Muhammad Azeem Akbar

Muhammad Azeem Akbar is an Associate Professor in the Software Engineering Department at LUT University, Finland, with a multidisciplinary research focus on integrating software engineering with large language models (LLMs), data analytics, artificial intelligence, and emerging technologies. He earned his Ph.D. in Software Engineering from Chongqing University, China, in 2019, followed by postdoctoral research at Nanjing University of Aeronautics and Astronautics and LERO – The Irish Software Research Centre. His career includes contributions to projects like the Automated Code Recommendation System, Huawei’s Software Trustworthiness initiative, and leadership in the 6GSoft project funded by Business Finland.

• Current position: Associate Professor, LUT School of Engineering Sciences
• Education: Ph.D. in Software Engineering (Chongqing University, 2019)

His research spans three core areas:

• Software Engineering: Specializing in software process improvement, requirements engineering, change management, DevOps/DevSecOps, and global software development. He has developed maturity models, decision-support frameworks, and prioritization taxonomies to enhance software efficiency.
• AI and LLMs in Software Engineering: Focused on AI-driven code recommendation, defect prediction, test case generation, and requirements analysis. His work also examines ethical implications and trustworthiness of AI tools, including generative AI like ChatGPT.
• Emerging Technologies: Pioneering research at the intersection of software engineering with quantum computing, 6G, blockchain, IoT, and MLOps. He has proposed predictive models for quantum software development and secure frameworks for blockchain-enabled DevOps.

Notable projects include the €3.2 million Code Recommendation System Improvement (China), €1.5 million Towards Zero-Touch Testing (Jiangsu-Nanjing), and contributions to EU Horizon proposals. He has published over 125 articles and collaborates with institutions like Huawei, King Saud University, and EU consortia.

His teaching and research emphasize empirical and evidence-based approaches to address real-world challenges in modern software systems, with a focus on human-AI collaboration, cybersecurity, and smart cities.