PeopleofSuperintelligence

Researcher

Christian Kästner

Also known as Christian Kaestner

Christian Kästner is a software engineering researcher at Carnegie Mellon University who studies how to build, test and operate production software that contains AI components. He earned a doctorate at the University of Magdeburg and received the 2011 prize for the best computer science dissertation in the German-speaking region, then moved from Marburg to Carnegie Mellon's faculty in 2012. TypeChef, a tool from his group, could typecheck its target subsystem of the Linux kernel in 2013, and the NSF awarded him a CAREER grant in 2016. After starting the Machine Learning in Production course in 2019, he received a Distinguished Paper Award at ICSE 2022 for a study of collaboration in ML-enabled systems and published the MIT Press textbook Machine Learning in Production in 2025. He is an associate professor who directs the CMU Software Engineering Ph.D. program and works on AI engineering and software supply-chain security.

Born
1982

Years link to their sources.

Timeline

  1. 2011

    Best computer science dissertation

    As a researcher at Philipps University Marburg, he receives the 2011 prize for the best computer science dissertation in the German-speaking region, presented at the annual meeting of the Gesellschaft für Informatik. It honors his Magdeburg doctoral thesis, "Virtual Separation of Concerns: Toward Preprocessors 2.0".

  2. 2012

    Faculty position at Carnegie Mellon

    In August 2012, he moves from Marburg, Germany, to Pittsburgh to start a faculty position at Carnegie Mellon University.

  3. 2013

    TypeChef and the Linux kernel

    TypeChef 0.3.4, released in March 2013, is able to typecheck the entire subsystem of the Linux kernel that the project targets. The tools built in his group for configurable software, including CIDE and TypeChef, are adopted widely in the research community.

  4. 2016

    An NSF CAREER award

    In 2016, the NSF awards him a CAREER grant for his work on variational execution and understanding feature interactions.

  5. 2019

    Machine Learning in Production course

    In 2019, he starts co-teaching a new course, Machine Learning in Production, at the intersection of software engineering and machine learning. His later research covers collaboration, documentation, and quality assurance in teams where software engineers and data scientists interact.

  6. 2022

    A distinguished paper on ML teams

    At ICSE 2022, his paper with Nadia Nahar, Shurui Zhou and Grace Lewis, "Collaboration Challenges in Building ML-Enabled Systems: Communication, Documentation, Engineering, and Process", receives a Distinguished Paper Award. It draws on interviews with 45 practitioners from 28 organizations about collaboration challenges in building and deploying ML systems.

  7. April 2025

    The Machine Learning in Production book

    MIT Press publishes his textbook Machine Learning in Production: From Models to Products in April 2025. The book covers the lifecycle from a prototype ML model to a system deployed in production, including responsible AI and MLOps, and all author royalties go to Evidence Action.

  8. As of October 2026

    Associate professor at Carnegie Mellon

    He is an associate professor in the School of Computer Science at Carnegie Mellon University, in the Software and Societal Systems Department, and directs the CMU Software Engineering Ph.D. program. His interests are AI engineering, open-source sustainability and software supply-chain security.

Career

  1. NowCarnegie Mellon UniversityAssociate Professor
  2. Philipps University of MarburgResearcher

Education

  1. Otto-von-Guericke-Universität MagdeburgPhD

From the biography.

  1. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionIncludes Carnegie Mellon University. We estimate where the people shaping AI studied and where their careers led. Massachusetts Institute of Technology leads with 467 former students, including 291 recorded doctorates.
  2. The company share of AI researchers’ top papers was 31% in 2020–2024 and 8% in 1970–1974Includes Carnegie Mellon University. We estimate where the people shaping AI worked when their most-cited papers appeared: the company share was 31% in 2020–2024 and 8% in 1970–1974, and Google led all organizations in 2020–2024.
  3. Google has the highest combined h-index among AI organizationsIncludes Carnegie Mellon University. We estimate that Google holds the highest combined h-index at 8,016, while universities account for 73% of the deduplicated total across AI organizations.
  4. The median h-index is 48 at universities and 14 at frontier AI labsIncludes Carnegie Mellon University. The median h-index is 48 at universities and 14 at frontier AI labs. We compare publishing careers, recent citations, dual appointments and job moves across 2,420 university researchers and 308 frontier-lab researchers.

Sources and credits

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  1. Beste Informatikdissertation im deutschsprachigen Raum uni-marburg.de. Checked 21 October 2026.
  2. Christian Kästner :: News :: CMU cs.cmu.edu. Checked 21 October 2026.
  3. Christian Kästner :: CMU cs.cmu.edu. Checked 21 October 2026.
  4. MSR 2022 - Keynotes - MSR 2022 conf.researchr.org. Checked 21 October 2026.
  5. Christian Kästner :: Publications :: CMU cs.cmu.edu. Checked 21 October 2026.
  6. Cover - Machine Learning in Production: From Models to Products mlip-cmu.github.io. Checked 21 October 2026.
  7. Christian Kästner - Software and Societal Systems Department - Kenneth C. Griffin School of Computer Science - Carnegie Mellon University s3d.cmu.edu. Checked 21 October 2026.