Prof. Shoemaker’s research focuses finding on cost-effective, robust solutions for environmental problems by using optimization, modeling and statistical analyses of resource allocation and operations management. This includes development of numerically efficient nonlinear optimization algorithms utilizing high performance computing and algorithm applications to complex, nonlinear systems. These new algorithms for nonlinear simulation-optimization and uncertainty analysis include parallel implementations for computationally expensive simulation models in many fields. Her environmental applications areas include physical and biological groundwater remediation, pesticide management, ecology, and surface water pollutant transport in large watersheds based in some cases on data that has been collected and analyzed over years. This analysis has resulted in improved policies for environmental remediation and protection.

Investigating Contaminant Hydrology with New Methods for Calibration, Sensitivity and Uncertainty Analysis including Application to Sensor Network Design

Integration of Weather Forecasting Models with Watershed Models

Environmental Sustainability Systems Analysis Including Multiple Objective and Fixed Cost Optimization of Management Decisions with Watershed and Groundwater Applications

CPA-SCA-T: Power-Performance Optimization Strategies for Highly Uncertain Multi-Core Systems

Integrated Statistical and Optimization Analysis for Computationally Expensive Models of Complex Environmental Systems 1/2005-12/2007

Integrating Data and Models from the Cannonsville, NY Watershed to Assess Short and Long Term Effects of Phosphorus BMPs in the Northeast 9/15/05-9/15/08