About the talk
Software engineering has evolved over decades into a well-defined discipline with established practices for reliability,
testing, design and maintenance, and it continues to improve as systems grow in scale and complexity. Research or science
software engineering builds on these foundations but operates in a context where requirements shift with new discoveries,
where code often embodies scientific models, and where correctness is tightly coupled to experiment and interpretation.
RSE adds further challenges to the complexities of SE: code must adapt as science advances, experiments must be reproducible,
data workflows can be immense, and performance and sustainability matter as much as correctness.
AI is now disruptive across many domains, and it is reshaping software engineering itself by changing how we write, test,
optimise and reason about code. In this keynote we synthesize these trends through a clear quadrant framework comparing SE
and RSE with their AI-supported counterparts, illustrating how AI assists development tasks, accelerates research pipelines,
supports documentation and testing, and even helps generate scientific insight. Attendees will leave with a structured understanding
of how AI is transforming research software engineering, what skills and practices are becoming more important, and how to actively
shape a future where human expertise and AI capability work together.
Bio
Professor Tekinerdogan is a computer scientist with over 25 years of experience in software/systems
engineering and information technology. He earned both his MSc (1994) and PhD (2000) in Computer Science
from the University of Twente, The Netherlands.
He has held academic positions at the University of Twente and Bilkent University, where he founded and led
the Bilkent Software Engineering Group. He is currently a full professor and chair of the Information
Technology group at Wageningen University. He has authored more than 400 peer-reviewed publications,
edited multiple books, and led numerous national and international research and consultancy projects in domains
such as consumer electronics, enterprise systems, automotive, critical infrastructures, cyber-physical systems,
satellite systems, energy systems, precision farming, and more.
His expertise spans software and systems architecture, software product line engineering, cyber-physical systems,
model-driven development, aspect-oriented software engineering, global software development, data science, and AI.
He has extensive experience as an educator and industrial trainer, and has supervised many MSc and PhD students.
