REU Site: Algorithms and Optimization for Sustainability and Biology

Modern interdisciplinary problems increasingly require complex solutions that incorporate sophisticated algorithmic techniques. Practitioners are needed who are able to both understand real-world problems and undertake abstract algorithm development. The goal of this project is to expose undergraduate students to collaborative algorithm development and problem solving. Students who participate in this project will develop broadly-applicable research skills that are valuable in both academic and commercial workplaces. Research projects will be centered on the broad themes of optimization and sustainability with specific topics in computational biology, geometry and optimization for applications of carbon capture technology. An overarching goal is to heighten undergraduate student interest and participation in innovative research and to increase the number and diversity of students (especially underrepresented groups) pursuing undergraduate and graduate degrees in computer science and/or related disciplines. The intellectual focus of this REU site is in developing algorithms and optimization approaches for real-world problems. The problems considered are computationally challenging (most are NP-hard), so innovative algorithms and optimization approaches are needed to solve them in practice. Accordingly, the activities of the REU program are centered on the following general topic areas: 1. Carbon capture infrastructure optimization, 2. Combinatorial and geometric optimization, and 3. Graph algorithms for computational biology. Carbon capture infrastructure optimization requires novel algorithms to intelligently design pipeline networks that meet industrial carbon dioxide emission mitigation targets. Combinatorial and geometric optimization is a traditional computer science research area, however a recent trend in geometric optimization is to consider more realistic constraints. Finally, the data revolution in biology has led to a variety of new research topics in algorithms and computation, including DNA assembly problems and characterizing gene interactions and networks. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.