Skip to main content

Data, AI and Robotics

Improving how the world uses data to make decisions

Pictures of seeds use to train AI model.

The artificial intelligence used by the DeepSeed research team learns to differentiate between seed species by analyzing photos like these that only contain one specific seed.

Our work contributes meaningfully to Oregon State’s mission to lead with impact in a world shaped by data, technology and discovery. We are accelerating solutions to real-world challenges, whether by analyzing genomic data, modeling ecosystems or tracking disease spread.

These tools help us strengthen the reliability of data-informed decisions and develop solutions that improve health, address climate challenges, inform policy and advance life-enhancing technologies. They also support research automation by providing the statistical and computational backbone when precision and scale are essential.

Through this work, we ground innovation in critical scientific knowledge.

“Equipping people with the tools and understanding to turn data into insight, and insight into action, strengthens our ability to shape a better future.”

Lan Xue

Department Head, Statistics

Bridging science and society

A flock of birds flying in the foreground with windmills in the background
A closeup of a scientist sorting seeds for a computer to analyze
Canola flower seeds resting in a pod
RNA structure of Amycolatopsis orientalis, a bacterium that produces the antibiotic vancomycin

Statistician Lisa Madsen and statisticians from the United States Geological Survey have come together to develop methodology to estimate the total mortality of bats, birds and other small creatures on wind farms and solar facilities. The Endangered Species Act requires that wind farms pay particular attention to endangered or threatened species such as golden eagles, brown pelicans, whooping cranes, condors and Indiana bats, which are killed when they accidentally collide with turbine blades.

Accurate seed testing to ensure the quality of crop is essential to global agriculture — and the methods developed at the Oregon State Seed Lab in the 1970s are still used today. The Seed Lab is now working with statistician Yanming Di, with funding from the USDA through the Oregon Department of Agriculture, to incorporate new advances in robotics, computer vision, machine learning and stochastic modeling into testing. The multidisciplinary research group aims to develop a computer vision system for real-time, onsite seed analysis — a tool that could revolutionize farming in Oregon and beyond. This innovative approach aims to improve seed quality assessment, increase efficiency and provide valuable insights to farmers in the seed industry.

Virginia Lesser, emeritus professor of statistics, brought her survey expertise to a National Academies committee assessing the Need for Native Seeds and the Capacity for Their Supply. Native seeds are vital for ecosystem restoration and biodiversity, yet the U.S. lacks a coordinated supply system. The committee’s 2023 report outlines the fragmented state of native seed supply and recommends creating a national native seed strategy, increasing investment, and improving data collection on seed needs and availability.

RNA molecules are central to biology, and their function often depends on how they fold. Developed by biochemist Dave Hendrix and his team, bpRNA-1m is a comprehensive, open-access database that makes RNA structures easier to analyze and compare — opening insights into health, disease and how life works. Version 1.0 catalogs the secondary structures of over 28,000 RNA molecules, detailing how each one folds to do its job in the cell. Built using the bpRNA tool, the database provides consistent annotations of key structural features. For scientists, it’s a powerful resource for understanding RNA function, improving structure prediction, and advancing RNA-based treatments.

Data-driven approaches to complex global systems

Related centers and facilities

  • Center for Quantitative Life Sciences
    The Center for Quantitative Life Sciences (CQLS) at Oregon State drives interdisciplinary innovation, helping researchers turn complex data into meaningful discovery. It accelerates life science progress by integrating biology with data science, bioinformatics, statistics, and high-performance computing. CQLS provides expertise, infrastructure and lab services that support breakthroughs in health, agriculture, environmental science and biotechnology — such as modeling microbial responses to ocean change, analyzing genomic data on antibiotic resistance, and using machine learning to study protein structure and function.
  • Survey Research Center
    The Survey Research Center has provided valuable survey design, implementation and analysis services to clients across various sectors for over 50 years. The center helps university researchers, organizations, businesses and government agencies craft effective surveys to gather reliable data, offering expertise in question development, data collection and statistical analysis. With a focus on both public and private sectors, the SRC ensures high-quality, actionable insights that drive decision-making and impactful research.
  • Jen-Hsun Huang and Lori Mills Huang Collaborative Innovation Complex
    The Jen-Hsun Huang and Lori Mills Huang Collaborative Innovation Complex will be a dynamic home for team-based transdisciplinary research and teaching. The complex will support innovation, entrepreneurship and partnerships with industry and other higher education institutions, while helping to prepare graduates for Oregon’s workforce and beyond.

Data scientists are in high demand.

Students with experience in data science are in high demand across almost all sectors, from private and non-profit companies to government agencies and academia. Data science is transforming knowledge and practice across all fields of science and beyond, from biology to chemistry, health to resource management, marketing and business development, emergency preparedness, actuarial science and more.