Sheng-I Yang

My research focuses on improving quantitative tools for modeling forest growth and yield in pure and mixed-species forests to inform management decisions. I am particularly interested in investigating the advantages and limitations of both existing and alternative statistical methods (e.g., machine learning, survival analysis, small area estimation) to address management challenges in forestry practice.

My lab at the Warnell School of Forestry and Natural Resources is seeking one to two graduate students. The research will focus on developing small area estimation (SAE) methods to improve forest inventory and growth projection for southern pine plantations. This collaborative project involves various forest industry companies and state forests, providing an excellent opportunity to gain experience in applying statistical and computational methods to solve practical forestry questions. Research topics include, but are not limited to:

1. Investigating the applications of unit-level models, both with and without random effects, for predicting tree lists and/or diameter distributions.
2. Examining the impact of varying levels of ground GPS spatial precision on SAE estimates.
3. Evaluating alternative quantitative methods (e.g., machine learning) within the SAE framework.
4. Assessing the precision of total volume estimates using SAE-derived input variables in commonly used growth and yield systems.
5. Exploring the incorporation of previous inventories and/or historical remote sensing data as auxiliary information in growth projections.

The selected students will be responsible for presenting research results at Plantation Management Research Cooperative (PMRC) meetings and professional conferences, as well as publishing relevant work in peer-reviewed journals. Priority will be given to applicants with backgrounds in statistics, computer science, and GIS. Funding is available (e.g., tuition, stipend, travel fund) if needed.

Please send your CV and a brief description of your experience relevant to this research topic to syang23@uga.edu.