Jan Hoffmann
Associate Professor of Computer Science

I am an Associate Professor (tenure-track) at Carnegie Mellon’s Computer Science Department, and a member of the Principles of Programming (PoP) group and CyLab.
My research areas are programming languages and verification. My mission is to discover beautiful mathematical ideas that have a real-world impact, shape the way programmers think, and help to create software that is more reliable, efficient, and secure. Currently, I am working on quantitative verification, type systems, static resource analysis of programs, probabilistic programming, and programming languages for digital contracts.
Before joining Carnegie Mellon, I was an Associate Research Scientist in the FLINT group at the Department of Computer Science at Yale University. Before that, I was a PhD student at LMU Munich. My advisor was Martin Hofmann.
coordinates
jhoffmann@cmu.edu | |
phone | +1 412 268 6309 |
office | GHC 9105 |
address | Computer Science Department Carnegie Mellon University 5000 Forbes Avenue Pittsburgh, PA 15213-3891 |
news
Jan 29, 2022 | MSc student Yiyang Guo and BSc student Runming Li have joined the group. |
Jan 10, 2022 | I’m looking forward to serving on the ESOP 2023 program committee. |
Oct 6, 2021 | I’m grateful for having been selected for an Amazon Research Award. |
Oct 1, 2021 | I’m excited to welcome PhD student Myra Dotzel to the group. Myra is co-adviced by Limin Jia. |
Sep 6, 2021 | Steffen Jost and I co-authored a survey on Automatic Amortized Resource Analysis, which will appear in the upcoming MSCS special issue in honor of my late advisor Martin Hofmann. |
Jul 2, 2021 | Our article Automatic Resource Analysis with the Quantum Physicist’s Method has been accepted to ICFP 2021. |
Jun 25, 2021 | Check out our new paper Nomos: A Protocol-Enforcing, Asset-Tracking, and Gas-Aware Language for Smart Contracts, which describes the Nomos implementation and blockchain-specific features. You can try out the language in the Nomos web interface. |
Jun 1, 2021 | I’m excited about our work on probablisitic session types. A paper draft is available here. |