program committee member in POPL, ICFP, and WITS

Tej Chajedمشاهده پروفایل

استادیار

• Formal Verification
• Systems Software
• Concurrency
• +۴ مورد دیگر

Tej Chajed is an Assistant Professor in the Department of Computer Science at the University of Wisconsin-Madison. His research focuses on formal verification of systems software, particularly addressing concurrency and crash safety in file systems and distributed protocols.

• Global Program Analysis
• Verification
• Debugging
• +۵ مورد دیگر

Manuel V. Hermenegildo is a Distinguished Professor at the IMDEA Software Institute and a Full Professor at the Department of Computer Science, Universidad Politécnica de Madrid. He holds a PhD in Electrical and Computer Engineering from the University of Texas at Austin (1986). His academic career spans over four decades, contributing to global program analysis, verification, and parallel computing. Education: PhD, Electrical and Computer Engineering, University of Texas at Austin (1986) M.S., Electrical and Computer Engineering, University of Texas at Austin (1984) M.S., Electrical Engineering, Technical University of Madrid (1981) Research Interests: His work focuses on global program analysis , verification , and optimization for functional/non-functional properties. He pioneered techniques in abstract interpretation , parallelism , and constraint/logic programming . His contributions include the Ciao programming system and the CiaoPP preprocessor, emphasizing static analysis and program debugging . Key Awards: ACM Fellow Julio Rey Pastor Prize (2006) Elected member of Academia Europaea (2010) Test of Time Award at ICLP 2017 His work has been cited over 10,000 times, with an h-index of 60. Leadership & Contributions: Founded and directed the IMDEA Software Institute Directed Spain's National Research Directorate (1999–2002) Chair of major conferences (POPL 2010, ICLP 2006) Labs & Teams: Leader of the CLIP Lab (Computational Logic, Implementation, and Parallelism) Principal investigator in EU-funded projects on resource-aware computing

Rui Abreuمشاهده پروفایل

استاد

• Software Quality
• Software Testing
• Debugging
• +۵ مورد دیگر

Rui Abreu is a Full Professor at the Faculty of Engineering of the University of Porto, Portugal. His academic career spans multiple institutions including IST, ULisbon where he served as an Associate Professor, and the University of Porto where he previously held the position of Assistant Professor. He has also been a Visiting Researcher at Google NYC (2019-2020) and a member of the Model-Based Reasoning group at PARC's System and Sciences Laboratory. Dr. Abreu earned his Ph.D. in Computer Science - Software Engineering from the Delft University of Technology, The Netherlands, and his M.Sc. in Computer and Systems Engineering from the University of Minho, Portugal. His research revolves around software quality with emphasis on automating testing and debugging phases of the software development life-cycle as well as self-adaptation. With extensive expertise in both static and dynamic analysis algorithms, his work spans traditional software engineering, quantum software testing, and security-focused development practices. His recent publications demonstrate a strong focus on applying AI techniques to software engineering problems, quantum software testing, and security vulnerability detection. The trend shows increasing integration of large language models in debugging tools and expanding research into quantum software verification. Dr. Abreu has received significant recognition for his work, including 6 Best Paper Awards and a Distinguished Paper Award at ESEC/FSE 2019. His research has attracted considerable attention in the software engineering community. As an entrepreneur, he co-founded DashDash in January 2017, a platform that allows users to create web applications using only spreadsheet skills. The company secured $9M in Series A funding in May 2018. His industry experience complements his academic work, particularly in the areas of practical software tools and applications. Dr. Abreu has been actively involved in numerous conferences, serving as General Chair for ICST 2020, Program Committee member for multiple tracks across various conferences, and as Steering Committee member for ICST. His leadership in the software engineering community is evident through his extensive service and contributions to the field.

Maurizio Leottaمشاهده پروفایل

پژوهشگر

• Test Automation
• Empirical Software Engineering
• Requirements Engineering
• +۶ مورد دیگر

Maurizio Leotta is a faculty member at the Department of Informatics, Bioengineering, Robotics, and Systems Engineering (DIBRIS) at the University of Genova, Italy. His research focuses on software testing automation, empirical software engineering, requirements engineering, business process modeling, and model-driven software development. He has contributed to advancing end-to-end web testing methodologies through tools like Assessor, STILE, and SleepReplacer-GPT, emphasizing robust locators, thread sleep replacement, and parallel test execution optimization. Primary Affiliation : DIBRIS, University of Genova Research Themes : Test Automation, Gamification in Software Testing, Web Accessibility, IoT Systems Testing In recent years, Leotta has explored the integration of large language models (LLMs) in automated testing, comparing browser automation tools (Selenium, Cypress, Puppeteer, Playwright), and analyzing job market trends post-pandemic. His work spans both practical tool development (e.g., TESTQUEST, Mutta) and empirical studies evaluating testing approaches. He actively participates in program committees for testing workshops and collaborates on gamification initiatives in software development education. The 15 most recent publications reflect his expertise in test automation frameworks, gamification strategies, and accessibility enhancements. Articles cover topics such as explicit wait management in web testing, LLM applications for image captioning, and comparative studies of automation tools. His research also extends to IoT system testing, runtime verification, and job market analysis using large-scale job advertisement data.

Francisco Fernández Riveraمشاهده پروفایل

استاد

• High Performance Computing
• Parallel Processing
• Computer Architecture
• +۵ مورد دیگر

Francisco Fernández Rivera is a Full Professor in the Department of Computer Architecture at the University of Santiago de Compostela (Spain), where he obtained both his BS (1986) and PhD (1990). His academic career spans parallel processing, computer architecture, and high-performance computing applications. He has supervised 7 PhD theses and authored over 150 publications, including 60+ journal articles and 90+ conference papers. Research Focus: His work centers on parallel/distributed system optimization, including compilation of irregular codes, performance prediction, sparse matrix algebra, GIS, and memory hierarchy improvements. Key applications include LiDAR data processing for infrastructure analysis, NUMA system optimization, and heterogeneous computing. Publication Trends: Recent works (2021-2024) emphasize LiDAR-based geospatial analysis, thread/memory optimization for NUMA systems, and heterogeneous computing frameworks (e.g., Intel OneAPI). Methodologies feature parallel algorithms, hardware-aware optimizations, and real-world applications in urban planning and remote sensing. Projects & Leadership: Principal investigator for 8 research projects (e.g., HiPerHC2DA, SDNHPC) focused on high-performance and cloud computing. Manages collaborations in geospatial technologies and parallel systems.

• Program Analysis
• Software Verification
• Debugging
• +۱۳ مورد دیگر

Manuel V. Hermenegildo is a Distinguished Professor at the IMDEA Software Institute and a Full Professor in the Department of Artificial Intelligence at the Technical University of Madrid (UPM). He is the founding Scientific Director of IMDEA Software and leads the CLIP Lab, a joint research unit between UPM and IMDEA Software focused on computational logic, programming languages, and parallelism. His career spans leadership in national research policy, academic positions in Spain and the U.S., and extensive international collaboration. PhD in Electrical and Computer Engineering, University of Texas at Austin (1986) M.S. in Electrical and Computer Engineering, University of Texas at Austin (1984) M.S. in Electrical Engineering, Technical University of Madrid (1981) His research centers on global program analysis, verification, debugging, and optimization for functional and non-functional properties such as time, memory, and energy. He has pioneered work in abstract interpretation, partial evaluation, constraint and logic programming, parallelizing compilers, and computational logic. His methodologies support the development of safe, efficient, and reliable software systems. The integration of static and dynamic analysis, resource-aware compilation, and assertion-based debugging are recurring themes in his work. His recent publications emphasize incremental and modular analysis, assertion checking, energy-aware computing, and verification via Horn clauses. Trends show a strong focus on making static analysis more practical, scalable, and integrated into real-world development workflows, particularly for logic and declarative languages. He frequently publishes in top venues such as TPLP, SCP, TOPLAS, and POPL. ACM Fellow Julio Rey Pastor Prize (2006) Aritmel Prize (2005) Elected member, Academia Europaea (2010) Test of Time Award, ICLP 2017 Best Paper Awards at ICSOC 2011 and ICLP 2005 Fulbright-Hays Scholarship Hermenegildo has supervised numerous PhD students and postdocs, many of whom are now leading researchers. He has been principal investigator in over 50 research projects funded by the EU, Spanish government, NSF, and industry partners. His leadership extends to national research policy, where he directed Spain’s National Research Directorate and launched the Ramón y Cajal fellowship program. He has served on tenure and evaluation committees for institutions worldwide and is active in shaping research agendas through roles in Informatics Europe and EIT Digital. He leads the CLIP Lab, which develops advanced program analysis tools and systems such as the Ciao programming environment, CiaoPP static analyzer, and LPdoc documentation generator. The lab fosters collaboration across academia and industry, focusing on next-generation program development tools, verification, and resource-aware computing.

• High-performance computing
• Decimal arithmetic
• Parallel programming
• +۴ مورد دیگر

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.

Nata Stulovaمشاهده پروفایل

پژوهشگر

• Software Engineering
• Formal Methods
• Natural Language Processing
• +۳ مورد دیگر

Nata Stulova is a Researcher currently working as a staff research scientist at MacPaw's Technological R&D Center, focusing on software engineering research involving formal and informal program specifications. Formerly, she held academic roles including senior postdoctoral researcher at the University of Bern (SCG), researcher at EPFL's LARA Lab, and PhD work at the Technical University of Madrid (UPM). Her research spans software documentation consistency, NLP applications, runtime verification, and low-code tools. She has led multiple projects addressing code comment quality, empirical studies on documentation practices, and tool development for requirements engineering. Despite transitioning to industry in 2022, she maintains active collaboration with academia, publishing in top conferences like ICSE and IEEE Transactions. She holds a PhD in Computer Science from UPM and has authored numerous peer-reviewed articles and conference papers. Her work emphasizes bridging academic research with industry applications, particularly in software analysis and developer productivity. Education: PhD in Computer Science, Technical University of Madrid (2018) MSc in Artificial Intelligence, Technical University of Madrid (2013) BSc in Applied System Analysis, NTUU "KPI" (2012) Research Interests: Her work focuses on improving software quality through automated documentation tools, runtime verification techniques, and low-code solutions for requirements engineering. She explores NLP methods for detecting inconsistent or outdated comments and optimizing static analysis efficiency. Recent projects include SwiftEval (LLM-generated code evaluation) and RepliComment (cloned comment detection). She also emphasizes practical applications of formal methods in dynamic languages like Prolog and Python. Grants & Funding: ASA: Agile Software Assistance TRACES: Resource-Aware Software Tools N-GREENS: Energy-Efficient Software Labs/Teams: Core member of the Ciao system development team at IMDEA Software Institute, contributor to the Software Composition Group (SCG) at UniBe, and collaborator with MacPaw's TR&D team on industry-focused R&D.

• High-Performance Interconnection Networks
• Computer Architecture
• Network Simulation
• +۷ مورد دیگر

Francisco J. Andújar Muñoz is an Associate Professor at the University of Valladolid in the Department of Computer Science since January 2024. His career spans multiple institutions including Universidad de Castilla-La Mancha (2008-2015) and Universitat Politècnica de València (2017-2018), with academic roles ranging from Research Assistant to Juan de la Cierva Formación Researcher. PhD in Advanced Computer Science Technologies (2011-2015) MsC in Advanced Computer Science Technologies (2010-2011) Computer Science Engineering (2008-2010) Computer Science Technical Engineering (2004-2008) His research focuses on high-performance interconnection networks , with significant contributions to quality-of-service mechanisms, energy-efficient network topologies, and heterogeneous programming optimization. He maintains the open-source VEF Traces framework for network workload modeling. Recent publications (2023-2025) demonstrate expertise in FPGA high-level synthesis portability, SYCL-based GPU optimization, and machine learning applications for Twitch streaming analysis. His work combines theoretical network design with practical implementations in the Journal of Supercomputing and IEEE Transactions on Computers .