Dr. Jan Hoffmann

Associate Professor

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Biography

Jan Hoffmann is an Associate Professor in the Department of Computer Science at Carnegie Mellon University. His research is primarily focused on formal methods and programming languages, particularly in the area of quantitative resource-usage analysis. Hoffmann's work aims to bridge the gap between theoretical insights and practical applications to improve the reliability, efficiency, and security of software systems. He emphasizes the need for rigorous techniques and tools that can be accessible to software developers without requiring excessive training. His areas of interest include digital contracts, probabilistic programming languages, and the analysis of algorithms. Hoffmann and his collaborators have developed new methodologies to model and analyze resource usage in software systems, tackling challenges such as performance bugs and timing safety in critical applications. His contributions extend to designing innovative programming languages that address the specific requirements of digital contracts, integrating features like session types and resource analysis. A key goal of his research is to derive automatic resource analyses that enhance the predictability and transparency of software execution, ensuring that developers can better understand and optimize the performance of their code.

Research Interests

Courses

15819 - Spring, 2026 15714 - Fall, 2025 15814 - Fall, 2024 15611 - Spring, 2024 15411 - Spring, 2024

Requirements for Carnegie Mellon University

Doctorate Program
Requirements
GPA Requirement
Required:3.5
GRE General
Verbal
Required:158
Quantitative
Required:149
Analytical Writing
Required:4
Overall
Required:4
Prerequisites
Bachelor's degree in Psychology or related field Research experience/publications
Application Checklist
  • Online application
  • Statement of Purpose
  • Three letters of recommendation
  • Transcripts
  • GRE scores (optional but reported in profile)
  • English Proficiency (TOEFL/IELTS/Duolingo)
Specialization Notes

Admission is extremely competitive with no strict GPA cut-offs; holistic review is used.