Keynote Speaker I
Prof. Hironori Washizaki
Waseda University, Japan
Title: SWEBOK Guide and AI-empowered Software Engineering
Abstract: The IEEE Computer Society has been strategically providing activities and products related to emerging technologies and professional and educational activities, including Technology Predictions and the Guide to the Software Engineering Body of Knowledge (SWEBOK Guide). This talk first explains the latest version of the Technology Predictions 2026, which foresees 26 breakthrough technologies (incl. AI and Future of Work and Future of Coding) to shape the future of our world for decades to come, and the SWEBOK Guide V4, which reflects contemporary engineering paradigms and emerging areas, including Agile and DevOps, software architecture, security, and AI. Then, as part of AI and SE, the talk provides an overview of Generative and Agentic AI-empowered software engineering, including LLM-supported requirements engineering, software architecting, coding agents, and software security engineering. The talk highlights how these approaches align with and extend the evolving body of knowledge represented in SWEBOK, pointing toward the future of AI-augmented software engineering.
Bio: Hironori Washizaki is a Professor and the Associate Dean of the Research Promotion Division at Waseda University in Tokyo and a Visiting Professor at the National Institute of Informatics. He also works as an Outside Director of eXmotion. He is the immediate past president of the IEEE Computer Society. He has led software engineering research and ICT professional and educational activities, including the development of IEEE-CS's Guide to the Software Engineering Body of Knowledge (SWEBOK Guide). He has led many academia-industry joint research projects and large-scale funded projects in software design, reuse, traceability, quality assurance, and machine learning engineering. Recent achievements include IoT design patterns and machine learning design patterns. He leads a professional IoT/AI/DX education project called SmartSE.
http://www.washi.cs.waseda.ac.jp/washizaki/
Keynote Speaker II
Prof. Lei Ma
University of Tokyo, Japan
Title: Assuring the Trustworthiness of LLM-Based Agentic AI Systems
Abstract: Recent advances in data-driven, AI-enabled systems have accelerated the development of intelligent applications across diverse domains. Large foundation models have further fueled this progress, serving as the backbone of increasingly capable agentic AI systems. Yet the growing complexity of these systems, coupled with their reliance on a small number of foundation models, presents new challenges for ensuring their trustworthiness. In this talk, I will provide a high-level overview of our ongoing exploratory research on assuring the trustworthiness of LLM-based agentic AI systems. I will discuss key challenges and emerging opportunities, outlining directions for future research and pathways to translating research advances into practical value for industry.
Bio: Lei Ma is currently an Associate Professor at the University of Tokyo, and shares his time with University of Alberta. His research focuses on trustworthy artificial intelligence (AI) and software engineering, with particular emphasis on interdisciplinary approaches to quality and reliability assurance, as well as the interpretability and analysis of intelligent software systems. Lei’s work has been published in numerous leading international conferences and journals in software engineering and AI, receiving 4 ACM SIGSOFT Distinguished Paper Awards (ASE 2015, ASE 2018, ASE 2019, FSE 2023), as well as the IEEE Transactions on Software Engineering Annual Best Paper Award for 2022. In recognition of sustained contributions to reliability assurance for data-driven software systems, he received the IEEE TCSE New Directions Award in 2025.
Invited Speaker I
Prof. Hirohisa Aman
Ehime University, Japan
Title: Impact of Human Factors on Code Quality: Comments and Variable Names
Abstract: Readable and understandable source code is
essential for effective software quality management, yet some practices that
are usually considered beneficial can have unexpected side effects.
In particular, comments and variable names are closely tied to how
developers read, interpret, and review code.
While well-written comments can support comprehension, they may also mask
underlying code smells and sometimes signal deeper design or implementation
problems.
Similarly, descriptive variable names can clarify intent, but when names
become long or visually similar—such as "lineIndent" and "lineIndex"—they
may increase the risk of confusion during programming and code review.
This talk will present empirical studies on these human-related factors and
discuss how comments and variable names influence code quality.
Bio: Hirohisa Aman is a Professor at the
Center for Information Technology, Ehime University, Japan.
He received his B.E., M.E., and Doctor of Engineering degrees from Kyushu
Institute of Technology, Japan, in 1996, 1998, and 2001, respectively.
His research interests include software metrics, software testing, empirical
software engineering, and human factors in software engineering.
He serves as a board member of JSSST, is a Senior Member of IEEE, and is a
member of IPSJ and IEICE.
He is currently serving as Program Co-Chair of the 3rd International
Symposium on Software Fault Prevention, Verification, and Validation (SFPVV
2026).
Invited Speaker II
Prof. Akito Monden
Okayama University, Japan
Title: Rethinking Software Engineering Research in the AI-Driven Era
Abstract: Generative AI and autonomous AI agents are rapidly changing software development. As AI increasingly takes over coding and other implementation tasks, the bottlenecks of software development may shift toward requirements, context, verification, operation, and ultimately the creation of value for users. These changes also raise a fundamental question for the software engineering community: what should we study when AI does much of the coding?
In this talk, I will first discuss recent changes in industrial software development and software business, including the growing use of AI agents, the changing role of software engineers, and the increasing importance of quality assurance and value creation. I will then discuss how these changes may affect traditional software engineering research and create new research opportunities. Drawing on examples from our own ongoing and completed studies, I will illustrate our attempts to shift research toward AI-assisted requirements engineering, analysis of AI-driven development practices, AI-based software testing, and software protection in the age of generative AI.
Bio: Akito Monden is a professor in the Faculty of Environmental, Life, Natural Science and Technology at Okayama University, Japan. He received his B.E. degree from Nagoya University and his M.E. and D.E. degrees from Nara Institute of Science and Technology (NAIST). His research interests include software measurement and analytics, software protection, and AI-assisted software engineering. He has recently served as Conference Chair of Software Symposium 2025, WSSE2025, and SNPD2026.
