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Biography
John Mitchell is the Mary and Gordon Crary Family Professor, professor of computer science, and by courtesy professor of electrical engineering and professor of education. He was previously Stanford Vice Provost for Teaching and Learning and chair of the Computer Science Department. As vice provost, his team worked with more than 500 Stanford faculty members and instructors on over 1,000 online projects for campus or public audiences and organized the Year of Learning to envision the future of teaching and learning at Stanford and beyond. As co-director of the Lytics Lab, Carta Lab and Pathways Lab, he has worked to improve educational outcomes through data-driven research and iterative design.
Mitchell’s research focusses on programming languages, computer security and privacy, blockchain, machine learning, and technology for education. Sample publications include Reinforcement Learning for the Adaptive Scheduling of Educational Activities (CHI 2020), Automated Analysis of Cryptographic Assumptions in Generic Group Models (J. Cryptology, 2019), Evaluating the privacy properties of telephone metadata (PNAS 2016), and Third-party web tracking: Policy and Technology (IEEE S&P). He is the author of two textbooks, Foundations for Programming Languages (1996) and Concepts in Programming Languages (2002). With over 250 publications and over 30,000 citations, he has led research projects on a range of topics, been a consultant or advisor to many companies, and served as editor-in-chief of the Journal of Computer Security.
Mitchell’s first research project in online learning started in 2009, when he and six undergraduate students built Stanford CourseWare, an innovative platform that expanded to support interactive video and discussion. CourseWare served as the foundation for initial flipped classroom experiments at Stanford and helped inspire the first massive open online courses (MOOCs) from Stanford.
Mitchell’s research focusses on programming languages, computer security and privacy, blockchain, machine learning, and technology for education. Sample publications include Reinforcement Learning for the Adaptive Scheduling of Educational Activities (CHI 2020), Automated Analysis of Cryptographic Assumptions in Generic Group Models (J. Cryptology, 2019), Evaluating the privacy properties of telephone metadata (PNAS 2016), and Third-party web tracking: Policy and Technology (IEEE S&P). He is the author of two textbooks, Foundations for Programming Languages (1996) and Concepts in Programming Languages (2002). With over 250 publications and over 30,000 citations, he has led research projects on a range of topics, been a consultant or advisor to many companies, and served as editor-in-chief of the Journal of Computer Security.
Mitchell’s first research project in online learning started in 2009, when he and six undergraduate students built Stanford CourseWare, an innovative platform that expanded to support interactive video and discussion. CourseWare served as the foundation for initial flipped classroom experiments at Stanford and helped inspire the first massive open online courses (MOOCs) from Stanford.
Other titles
Professor, Computer Science
Professor (By courtesy), Electrical Engineering
Professor (By courtesy), Graduate School of Education
Faculty Affiliate, Institute for Human-Centered Artificial Intelligence (HAI)
Program affiliations
DAPS
SHIPS (PhD): Educational Data Science
Research interests
Higher Education | Teachers and Teaching | Technology and Education
Recent publications
Kizilcec, R., & Mitchell, J. (2024). Remote Learning and Work. IEEE INTERNET COMPUTING, 28(1), 7–9.
Charitsis, C., Piech, C., & Mitchell, J. C. (2023). Detecting the Reasons for Program Decomposition in CS1 and Evaluating Their Impact. Proceedings of the 54th ACM Technical Symposium on Computer Science Education.
Bigman, M., Gilon, Y., Han, J., & Mitchell, J. C. (2022). Insights for post-pandemic pedagogy across one CS department. Arxiv. Retrieved from https://arxiv.org/abs/2203.09050
