Donna has over 25 years of experience with machine learning and heuristic optimization methods that 1) enable social issues (essentially penalties for not meeting constraints) to be placed on the site/stakeholder objective functions, and 2) provide stakeholders with a suite of "optimal" solutions rather than a single design, allowing consideration of the trade-offs between costs, risks, and assumptions. The focus of her Ph.D. and private sector experience involved field-scale applications of multi-objective optimization, much of this done while working with prior Gund fellows and a few who remain on as Gund Affiliates.

Since Donna's arrival at UVM she has collaborated with faculty and students across five different UVM colleges on a number of computational approaches to multi-scale environmental problems, including: the evaluation of human impacts to surface waters and groundwaters; lake Cyanobacteria bloom research; and assessing linkages between stream geomorphic, water quality, and habitat metrics/parameters. Collaborating with microbiologists around the world has led to the development and application of new tools for characterizing the spatial structure of microbial communities in municipal landfill leachate-contaminated groundwater environments, and tracking these changes through time at discrete monitoring locations using molecular-based techniques.