We advance SE with insight-driven design to build software that redefines what’s possible.
The paper was published online in Software and Systems Modeling on August 18, 2026. Online access to this article has been shared by the author(s) via Springer Nature SharedIt, and the full text is freely accessible through the link below.
WSELab pioneers advancements in classical and quantum software engineering by integrating cutting-edge techniques—including AI, large language models (LLMs), and evolutionary computing—across every stage of software development.
Integrating uncertainty modeling, quantification and mitigation across the software lifecycle—modeling, testing, and evolution—to enable resilient software systems that thrive in dynamic environments.
Developing principles, methodologies, and tools to design, implement, test, and optimize software for quantum and hybrid quantum-classical systems.
Utilizing precise digital models to enhance efficiency, consistency, and automation in software system development.
Harnessing advanced AI techniques to streamline testing processes, ensuring robust quality and adaptive performance across diverse software landscapes.
Applying both classical and quantum optimization techniques to enhance software performance, efficiency, and decision-making in complex engineering problems.
Explore our key research areas where we're making significant contributions.
Transforming models—spanning prior knowledge systems, machine learning frameworks, and more—into dynamic, context-aware collaborators.
Learn MoreAdvancing model-driven engineering and managing uncertainty in intelligent software systems across modeling, testing, and evolution.
Learn MoreExploring quantum, quantum-inspired, and hybrid computing approaches for solving complex software engineering problems.
Learn MoreGenerating and executing test case specifications dynamically, through continuous interaction with the autonomous driving system and its environment.
Learn MoreMeet the researchers and students who make our work possible.
Full Professor
Builts years of experience in SE research, tackling complex challenges and developing practical solutions.
Associate Professor
Specializes in software testing for complex software/system with a focus on AI-based techniques.
PhD. Student
Participated in ModelCopilot's backend development, focusing on model syntax parsing and semantic validation.
PhD. Student
Participated in ModelCopilot's backend development, focusing on explainable AI and model validation techniques.
PhD. Student
Participated in ModelCopilot's frontend development, focusing on UI design and interface layout.
PhD. Student
Participated in ModelCopilot's backend development, focusing on model syntax parsing and semantic validation.
M.Eng. Student
Participated in ModelCopilot's backend development, focusing on model syntax parsing and semantic validation.
M.Eng. Student
Participated in ModelCopilot's backend development, focusing on model syntax parsing and semantic validation.
M.Eng. Student
Participated in ModelCopilot's backend development, focusing on model visualization.
M.Eng. Student
Participated in ModelCopilot's backend development, focusing on model visualization.
M.Eng. Student
Participated in ModelCopilot's frontend development, focusing on UI design and interface layout.
M.Eng. Student
M.Eng. Student
M.Eng. Student
M.Eng. Student
M.Eng. Student
M.Eng. Student
M.Eng. Student
M.Eng. Student
M.Eng. Student
M.Eng. Student
B.Eng. Student
B.Eng. Student
Scholars and students collaborating with us from institutions around the world.
Visiting Student
