جست‌وجوی استاد و پژوهشگر

Bowen Xuمشاهده پروفایل

استادیار

• Software Engineering
• Machine Learning
• Program Analysis
• +۱۲ مورد دیگر

Bowen Xu is an Assistant Professor in the Department of Computer Science at North Carolina State University (NC State), College of Engineering. His research focuses on software engineering, machine learning, and program analysis, particularly in securing AI models and improving code quality. He holds a PhD from Singapore Management University (SMU), where he also conducted postdoctoral research. Education: PhD in Computer Science, Singapore Management University (SMU) Postdoctoral Researcher, SMU School of Computing and Information Systems Research Interests: AI for Code, Backdoor Attacks on Code Models, Vulnerability Detection Code Representation Learning, Model Compression, Safety of AI Systems Chatbot Development for Developers, Automatic Code Review Key Contributions: Developed PTM4Tag+, a Stack Overflow tag recommendation system using pre-trained models Explored stealthy backdoor attacks in code and reinforcement learning systems Pioneered work on automatic vulnerability repair using LLMs and broader input analysis Awards: 2022: Honorable Mention Award (ACSAC) 2018: Highly Commended Full Paper Award (ESEM) Service Roles: Editorial Board Member, Empirical Software Engineering Journal Program Committee Co-chair for ICSE/FSE Research Tracks Organized workshops like FORGE, MaLTeSQuE, and SEA4DQ Labs & Teams: Leads the Softmax Lab at NC State, advising 12+ students across PhD, Master's, and undergraduate levels. Alumni include industry professionals at Microsoft, Barclays, and Marvell Semiconductor.

• Computer Architecture
• Parallel Systems
• Network-on-Chip Design
• +۴ مورد دیگر

Dr. Cruz Izu is a Lecturer in the School of Computer and Mathematical Sciences at the University of Adelaide. She holds a BSc (Hons) in Computer Science and a PhD in Computer Architecture from the University of the Basque Country, along with a Graduate Certificate in Online Learning from the University of Adelaide. Her research focuses on two primary areas: interconnection network design for parallel systems and computer science education methodologies. Research Interests: Interconnection networks in parallel systems and Network-on-Chip architectures Computer Science Education, including program comprehension, code quality assessment, and pedagogical strategies for novice programmers Computational thinking and problem-solving in early university education Teaching Contributions: Coordinator for Masters of Computing and Innovation program Lead developer of Systems, Programming, and Problem Solving courses Former coordinator of the Google-funded Educators PD program (2011-2020) Collaborations: International partnerships with institutions in Spain, Italy, and Australia Contributions to the design of the SACE Digital Technologies curriculum Professional Activities: Editor of Informatics in Education (2021 Special Issue on Abstraction) PC member for SIGCE and ITiCSE conferences

Wieland Konradمشاهده پروفایل

پژوهشگر

• Software Engineering
• Model-Driven Engineering
• Collaborative Systems
• +۳ مورد دیگر

Wieland Konrad is a researcher affiliated with the Institut für Softwaretechnik und Interaktive Systeme at TU Wien. His work focuses on model-driven engineering, software versioning, and collaborative systems. He has extensively contributed to advancing model versioning techniques, conflict resolution in software models, and UML-based solutions. His research emphasizes practical applications in software development lifecycle management and educational methodologies for UML. Key research areas include: Model versioning systems and semantics Conflict detection and resolution algorithms Collaborative cross-organizational modeling EMF/UML profile-based extensions Software evolution analysis His publications highlight advancements in concurrent modeling tools like Colex, adaptable versioning frameworks, and educational strategies for large-scale UML teaching. While no awards are listed, his prolific output since 2009 demonstrates sustained academic contribution.

• Software Engineering
• Green Software Development
• Sustainable Computing
• +۶ مورد دیگر

Félix García is a prominent professor at the University of Castilla-La Mancha in Ciudad Real, Spain, with extensive contributions to software engineering, sustainable computing, and business process management. His research spans over two decades with 187 publications indexed in dblp, demonstrating consistent scholarly productivity and leadership in multiple research areas. Dr. García's research interests focus on critical contemporary challenges in software development, particularly green software engineering, energy efficiency in computing systems, and sustainable software development practices. His work bridges theoretical foundations with practical applications, addressing how software design, implementation, and maintenance impact environmental sustainability. He has pioneered research connecting software quality attributes with energy consumption, examining how design patterns, code smells, and refactoring techniques affect resource usage. His recent publications (2023-2025) reveal a strong focus on cutting-edge topics including Green AI, quantum computing sustainability, and energy-aware programming language design. These works demonstrate his ability to anticipate and address emerging challenges at the intersection of software engineering and environmental sustainability. Dr. García has received significant recognition through numerous collaborations, particularly with Mario Piattini (133 co-authored papers), Francisco Ruiz (63 papers), and María Ángeles Moraga (30 papers), establishing him as a central figure in his research community. His work has appeared in prestigious venues including IEEE Transactions on Software Engineering, Journal of Systems and Software, and ACM Computing Surveys. He has mentored numerous researchers who have become established scholars in their own right, including Javier Mancebo, Laura Sánchez-González, and César Jesús Pardo Calvache. His contributions to gamification in software engineering education through serious games like GLOBAL-MANAGER demonstrate his commitment to innovative teaching approaches.

Edgar Vadimovich Vatamanitsaمشاهده پروفایل

استادیار

• Client-server programming
• Java and Android pattern development
• Application information systems
• +۶ مورد دیگر

Edgar Vadimovich Vatamanitsa serves as an Assistant Professor in the Department of Computer Science at Chernivtsi National University, specializing in cross-platform software development and cloud computing applications. His work bridges academic research with industry practice through active engagement in both university teaching and commercial software development. Education: Yuriy Fedkovych Chernivtsi National University (2013): Systems Software, Software Engineer Dr. Vatamanitsa's research centers on Java/Android pattern development, client-server architectures, and distributed systems. He pioneers practical implementations of design patterns in cloud environments, with significant contributions to optical field simulation, semiconductor modeling, and intelligent transportation systems. His methodology emphasizes cross-platform efficiency and real-world applicability of theoretical computing concepts. Analysis of his 2022-2024 publications reveals dominant themes in cloud-based optical computation (AWS infrastructure), Java pattern implementation for Android, and cross-platform solutions for traffic management and semiconductor physics. His work consistently integrates distributed systems with domain-specific challenges in optics, printing technology, and educational analytics, demonstrating exceptional versatility across engineering disciplines. Professional Activities: Member of Bukovina Information Technology Cluster (since 2022) Senior Software Developer at EPAM SYSTEMS Certificate in Cross-platform Programming and Information Security (Ternopil National Technical University, 2023) Tech Summer Bootcamp for Teachers participant (2023)

Markus Borgمشاهده پروفایل

مدرس

• Artificial Intelligence
• Software Engineering
• Empirical Software Engineering
• +۱۱ مورد دیگر

Dr. Markus Borg is a Senior Researcher and Adjunct Lecturer at Lund University, Sweden, specializing in the intersection of software engineering and applied artificial intelligence. He is a Principal Researcher at CodeScene and contributes to editorial boards for Empirical Software Engineering and IEEE Software . His work bridges academic research with industrial practice through collaborations with Ericsson and contributions to open-source tools like SMIRK. Markus's research focuses on empirical software engineering , technical debt , safety engineering , and requirements engineering for AI-integrated systems. He explores two key directions: AI4SE (applying machine learning to software engineering challenges like defect management and technical debt remediation) and SE4AI (ensuring quality assurance for ML components in safety-critical domains such as automotive systems). His work aligns with regulatory frameworks like the EU AI Act and industry standards for automotive safety. 2025 Contributions : Gamify Track: Two papers on gamification in software maintainability ICSE Journal-First: Longitudinal study on automated bug assignment at Ericsson IDE Track: Trust calibration in AI-assisted refactoring TechDebt Technical Papers: ACE tool for LLM-based technical debt remediation 2024 Contributions : PROFES: AI Act compliance in requirements engineering MO2RE: Code quality specifications TechDebt: Maintainable code ROI analysis Programming with AI: CodeScene platform demonstration 2023 Contributions : CAIN: ML testing in automotive perception systems EASE: Code ownership and defect resolution Mutation Track: Safety-critical mutation testing validation His recent publications emphasize automated defect management , LLM-driven refactoring , and safety validation for ML components , particularly in automotive contexts. Tools like SMIRK and ACE demonstrate practical applications of his research. Markus actively participates in program committees for ICSE, TechDebt, and ICSME, with a focus on bridging academic research with industrial AI/SE challenges.

Michele Lanzaمشاهده پروفایل

استاد

• Software Engineering
• Software Visualization
• Software Evolution
• +۷ مورد دیگر

Michele Lanza is a Full Professor at the Faculty of Informatics, Università della Svizzera italiana (USI), Lugano, where he co-founded the faculty in 2004. He is the founder and director of the Software Institute (since 2017) and leads the REVEAL research group, focusing on software visualization, evolution, and analytics. He holds a PhD from the University of Bern (2003), where he also earned his MSc (1999), and was a postdoctoral researcher at the University of Zurich. Research Interests: Software Engineering Software Visualization (notably the 'City Metaphor') Mining Software Repositories (MSR) Software Evolution and Analytics Program Comprehension Reverse Engineering and Architecture Recovery His recent publications (2023–2025) emphasize immersive software visualization in virtual reality, automated documentation, code refactoring, and empirical studies on developer behavior and documentation. There is a strong trend toward human-centric, visual, and data-driven approaches, often leveraging VR and interactive tools for deeper software understanding. Scientific Awards: Ernst Denert Award (2003) Credit Suisse Teaching Award (2007, 2009) Best Paper Awards (SANER 2024, VISSOFT 2022, ICPC 2016) Most Influential Paper Award (MSR 2010) Advising and Grants: Prof. Lanza has supervised over 13 PhD students and numerous MSc and BSc theses, fostering a vibrant research group. He leads multiple funded projects, including SNF grants (FORCE, TUML, INSTINCT, PROBE, ESSENTIALS, BIGDATA), FFL (CSRD), and industry R&D initiatives. Funding supports travel, hardware, software, and PhD positions, enabling cutting-edge research in software engineering. Labs and Teams: He leads the REVEAL research group and the Software Institute at USI, which serve as hubs for innovation in software visualization, mining, and evolution. These teams are highly collaborative, interdisciplinary, and active in top-tier conferences (ICSE, FSE, ICSME, MSR, VISSOFT).

Ioannis Stamelosمشاهده پروفایل

استاد

• Software Engineering
• Open Source Software
• Software Effort and Quality Estimation
• +۷ مورد دیگر

Ioannis Stamelos is a Professor of Software Engineering at the School of Informatics, Aristotle University of Thessaloniki (since 2015, research/teaching staff since 1997). He serves as Director of the Postgraduate Master Course in Interactive Hardware & Software Technologies. Major Research Areas: Open Source Software, Software Effort/Quality Estimation, Agile Methods, Enterprise Information Systems Key Projects: Deep Blue/AUTH Research Hub (2018-2022), BlockAdemic (blockchain-based micro-credentials), European Commission Open Source Policy Studies Research Trends from recent publications include: Process mining in library information systems Reusability metrics for software assets Bayesian networks in software project management Impact of design patterns on gaming software defects Technical debt assessment via structural metrics Blockchain applications in supply chain management Scientific Awards: Best Paper Award at IEEE DEST’09 Best Student Paper Award at ICSR 2012 Best Paper Award at QUATIC2012 Education & Leadership: PhD in Computer Science (1988), Diploma in Electrical Engineering (1983). Led numerous EU-funded projects (IST, ERASMUS, FP7) and national initiatives (ΓΓΕΤ, ΕΠΕΑΕΚ). Supervised PhD/MSc students in software reuse, OSS quality, and agile practices.

Jun Yangمشاهده پروفایل

مدرس ارشد

• Chinese linguistics
• second language acquisition
• discourse analysis
• +۲ مورد دیگر

Jun Yang is a Senior Lecturer in Chinese Language at the Department of East Asian Languages and Civilizations, University of Chicago. He serves as Director of the Chinese Language Program and focuses on pedagogy, linguistics, and language evaluation. His work bridges theoretical and applied research in language acquisition and teaching methodologies. University: University of Chicago School: East Asian Languages and Civilizations Role: Director of Chinese Language Program His research interests span Chinese linguistics , second language acquisition , discourse analysis , and Chinese language pedagogy . These areas are reflected in his leadership and instructional strategies within the Chinese language curriculum. Jun Yang’s publication record includes 14 recent articles (2017–2022) focused on optimizing database-backed web applications. Key themes involve automated code refactoring , schema management , reinforcement learning for data pipelines , and performance bug detection . These works emphasize tools for improving software reliability and efficiency in distributed systems and IDE environments. Jun Yang holds a Ph.D. in Second Language Acquisition and Teaching, underscoring his expertise in language education. His email address is yangj@uchicago.edu , and he is based at Classics 416, 1010 E 59th St, Chicago, IL 60637.

Julia Lawallمشاهده پروفایل

پژوهشگر

• Operating Systems
• Domain-Specific Languages
• Program Transformation
• +۴ مورد دیگر

Julia Lawall is a Senior Research Scientist (Directrice de Recherche) at Inria-Paris, where she leads research in the Whisper group. She has made significant contributions to the fields of programming languages, operating systems, and software engineering, with a particular focus on program transformation and Linux kernel development. Her work bridges theoretical computer science with practical software engineering challenges. Dr. Lawall's research primarily centers on the design and implementation of domain-specific languages for operating system problems, program transformation techniques, and automated software evolution. Her most notable contribution is the Coccinelle framework, which has been instrumental in automating the evolution of Linux device drivers for over a decade. Her work spans from theoretical foundations in optimal reduction of the lambda calculus to practical tools that address real-world software maintenance challenges in large-scale systems like the Linux kernel. Her publication record demonstrates consistent contributions across multiple domains, with recent work focusing on Android API evolution, Linux kernel bug detection, and program transformation techniques. The trajectory of her research shows a progression from theoretical programming language concepts to increasingly practical applications in system software maintenance and evolution. EuroSys Test of time award for 'Documenting and Automating Collateral Evolutions in Linux Device Drivers' at EuroSys 2008 Best paper award for 'Diagnosys: Automatic Generation of a Debugging Interface to the Linux kernel' at ASE 2012 Most Influential ICFP Paper Award for foundational work on lambda calculus Best Reviewer at GPCE 2020 and Distinguished Reviewer at ASE 2020 Dr. Lawall has been actively involved in the academic community, serving as program co-chair for numerous prestigious conferences including ASE 2019, FSE 2026, and EuroSys 2025. She has also contributed to community initiatives as the Linux kernel coordinator for Outreachy (2015-2018) and as a member of the advisory board for Software Heritage. Her leadership extends to editorial roles, including associate editor for Higher-Order and Symbolic Computation and membership on the editorial board of Science of Computer Programming. She leads the Whisper research group at Inria-Paris, which focuses on program transformation techniques and their applications to system software. The group has developed several influential tools including Coccinelle, Coccinelle4J, LiLiput, Prequel, and JMake, which have had substantial impact on both academic research and industrial practice in software maintenance and evolution.

• Reconfigurable Computing
• Electronics Design Automation
• Post-Quantum Cryptography
• +۴ مورد دیگر

Dr. Andrea Guerrieri is an Associate Professor at the University of Applied Sciences and Arts Valais-Wallis - School of Engineering , specializing in Reconfigurable Computing, Electronics Design Automation (EDA), and Post-Quantum Cryptography . His work focuses on accelerating FPGA compilation through tools like DynaRapid and optimizing security protocols via Dynamatic , with technologies adopted by industry leaders including Intel, AMD-Xilinx, and CERN . He holds a BSc in Industrial Systems and a MSc in Engineering from HES-SO, and teaches courses in Digital Design and Embedded Hardware. BSc HES-SO in Industrial Systems (2019) BSc HES-SO in Computer and Communication Systems (2017) MSc HES-SO in Engineering (2021) Guerrieri’s research bridges High-Level Synthesis (HLS) and Reconfigurable Architectures to enhance FPGA performance for both terrestrial and space applications . His 2025 publications highlight advancements in heterogeneous computing , energy-efficient PQC , and rapid compilation frameworks . Notably, his 2024 work on DynaRapid achieved 20× speedup in C-to-FPGA implementation. Key scientific contributions span dataflow circuit optimization , dynamic scheduling , and automated code transformations . His 2023 book Applications Enabled by FPGA-Based Technology and 2021 textbook System-on-Chip Design with Arm established foundational references in embedded systems. Awards include Best Paper at FPL 2024 , Outstanding TPC Member at DAC 2024 , and IEEE Senior Membership (2021) . 2024: Best Paper Award (FPL), Outstanding Short Paper Award (HPEC) 2023: H-Saber publication on PQC optimization 2021: IEEE Senior Member recognition As Chair of Onboard Computing for the CHEESE-NASA SSERVI consortium, he leads international collaborations with ETH Zurich, University of Geneva, California State University , and companies like NVIDIA, Arm, and NASA . His projects include the Innosuisse-funded DyReCte initiative (2019–2021) for reconfigurable cryptoengines in nanosatellites.

Ying Wangمشاهده پروفایل

دانشیار

• Dependency management
• Software ecosystem
• Software refactoring
• +۷ مورد دیگر

Dr. Ying Wang is an Associate Professor and doctoral supervisor at the Software College of Northeastern University (China), where she has been working since February 2019. She serves as Assistant Dean at the School of Software and is an active member of several CCF committees including the System Software Committee, Software Engineering Committee, Open Source Development Committee, and Women's Committee. Dr. Wang received her Ph.D. in Software Engineering from Northeastern University in January 2019 under the supervision of Professor Zhiliang Zhu. She completed postdoctoral research at the Hong Kong University of Science and Technology (HKUST) from 2022 to 2023 under Professor Shing-Chi Cheung and was a visiting scholar at Microsoft Research Asia through the StarTrack Program in 2021. Her research focuses on intelligent software development technologies, large AI models, open source software big data analysis, and software supply chain security. She has made significant contributions to the governance of open source software ecosystems across multiple programming languages including Java, C#, Python, Go, JavaScript, Android, and Rust. Her work has led to the development of practical tools like 'League of Legends' for monitoring dependency defects in open source ecosystems, with several technologies commercialized by Huawei and Microsoft. Dr. Wang's recent publications demonstrate her expertise in cross-language dependencies, software component analysis, software refactoring, and the application of large language models in software engineering. Her work spans both theoretical foundations and practical applications, with a strong emphasis on real-world impact through industry collaboration. Among her notable achievements are the ACM SIGSOFT Distinguished Paper Awards at ICSE 2021 and ESEC/FSE 2023, making her the first researcher from Northeastern University to receive this honor. She has also received multiple awards for her doctoral dissertation and prototype implementations. Dr. Wang actively contributes to the academic community as an Associate Editor for IEEE Transactions on Software Engineering and serves on program committees for top conferences including ASE, ICSE, and ESEC/FSE. She mentors a large group of doctoral and master's students, with many alumni securing positions at major technology companies including Huawei, Microsoft, Alibaba, and Tencent.

Zhi Jinمشاهده پروفایل

استاد

• Requirements Engineering
• Self-Adaptive Systems
• Learning from Source Code
• +۵ مورد دیگر

Zhi Jin is a Professor in the Department of Computer Science and Technology at Peking University, where he has been employed since 2009. Previously, he served as a professor at the Academy of Mathematics and System Sciences, Chinese Academy of Sciences from 1994-2009. He received his BS from Zhejiang University in 1984 and MS/PhD from National University of Defense Technology in 1984 and 1992 respectively. He progressed from assistant professor (1992) to associate professor (1995) to full professor (2001). His research focuses on knowledge engineering and software engineering, with special interests in knowledge graphs, self-adaptive systems, and deep learning applications. Current research directions include Self-Adaptive Software in Human-Cyber-Physical Systems, Crowd-based Requirements Engineering, and Learning from both Natural Language and Programming Language. His work bridges theoretical knowledge engineering with practical software development challenges. His recent publications demonstrate a strong trend toward applying large language models and AI techniques to traditional software engineering problems, particularly in requirements engineering, code generation, and vulnerability detection. The articles span multiple high-impact venues including ASE, ICSE, and RE, with significant focus on aerospace applications and multi-agent collaboration approaches. Scientific honors include: Winner of National Science Fund for Distinguished Young Scholars (2006) Project 973 project lead scientist (2014) Member of Discipline Appraisal Group of the Academic Degree Commission (2015) Multiple ACM Distinguished Paper Awards He serves in numerous editorial roles including Associate Editor for IEEE Transactions on Software Engineering (2018-present) and IEEE Transactions on Reliability (2019-present). He is also an Editorial Board Member for Empirical Software Engineering and Requirements Engineering Journal, and holds leadership positions in the China Computer Federation. His extensive conference service includes PC membership for ICSE, FSE, RE, and other major software engineering venues.

Fredrik Kjolstadمشاهده پروفایل

استادیار

• Compilers
• Programming Models
• Systems
• +۵ مورد دیگر

Fredrik Kjolstad is an Assistant Professor of Computer Science at Stanford University. His research focuses on compilers, programming models, and systems for sparse computing, with an emphasis on separating algorithms from data representation. He leads efforts in developing compilers like TACO, Simit, and Legate Sparse to optimize sparse tensor algebra and distributed computations. Kjolstad's work spans compiler design, hardware-software co-design, and programming languages for high-performance computing. His research group aims to enable portable applications across diverse data representations and architectures. Notable projects include the TACO compiler for sparse tensor algebra, the Simit programming language for physical simulations, and the Copy-and-Patch compilation technique for fast runtime code generation. He has also contributed to distributed systems like Legate Sparse and hardware accelerators such as Onyx. Kjolstad has received prestigious awards including the NSF CAREER Award and the MIT EECS PhD Thesis Award. His publications cover topics like sparse tensor compilation, compiler optimization, and agile hardware design. He advises multiple PhD students and collaborates with researchers like Kunle Olukotun and Alex Aiken. Key areas of impact include efficient sparse data processing, compiler-driven hardware design, and scalable distributed computing frameworks. His work bridges theoretical compiler techniques with practical system implementations, aiming to simplify and accelerate complex computational tasks.

Diomidis Spinellisمشاهده پروفایل

استاد

• Software Engineering
• Programming Languages
• Computer Science
• +۵ مورد دیگر

Professor Diomidis Spinellis is a renowned academic in Software Technology at Athens University of Economics and Business (AUEB). He specializes in software engineering practices, code quality, AI ethics, and system architecture. His work bridges theoretical advancements with practical applications in industry, emphasizing reproducibility and empirical methods. Recipient of the IEEE Computer Society's prestigious 'Distinguished Contributor Recognition,' Spinellis is the sole Greek scientist to achieve this honor. His research spans software evolution, security, and open-source ecosystems, with a focus on methodologies like refactoring, static analysis, and debugging strategies. Key research interests include AI-generated content detection, modular data analytics, and incident management systems. His studies often leverage large-scale datasets (e.g., Unix evolution, Linux supercomputing analysis) to uncover patterns in software behavior and development practices. Publications frequently address emerging technologies' societal impacts, such as energy-efficient computing and ethical AI deployment. He advocates for reproducible research through tools like the Alexandria3k framework and contributes to open-source initiatives.