Kenneth Mulder

  • Visiting Associate Professor in Data Science
Kenneth Mulder

Kenneth Mulder enjoys using various mathematical models to pull information from data that can be used to improve our understanding and management of natural and human systems. Much of his work is rooted in systems science and how patterns and models can transcend specific systems. Recently, Mulder has applied the same statistical modeling methods to better understand the gut bacterial composition of ticks, to compare subtropical plant communities in the sky islands of Arizona and New Mexico, and to derive a handful of meaningful indicators for sustainable human wellbeing

Areas of Expertise

Statistical modeling of human and natural systems

Recent Publications

Coe, N. R., Mulder, O., & Mulder, K.(2023). Examining the effect of beech bark disease on radial growth in American beech. Forests, 14, 312.

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