The research is broad and a wide variety of projects within the general context of data science methods applied to solving problems towards sustainability are studied. A sample of possible projects are listed below, while others will be added over time and/or may be offered by research mentors.

Project: Minimizing Solvent Waste Using Machine Learning
Project: Data-Science Driven Design of Architected Materials and Composites
Project: Accelerating Discovery and Characterization of Functional 2D Materials for Catalysis and Solar Energy Conversion Using Data Science Methods

Project: Improved Recovery of Wastewater Resources Using Microbial Communities, Machine Learning, and Photobioreactors
Project: Data Analytics for Lithium Ion Battery Upcycling
Project: Metal-Free Catalysis Development with Machine Learning

Project: Modeling and Data Analysis for Designing Photocatalytic Degradation
Project: Modeling Impacts of Chemical Pesticides on Wild Pollinator and Native Plant Ecosys-tems
Project: Deep-Learning for Scientific Discovery of Materials with Improved Corrosion-Resistance

Project: Machine Learning for Raman Spectroscopy