Mohamad Kassab

Mohamad Kassab is an Associate Professor of the Practice of Computer Science at Boston University. His research advances empirical software engineering, with a focus on requirements engineering, software architecture, software quality, and large-scale software practices. He is particularly known for developing data-driven methods to assess and improve requirements and architectures, and for creating empirical frameworks that connect design decisions and quality outcomes across the lifecycle. A central thrust of his recent work is the integration of artificial intelligence into software engineering workflows—including multi-LLM approaches for requirements completeness analysis, defect taxonomies and verification strategies for AI-intensive systems, and empirical studies of how AI-driven techniques reshape software engineering practices. Before joining BU, Kassab spent 12 years at Penn State University as Associate Professor of Software Engineering, where he designed and delivered graduate courses, supervised numerous graduate students, and led collaborative research programs on software engineering and emerging technologies.

Kassab earned his Ph.D. in Computer Science from Concordia University in Montreal in 2009. He has authored more than 150 peer-reviewed publications in leading software engineering conferences and journals, and his textbooks and reference works are widely used in both academia and industry training programs. He serves on the editorial boards of several journals and magazines and is an active contributor to program committees of premier international venues.

He has held visiting appointments at institutions including Carnegie Mellon University, NYU Abu Dhabi, Concordia University, École de technologie supérieure (ÉTS), and the University of Twente, collaborating on research and curriculum development in software engineering.

Before his academic career, Kassab accumulated over two decades of industry experience, holding leadership and consultancy roles at Nokia, SAP, Morgan Stanley, McKesson, Positron Public Safety Systems, and Soramitsu. In these capacities, he guided large-scale initiatives across mobile platforms, enterprise applications, financial systems, and blockchain solutions. These professional experiences continue to inform his research agenda and reinforce his commitment to bridging theory and practice in software engineering.

Selected Publications:

• Laplante, P., & Kassab, M. (2022). Requirements Engineering for Software and Systems (4th ed.). Auerbach Publications.
• Kassab, M., & AbdElhameed, M. (2025). Detecting and repairing incomplete software requirements with multi-LLM ensembles. In Proceedings of the 40th IEEE/ACM International Conference on Automated Software Engineering (ASE 2025), New Ideas and Emerging Results Track.
• Kassab, M. (2025). An Empirical Study of Faculty and Postdoctoral Roles. Proceedings of the ACM International Conference on the Foundations of Software Engineering (FSE 2025), Software Engineering Education Track.
• Veríssimo, M., Kassab, M., Galvão, A., Graciano Neto, V. V., & Oliveira Jr., E. (2025). “Is It Responsible?” Emerging results on comparing guardrails for harm mitigation in LLM-enhanced software applications. In Proceedings of the 19th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM 2025), Emerging Results, Vision and Reflection Papers Track.
• Kassab, M. (2026). Prompt engineering patents in software development: Trends, themes, and future directions. In Proceedings of the Hawaii International Conference on System Sciences (HICSS).
• Manzano, W., Graciano-Neto, V. V., Bianchi, T., Kassab, M., & Nakagawa, E. Y. (2025). Simulation of system architectures using optimization and machine learning: The state of the art and research opportunities. Journal of Software and Systems Modeling, 1–22.
• Laplante, P., DeFranco, J., Kuhn, R., Voas, J., & Kassab, M. (2024). Proxy validation and verification for critical AI systems. NIST Cybersecurity White Paper (CSWP 31).
• Kassab, M., & Laplante, P. (2022). The current and evolving landscape of requirements engineering in practice. IEEE Software, 39(5), 76–83.