36-613
Statistics · Data Science · Machine Learning · AI
Shannon Gallagher
Special Faculty, Lecturer
Carnegie Mellon University
I am a statistician and machine learning researcher interested in rigorous evaluation, interpretable AI, and responsible use of models in high-stakes settings.
Current teaching
About
Statistics for modern applications.
My work spans large language models, AI evaluation, infectious disease modeling, and statistical software. Before returning to Carnegie Mellon as faculty, I led machine learning research at the Software Engineering Institute and conducted postdoctoral research at the National Institute of Allergy and Infectious Diseases.
I earned my Ph.D., M.S., and B.S. at Carnegie Mellon University.
Teaching
Fall 2026
36-614
Data Engineering and Distributed Environments
Fall 2026 · Mini 2
Monday & Wednesday, 9:30–10:50 AM · Baker Hall 140A
Recent teaching
36-642
Telling Impactful Stories with Data Visualization
Summer 2026 · Mini 6
36-643
Introduction to Data Science Computing Workflows
Summer 2026 · Mini 5
36-644
Applications of Real-World Data Science: A Capstone Experience
Summer 2026 · Mini 5
36-315
Statistical Graphics and Visualization
Spring 2026
Research
Selected work
- 2026 Interpretable Stylistic Variation in Human and LLM Writing Preprint
- 2025 Quantifying the Efficacy of Fine-tuning Large Language Models Preprint
- 2024 Assessing LLMs for High Stakes Applications International Conference on Software Engineering
- 2022 Branching Process Models to Identify Risk Factors for Infectious Disease Transmission Journal of Computational and Graphical Statistics
A full curriculum vitae is available by email.
Contact
Contact me.
Department of Statistics & Data Science
Carnegie Mellon University
sgallagh [at] stat.cmu.edu