جست‌وجوی استاد و پژوهشگر

Arie van Deursenمشاهده پروفایل

استاد

• Software Engineering
• Software Testing
• Trustworthy AI
• +۵ مورد دیگر

Arie van Deursen is a Professor in Software Engineering at Delft University of Technology, where he is affiliated with the Department of Software Technology within the Faculty of Electrical Engineering, Mathematics, and Computer Science (EEMCS). He previously served as head of department from 2016-2023 and currently chairs the Software Engineering Research Group (SERG). He is also the scientific co-director of AI4SE, a five-year collaboration between JetBrains and TU Delft investigating novel uses of artificial intelligence in software engineering. His research interests span software engineering, software testing, trustworthy AI, language models for code, software architecture, human aspects of software engineering, and digitalization in the financial and public sector. His work often bridges academic research with practical industry applications, as evidenced by his co-founding of two companies: The Software Improvement Group (2000) and PerfectXL (2010/2013). Recent publications show a strong focus on large language models in software engineering contexts, with multiple 2024-2025 papers examining code generation quality, multilingual code comments, contamination-free code datasets, and license infringement concerns in LLM training data. His research demonstrates significant engagement with the challenges and opportunities presented by AI in software development. AIWare 2024 ACM SIGSOFT Distinguished Paper Award ASE 2024 ACM SIGSOFT Distinguished Paper Award CAIN 2023 Distinguished Paper Award CSCW 2015 ACM SIGCHI Best Paper Award EASE 2016 Best Paper Award Professor van Deursen has (co-)supervised 50 PhD students and 100 MSc students throughout his career. He serves on the Advisory Council on IT Assessment (AcICT) of the Dutch government (since 2022) and the Advisory Board of ING Bank Netherlands (since 2024). He was elected as a fellow of the Netherlands Academy of Engineering (NAE) in 2023. He leads the AI4SE lab, which hosts 10 PhD students, dozens of MSc and BSc students, and collaborates with many TU Delft faculty members and JetBrains specialists. The lab focuses on investigating novel uses of artificial intelligence in software engineering, with particular attention to practical applications and industry relevance.

Jim Buckleyمشاهده پروفایل

استاد

• Software Engineering
• Software Evolution
• Artificial Intelligence for Software Engineering
• +۵ مورد دیگر

Jim Buckley is a Professor in the Computer Science and Information Systems Department at the University of Limerick, Ireland, and a Principal Investigator in Lero. He leads the ARC research group focused on software evolution and legacy system modernization, with significant industry collaborations including Huawei, IBM, and Fidelity. Education: BSc in Biochemistry, University of Galway (1989) MSc in Computer Science, University of Limerick (1994) PhD in Computer Science, University of Limerick (2002) Research Focus: His work centers on AI-enhanced software engineering (AI4SE/SE4AI), featuring breakthroughs in clone detection, software architecture evaluation, and feature location. He has developed industry-adopted tools for software comprehension and evolution, with recent emphasis on explainable AI (XAI) and scalable neural network applications for industrial codebases. His research consistently bridges academic rigor with industrial implementation. Publication Trends: Recent articles (2022-2025) reveal a dominant shift toward AI-driven software engineering solutions, particularly in clone detection and architecture recovery. Key themes include industrial scalability, developer experience optimization, and responsible AI integration, with strong representation in top-tier venues like IEEE Transactions and ACM Computing Surveys. Scientific Awards: No awards specified in source material. Grants & Industry Impact: Leads the Huawei-funded TREES Programme and maintains active partnerships with 9+ companies. His research has yielded licensed tools (e.g., for legacy system evolution), two IP assignments from LLM-based clone detection work, and practical frameworks adopted by seven Irish enterprises. Research Infrastructure: Directs the ARC group within Lero, which combines academic researchers and industry practitioners to address real-world software maintenance challenges through empirical studies and tool prototyping.

Zhou Yangمشاهده پروفایل

استادیار

• Software Engineering
• Artificial Intelligence
• AI for Software Engineering
• +۳ مورد دیگر

Zhou Yang is an Assistant Professor at the University of Alberta and Fellow at the Alberta Machine Intelligence Institute (Amii), with research focusing on the intersection of software engineering and artificial intelligence. His academic journey includes a Ph.D. from Singapore Management University, an M.Sc. in Software System Engineering from University College London, and undergraduate studies at Yangzhou University. His research interests span Software Engineering, Artificial Intelligence, AI for Software Engineering (AI4SE), Software Engineering for AI (SE4AI), Large Language Models, and Cybersecurity. Yang's work explores how human and AI collaboration can improve code writing, how AI impacts open-source communities, and how developers build software in emerging environments like VR/AR. His recent publications demonstrate strong trends in code language models, with significant contributions to ASE, ICSE, ISSTA, and top journals like TOSEM and TSE. His research addresses critical challenges including token efficiency in code generation, user perception of AI coding assistants, privacy preservation in code models, and fairness in AI systems. 2024 IEEE Computer Society Best Paper Award (1 out of 183 submissions) ACM Distinguished Paper Award from ISSTA 2024 Distinguished Reviewer Award from Internetware 2024 SMU Research Staff Excellence Award (1 of 4 university-wide) SMU Presidential Fellowship Award SMU Dean's List Award 1st Place in ACM Student Research Competition at ICSE 2024 Yang actively mentors graduate students with regular one-on-one meetings, constructive feedback, and support for top-venue publications. He provides full funding through teaching assistantships and research grants, including travel support for conferences. His lab focuses on responsible research conduct and societal implications of AI work. Though early-career, he actively builds professional networks for students through collaborations and supports diverse career paths in academia and industry. He leads research in the Alberta Machine Intelligence Institute, focusing on practical applications where software engineering principles enhance AI systems and where AI techniques solve real-world software engineering challenges.

Zhongxin Liuمشاهده پروفایل

استادیار

• Intelligent Software Engineering
• AI for Software Engineering
• Code Intelligence
• +۵ مورد دیگر

Zhongxin Liu is a Distinguished Research Fellow (Assistant Professor) and Doctoral Supervisor at the College of Computer Science and Technology, Zhejiang University. He received his Ph.D. from Zhejiang University under the supervision of Prof. Shanping Li. His research focuses on intelligent software engineering (AI4SE), particularly using AI to help developers understand, write, change, and test code through learning from software "big data". His educational background includes: Ph.D. in Computer Science, Zhejiang University (2016-2021) Dr. Liu's research interests center around intelligent software engineering with emphasis on code intelligence, program analysis, and software testing. His work leverages machine learning, particularly large language models, to solve challenging problems in software development including code generation, bug localization, and test case generation. He has made significant methodological contributions to the field through his innovative approaches to understanding and improving the software development lifecycle. His recent publications (2024-2026) demonstrate a clear trend toward leveraging large language models for software engineering tasks, with particular focus on code generation, fault localization, and program analysis. The research spans multiple domains including vulnerability detection, smart contract development, and cross-domain code search, showing how AI can enhance traditional software engineering practices. Dr. Liu has received numerous prestigious awards for his contributions: ACM SIGSOFT Distinguished Paper Award (ISSTA 2025, ASE 2018-2020) Distinguished Paper Award (APSEC 2023) Zhejiang University Education Foundation Qizhen Scholar (2021) Distinguished Doctoral Thesis of Zhejiang University (2021) As a Doctoral Supervisor at Zhejiang University, Dr. Liu mentors graduate students in intelligent software engineering. He serves on program committees for major conferences including ICSE, ASE, and FSE. His research group actively recruits undergraduate interns, graduate students, and postdocs to work on code intelligence projects. Dr. Liu is also scheduled to be a Visiting Professor at the University of Stuttgart from October 2024 to January 2025. Dr. Liu leads a vibrant research group at Zhejiang University focused on advancing AI-powered tools for software development. His work bridges theoretical advances in machine learning with practical applications in software engineering, creating novel solutions that help developers be more productive and produce higher quality code.

Masud Rahmanمشاهده پروفایل

دانشیار

• Software Engineering
• Artificial Intelligence for Software Engineering (AI4SE)
• Software Maintenance and Evolution
• +۱۱ مورد دیگر

Masud Rahman is an Associate Professor in the Faculty of Computer Science at Dalhousie University, Canada, where he leads the RAISE Lab. Previously a tenure-track Assistant Professor, he completed his Ph.D. in Computer Science/Software Engineering from the University of Saskatchewan and a postdoctoral fellowship at Polytechnique Montreal. His academic career demonstrates strong progression with significant research impact in software engineering. Faculty of Computer Science, Dalhousie University (Current) University of Saskatchewan (Ph.D. studies) Polytechnique Montreal (Postdoctoral research) Dr. Rahman's research focuses on the intelligent automation of software maintenance and evolution, particularly targeting software debugging, code search, and code reviews. His work strategically combines Software Engineering with Artificial Intelligence techniques including Machine/Deep Learning, Information Retrieval, Mining Software Repositories, and Natural Language Processing. His industry experience as a professional developer for three years significantly shaped his research direction toward solving practical software maintenance challenges that cost the global economy billions annually. His research program addresses critical problems in software bug detection, diagnosis, explanation, and reproduction, with increasing focus on AI-powered and simulation modeling software. His publications demonstrate consistent output in top-tier venues including 7 papers at ICSE (A*), 3 at FSE (A*), 3 at ASE (A*), 8 at EMSE (A), 6 at ICSME (A), and 9 at MSR (A). The research trends show increasing focus on deep learning applications for software engineering problems, with particular attention to code search, bug localization, and debugging automation. His work has evolved from traditional information retrieval approaches to incorporate advanced neural network techniques and generative AI. Governor General's Gold Medal 2019 U of S Doctoral Thesis Award 2019 CS Best PhD Thesis Award 2019 TCSE Distinguished Paper Award Most Influential Paper Award Dr Keith Geddes Award Dalhousie Belong Research Fellowship President's Gold Medal (Bangladesh) Dr. Rahman has secured $500K+ in competitive research funding as Principal Investigator, including an NSERC Discovery Grant, Mitacs Accelerate International, and Climate Action and Awareness Fund. He actively collaborates with industry partners including Metabob Inc., Mozilla Firefox, and Vendasta Technologies. His service to the community includes extensive program committee work for major conferences and journal reviewing. He leads the RAISE Lab, which focuses on developing AI-powered solutions for software maintenance challenges, with current projects emphasizing sustainable software innovation and sustainable AI as part of Dalhousie's strategic goals.