Jan Hoffmann
Assistant Professor, Computer Science Department
Jan Hoffmann is an assistant professor in Carnegie Mellon University’s Computer Science Department, and a member of Cylab and the Principles of Programming (PoP) group. His research areas are programming languages and verification. His mission is to discover beautiful mathematical ideas that have a real-world impact, shape the way programmers think, and help to create better software. Hoffmann is currently working on projects involving quantitative verification, type systems, static resource analysis of programs, probabilistic programming, proof assistants, and decision procedures.
Education
2011 Ph.D. in Computer Science, Ludwig-Maximilians-Universität and TU Munich
2007 M.S. in Computer Science, Ludwig-Maximilians-Universität
Affiliations
Research Interests
- AI and ML for security
- Applications of security and privacy
- blockchain
- cryptography
- cyber physical systems security and privacy
- embedded systems security
- Formal methods
- formal methods for security
- formal verification
- hardware security
- language-based security
- security
- security of AI and ML
- software security
- systems security
- verification
Media mentions
CyLab Security and Privacy Institute
CMU brings together experts from academia and industry during inaugural Secure Blockchain Summit
On May 8-9, the Carnegie Mellon CyLab Security and Privacy Institute hosted the University's first-ever Secure Blockchain Summit, bringing together experts from around the world to share their research and discuss the future of the technology and its applications.
CyLab Security and Privacy Institute
CyLab’s Jan Hoffmann receives Amazon Research Award
Amazon Research Awards provide funding, access to Amazon public datasets, and the use of artificial intelligence and machine learning services and tools.
CyLab Security and Privacy Institute
How CyLab researchers are safeguarding digital transactions
A new programming language developed by CyLab Ph.D. student Ankush Das aims to reduce the number of errors made in smart contracts.