The widespread adoption of generative AI is fundamentally changing software engineering. AI is no longer merely a development assistant but an integral component of the software engineering lifecycle, influencing requirements elicitation, design, implementation, testing, deployment, and maintenance. Despite the rapid adoption of AI-powered development tools, organizations continue to rely on ad hoc practices and fragmented workflows, with limited evidence regarding their effectiveness, reliability, and long-term sustainability. There is an increasing need for systematic engineering methodologies, standardized development processes, evaluation frameworks, and best practices that enable the development of robust, trustworthy, and maintainable AI-native software systems.

This special session aims to bring together researchers and practitioners working on the emerging foundations of AI-native software engineering, with emphasis on evidence-based methodologies, engineering processes, empirical studies, and industrial experiences that advance the maturation of AI-assisted software development.

Topics of interest include, but are not limited to:

• AI-native software engineering methodologies and frameworks
• AI-assisted software development processes and workflows
• AI-driven requirements engineering
• AI-assisted software architecture and design
• AI-supported testing, verification, and validation
• Code quality and maintainability of AI-generated software
• Human-AI collaboration in software engineering
• Metrics and empirical evaluation of AI-assisted development
• AI governance, trustworthiness, and security
• Industrial case studies and best practices
• Standards, guidelines, and engineering frameworks for AI-native software development

The session seeks to synergise software engineering principles with AI-driven approaches to address emerging challenges of engineering software-intensive systems and provide a forum for disseminating results and building a community of research on AI for SE.

Submission Link: https://www.zmeeting.org/submission/icsie2027

Please Select Track: Special Session 1 to Submit

 

Organizer

Dr Sokratis Karkalas
University of Derby

Email: s.karkalas@derby.ac.uk
Research Areas: Educational Technology, Computer Programming Education, Intelligent Tutoring Systems, Exploratory Learning Environments, Learning Analytics, Learning Platform Architecture, Educational Software Engineering, Interoperability and Integration, AI in Education

Dr. Sokratis Karkalas has been working at the intersection of industry and education since 1991. He holds degrees in economics, business administration, computer science, and pedagogy. Currently, he is a Senior Lecturer in Software Engineering at the University of Derby, where he heads the Education and AI Research Group. He also serves as a Visiting Research Fellow at the UCL Knowledge Lab, University of London.
Dr. Karkalas earned his PhD in Computer Science from the University of London, where he was awarded the Best PhD Project Award by INSTICC (Institute for Systems and Technologies of Information, Control and Communication) in 2015. He is an accredited TOGAF Enterprise Architect, a member of the Association of Enterprise Architects (UK), an Associate Fellow of the Higher Education Academy (UK), and a member of the British Computer Society – The Chartered Institute for IT.
Prior to his academic career, Dr. Karkalas held the position of Group Chief Information Officer (CIO) for a multinational industrial group and worked as a senior / lead software engineer and project architect at major consulting firms. In these roles, he led the design and development of prototypes for R&D departments. He has contributed to numerous research projects - academic and industrial - funded by the EU, local governments (ESRC/EPSRC), and the private sector.
With over 25 years of academic experience, including 20 years at leading UK universities, Dr. Karkalas' research focuses on computer-supported education, particularly the application of artificial intelligence to improve learning. He applies machine learning techniques to provide personalized support to both students and educators. Dr. Karkalas also has extensive experience designing and implementing information systems for educational and industrial applications, as well as working on technologies that enable the semantic enhancement, integration, and interoperability of diverse components within learning platforms.

Co-organizers

Dr. Aakash Ahmad
University of Derby, UK
Email: a.abbasi@derby.ac.uk
Research Areas: Software Architecture, Software Engineering, Service Computing, Empirical Software Engineering

Dr. Aakash Ahmad is a Senior Lecturer in Software Engineering at the University of Derby, UK. His research focuses on software engineering, with expertise in software architecture and AI-enabled software engineering. His work advances architecture-centric methods, engineering processes, and AI-assisted techniques for developing and evolving complex software systems. He has served as Principal Investigator on funded research projects and as a technical consultant on industry-funded collaborations, leading the development of methods, tools, and software architectures for software-intensive systems. Previously, he served as Director of the Doctoral Programme at Lancaster University Leipzig, Germany.
Aakash has authored over 80 peer-reviewed publications in leading software engineering venues, including IEEE TSE, IEEE/ACM ICSE, and JSS. His work has received over 3,800 citations (h-index 32) and multiple Best Paper Awards at FICS 2025, SEAMS 2024, and SEKE 2023. He has delivered keynote talks at international venues, including IWSA 2025 (co-located with ECSA) and LEiSYS 2026 on AI for software architecting. He has served as Executive Guest Editor, Associate Editor, and Editorial Board Member for journals, and contributes to the software engineering community through leadership roles as General Chair, Workshop Chair, and Program Committee member.

Assoc. Prof. Hong Qing (Harry) Yu
University of Derby, UK
Email: h.yu@derby.ac.uk
Research Areas: Knowledge representation, Agentic AI, Service Computing, Computer Vision

Dr Hongqing (Harry) Yu is an Associate Professor (Reader) in Data Science at the University of Derby, where he leads the MSc Computing portfolio, chairs the Postgraduate Teaching Committee, and directs the Digital Society Research Cluster. His research spans agentic AI systems, digital twins, large-scale data integration, retrieval-augmented generation, and knowledge-graph-driven reasoning. He has an established international research profile with 80+ published research papers, reflecting sustained contributions across AI, data science, and computational healthcare. Dr Yu has served as Principal Investigator and Co-Investigator on numerous UKRI, Innovate UK, EMIZ, industry, and EU FP6/FP7/H2020 projects, producing impactful AI solutions for aerospace, manufacturing, healthcare, rail inspection, and finance. He is the CEO and Co-founder of LucenAI Ltd, a University of Derby spin-out built on his research into enterprise knowledge memory and agentic AI. He also serves as a Visiting Professor at multiple EU research institutions on EC-funded collaborations, and as External Examiner for AI and Computer Science MSc programmes at the University of Law, London. Dr Yu has supervised over a dozen PhD researchers, many industry-funded, and contributes extensively to the academic community through editorial board roles, conference chairing, keynote talks, and best-paper-award-winning publications.