My work focuses on using computational methods to make complex systems more interpretable, actionable, and useful for decision-making. I have contributed to research on LLM bias, explainability, text mining, online communication, science-of-science, and digital humanities, with publications in venues including Nature Communications, Nature Human Behaviour, IEEE Transactions on Biomedical Engineering, and Artificial Intelligence in Medicine.
I am especially interested in translational, cross-disciplinary research that connects technical innovation with real-world application. Across funded projects, industry collaboration, and academic leadership, I work to build data-driven approaches that are rigorous, explainable, and practical for stakeholders.
Black and Hispanic faculty – underrepresented minorities (URMs) within academia – face career barriers that come to a crux in promotion and tenure decisions. Leveraging a natural …
Although engaging with both academic and general audiences is a key objective of the digital humanities, the extent to which this value influences the full development of a project …
Missouri University of Science & Technology
University of Houston
HPE Data Science Institute, University of Houston
University of Houston, Department of Mechanical Engineering & Honors College"
University of Houston, Department of Computer Science
University of Stuttgart, Germany
Freiberg University of Mining and Technology, Germany
Freiberg University of Mining and Technology, Germany
Peggy Lindner
Associate Professor | Associate Chair for Graduate Studies
Engineering Management and Systems Engineering
Missouri University of Science & Technology
Engineering Management Building 214
Email: plindner@mst.edu