جستجوی استاد راهنمای دانشگاهی

Yao Wan is an Associate Professor at the School of Computer Science and Technology, Huazhong University of Science and Technology (HUST) in Wuhan, China. He leads the ONE Lab, focused on empowering machines to interact with the physical world through unified natural language interfaces (Language + X paradigm). He obtained his Ph.D. from Zhejiang University and has research visiting experience at Chinese University of Hong Kong, University of Technology Sydney, and University of Illinois Chicago. His research bridges Artificial Intelligence and Software Engineering, with core interests in: Natural Language Processing for code intelligence Large Language Model applications Multimodal learning across code, vision, and UI domains Program analysis and code generation Software engineering automation His publications demonstrate strong focus on applying transformer-based models to software engineering challenges, with recent work expanding into multimodal applications. Research spans code model security, GUI generation, data visualization, and compiler understanding, predominantly using deep learning approaches. Awards: IEEE TCSE Distinguished Paper Award for SANER 2025 publication He actively mentors students through the ONE Lab and serves on program committees for top conferences including ASE, ISSTA, and ICSE. He is seeking highly-motivated undergraduate researchers to join his team. The ONE Lab conducts cutting-edge research at the intersection of programming languages and artificial intelligence, with ongoing projects in code intelligence, multimodal learning, and LLM applications for software engineering.

• Artificial Intelligence
• Software Engineering
• Natural Language Processing
• +۳ مورد دیگر

Simone Scalabrino is an Assistant Professor at the University of Molise, Italy, where he is part of the STAKE lab. He also serves as CSO at Datasound. His academic career includes teaching courses such as Automated Software Delivery and Object-Oriented Programming at the University of Molise. Dr. Scalabrino received his Ph.D. from the University of Molise in 2019 with a thesis entitled "Automatically Assessing and Improving Code Readability and Understandability," supervised by Prof. Rocco Oliveto. He earned his Master's Degree in Computer Science from the University of Salerno in 2015 and his Bachelor's Degree in Computer Science from the University of Molise in 2013. His research interests focus on Software Quality, Software Testing, Software Security, and Empirical Software Engineering . Dr. Scalabrino's work spans multiple areas including code readability assessment, software testing methodologies, Docker container analysis, game quality assessment, and voice user interface testing. His research often combines empirical methods with machine learning techniques to address practical software engineering challenges. Analysis of his recent publications reveals a strong focus on improving software quality through various approaches. His work spans code readability assessment, Docker container analysis, game quality testing, and voice user interface evaluation. There's a clear trend toward applying machine learning techniques to traditional software engineering problems, particularly in the areas of code understanding, defect prediction, and quality assessment. His research often involves large-scale empirical studies with real-world data from open source projects and commercial applications. Scientific Awards Distinguished Reviewer Award @ FSE 2025 Distinguished Reviewer for TSE (2023) Best Reviewer Award for JSS (2022) ACM Distinguished Paper Award @ MSR 2019 ACM Distinguished Paper Award @ ASE 2017 ACM Distinguished Paper Award @ ICPC 2016 Dr. Scalabrino has been actively involved in mentoring students through research projects, though specific student names are not listed in the provided information. He has served on program committees for numerous prestigious conferences including ASE, ICSE, ICPC, and FSE. His service extends to reviewing for top-tier journals such as Transactions on Software Engineering and Empirical Software Engineering. He leads or contributes to several research projects including DevProDev, which focuses on developer-centered recommendation systems, and ATTICUS, a tele-monitoring system for ambient-assisted living. Dr. Scalabrino has also developed multiple research tools such as Code Readability Predictor, TIRESIAS, OCELOT, CLAP, and ACRyL to address various software engineering challenges.

• Software Quality
• Software Testing
• Software Security
• +۲ مورد دیگر

Thomas Degueule is a researcher at CNRS (Centre National de la Recherche Scientifique) in France, actively contributing to software engineering research since 2015. He serves on program committees for major conferences including ASE, ICSE, and SLE, with primary research interests in Software Evolution, Empirical Software Engineering, and Domain-Specific Languages. His work focuses on breaking change analysis in APIs and libraries, client-library compatibility testing, and dependency management. He develops practical tools like Roseau for source-based breaking change detection and investigates semantic versioning impacts in ecosystems like Maven Central. His empirical approach leverages large-scale repository analysis to address real-world software maintenance challenges, particularly in Java ecosystems. Recent publications (2023-2025) show consistent contributions to breaking change analysis and compatibility testing, appearing in top venues like ASE, ICSE, and ISSTA. His research bridges theoretical insights with practical tooling for software evolution challenges, demonstrating strong empirical methodology and tool-oriented contributions. No scientific awards are documented in the available information. Degueule has advised no publicly listed students and holds no mentioned research grants. His organizational roles include Program Co-Chair for SLE 2023 and committee positions across multiple conferences, reflecting significant service to the software engineering community.

• Software Evolution
• Empirical Software Engineering
• Domain-Specific Languages
• +۲ مورد دیگر

Chaiyong Ragkhitwetsagul is an Assistant Professor at the Faculty of ICT, Mahidol University, Thailand, and co-founder of the SERU research group. His research focuses on software engineering with emphasis on maintenance, evolution, and program comprehension. Education: PhD in Software Engineering, University College London (UCL) MS in MSIT-Very Large Information Systems, Carnegie Mellon University BE in Computer Engineering, Kasetsart University His work investigates code proficiency metrics for Python and JavaScript to improve maintenance practices, employs search-based techniques for multi-objective clone configuration, and pioneers autorepairability as a novel software quality dimension. Recent publications demonstrate strong empirical focus on developer productivity and code quality assessment. 2024 publications reveal a cohesive trend toward practical tool development (e.g., jscefr) and empirical validation of software quality characteristics, bridging theoretical research with real-world engineering challenges. Active across major software engineering venues (ASE, ICSE, ICSME), he contributes to the community through program committees while leading the SERU research group's mission to advance software engineering science at Mahidol University.

• Software Engineering
• Software Maintenance
• Program Comprehension
• +۳ مورد دیگر

Djamel Eddine Khelladi is a CNRS Researcher at the IRISA laboratory within the DIVERSE team at University of Rennes, specializing in software engineering with emphasis on model-driven techniques and empirical validation. His work bridges theoretical frameworks and industrial-scale applications, particularly in evolving software ecosystems. His academic foundation includes a Ph.D. from Sorbonne University (formerly University Pierre et Marie Curie) at the Laboratory of Computer Science of Paris 6 (LIP6), followed by postdoctoral research at Johannes Kepler University Linz's Institute for Software Systems Engineering. This trajectory established his expertise in software evolution and model-driven approaches. Khelladi's research centers on software evolution challenges, particularly model-code co-evolution in highly-configurable systems like the Linux kernel. He develops scalable analysis tools (e.g., HyperAST, HyperDiff) and investigates empirical phenomena in build systems, configuration management, and polyglot programming environments. Recent work increasingly integrates large language models for automated co-evolution tasks while maintaining rigorous empirical validation. His publication trends reveal a consistent focus on practical tooling for software evolution, with growing exploration of AI-assisted engineering. Key themes include scalability in software history analysis, reproducibility in configurable systems, and debugging multi-language environments, often using Linux kernel ecosystems as testbeds. As an active community contributor, Khelladi serves on program committees for ASE, ICSE, and ESEC/FSE while advancing research through the DIVERSE team at IRISA. This group specializes in variability-intensive software systems, providing the collaborative environment for his empirical and tool-building research.

• Software engineering
• Model-Driven Engineering
• Software Evolution
• +۳ مورد دیگر

Leopoldo Teixeira is an Assistant Professor at the Informatics Center (CIn) of the Federal University of Pernambuco, where he leads the Software Testing and Analysis Research group. He is also affiliated with the Software Productivity Group and CIn-Trust. Since May 2023, he has served as head of graduate studies at his department. His educational background includes: PhD in Computer Science from the Federal University of Pernambuco (CIn-UFPE) in 2014, supervised by Paulo Borba and Rohit Gheyi MSc in Computer Science from CIn-UFPE in 2010 Bachelor's degree in Computer Engineering from the Polytechnic School of Pernambuco in 2007 During his PhD, he spent a winter term at the University of Waterloo working with Krzysztof Czarnecki. In 2022, he was a CAPES-Alexander von Humboldt Experienced Research Fellow at the Chair of Software Engineering of Universität des Saarlandes, working with Sven Apel on variability analysis over time and space. His research focuses on Software Engineering with emphasis on improving software quality and productivity. His work spans software product lines, configurable systems, refactoring, formal methods, software testing, and mobile development. His publication record shows a consistent focus on software analysis, testing, and maintenance, with recent work exploring Dockerfile repair and flaky test detection. His scientific recognition includes the CAPES-Alexander von Humboldt Experienced Research Fellowship in 2022. As an active member of the software engineering research community, he has served on program committees for numerous conferences including ASE, ICSE, ESEC/FSE, and others across multiple years. Leopoldo leads the Software Testing and Analysis Research group at CIn-UFPE and is affiliated with the Software Productivity Group and CIn-Trust, indicating a strong institutional presence and collaborative research environment.

• Software Engineering
• Software Product Lines
• Configurable Systems
• +۷ مورد دیگر