Research

Dr. Welch's research covers theoretical plant modeling with emphasis on ecological genomics, crop modeling, aquifer-based agricultural production systems, optimization theory, and applications including model-based decision support systems.

This entails merging ecophysiological and quantitative genetic modeling approaches along with advanced automated sensor-based methods for collecting large amounts of within season data on plant and microenvironment status. In many cases extracting quantities of interest from this massive data requires model inversion via novel optimization algorithms. The goal is predicting the performance of given genotypes subjected to particular management schemes in specified environments. This capability is central to (i) accelerating breeding programs by predicting the outcomes of prospective crosses and (ii) improving management decision-making in precision agriculture.

• Ph.D. Zoology, Michigan State University, 1977
• B.S. Computer Science, Michigan State University, 1971