Christian Kästner

Christian Kästner is an Associate Professor in the Software and Societal Systems Department (S3D) within Carnegie Mellon University's School of Computer Science, where he also serves as the director of the CMU Software Engineering Ph.D. Program. His work bridges software engineering and machine learning, focusing on the practical challenges of building production systems with ML components.

His research spans several interconnected areas: software engineering for AI-enabled systems (particularly "Machine Learning in Production"), sustainability and fairness in open source communities, and software-supply-chain security. He investigates the limits of modularity and complexity caused by variability in software systems, with applications in quality assurance, interoperability, and feature interactions. His approach combines rigorous empirical research with program analysis and tool building.

His recent publications reveal a strong trend toward ML systems engineering, with numerous papers on building reliable ML products, understanding open source sustainability challenges, and securing software supply chains. His work often involves large-scale empirical studies and the development of practical tools to address real-world software engineering problems.

He has received multiple distinguished paper awards at top software engineering conferences including ICSE and FSE for his work on dependency abandonment, supply chain security, and collaboration challenges in ML systems.

As an educator, he created and teaches the "Machine Learning in Production" course, which formed the basis for his MIT Press book of the same name. He has advised numerous PhD students and mentored many REU students, with several former students now holding faculty positions or working at major tech companies.

His service to the community includes extensive program committee work for major software engineering conferences and editorial roles, demonstrating his significant influence in the field.