NCSA REU Program currently has the below Faculty Offered Projects to choose from for this summer.
Summer 2026 REU Projects – more coming soon!
(Click to expand each project)
PROJECT 1: TBD
Andre Schleife, The Grainger College of Engineering, Materials Science & Engineering
TBD
Project Description:
TBD
Student Contributions:
TBD
PROJECT 2: Climate Change, Migration, and Socioeconomic Impacts of the Deforestation of the Amazon in Brazil
Angela Lyons, College of Agricultural, Consumer and Environmental Sciences, Agricultural & Consumer Economics
Aiman Soliman, College of Fine and Applied Arts, Department of Urban and Regional Planning
Project Description:
This interdisciplinary research project examines how internal migration in Northern Brazil and the Amazon—driven by environmental degradation and economic hardship—is reshaping land use, regional economies, and ecological sustainability. Rapid deforestation, fueled by land speculation, agricultural expansion, and poorly designed policies, has disrupted ecosystems, accelerated climate change, and created harsh living conditions that push vulnerable populations to migrate. These migration flows often move people to equally fragile areas, potentially perpetuating cycles of deforestation.
The ultimate goal is to inform sustainable development strategies that balance economic needs with conservation efforts in the Amazon and similar forested regions worldwide.
Student Contributions:
Responsibilities:
The student will work closely with NCSA researchers, faculty, and graduate students to:
Preprocess geospatial and socioeconomic datasets
Conduct data modeling, analysis, and predictions
Create maps and other data visualizations from geospatial and socioeconomic data
Develop, review, and document code in Python and/or R
Assist with the development, training, validation, and testing of machine learning algorithms
Create and maintain a GitHub repository for scripts and documentation
Participate in regular mentor meetings and team discussions
Preferred Qualifications:
Undergraduate student in data science, computer science, electrical and computer engineering, statistics, or related field
Proficiency in Python and/or R
Basic knowledge of machine learning techniques and/or geospatial analysis
Experience with GIS tools (e.g., QGIS, ArcGIS) and/or remote sensory data is a plus
Ability to create maps, dashboards, and visual analytics
Familiarity with version control systems (e.g., Git/GitHub)
Strong problem-solving skills and attention to detail
PROJECT 3: Generative AI and exascale computing for materials science discovery
Eliu Huerta, College of Liberal Arts and Sciences, Department of Astronomy
Hao Peng, The Grainger College of Engineering, Siebel School of Computing
Project Description:
TBA
Student Contributions:
Responsibilities:
The selected student will participate in the development and evaluation of generative AI and scientific large language models for the in silico discovery of materials for energy storage and conversion, including metal organic frameworks and crystal-like materials.
Preferred Qualifications:
Hands-on knowledge using computational chemistry software, such as LAMMPS, DFT and/or GCMC will be a plus. Students should have experience using python, and popular AI APIs (PyTorch, TensorFlow, etc.,). Experience using high performance computing platforms will be a plus.