Amy Glen loves skiing, so much that it factored into her decision to attend the University of Vermont, where the Alaska native majored in biology and competed with the university’s ski team.
After graduating with her bachelor’s degree, Glen worked at a lab that conducted analytical chemistry studies for pharmaceutical companies, where she worked with a lot of Excel spreadsheets. She realized that automating the manual data entry tasks would help her become more efficient in her job, but she didn’t have any programming background.
Ravonne Byrd’s school and work are both in Corvallis, although her home is much closer to Albany — not the one just up the road, but that other Albany — about 3,000 miles away, in New York.
A student in the popular postbaccalaureate computer science online degree program offered through Oregon State Ecampus, Byrd also telecommutes to her job with the College of Engineering’s Center for Applied Systems and Software.
As an undergraduate student in electrical and computer engineering at Oregon State University, Bradley Heenk and his fellow students often printed 3D parts to use in their class projects. Since many students needed custom-printed parts at the same time, Heenk saw this as opportunity to start a business and help his classmates get quality parts more quickly.
Computer science and ecology may seem like an unlikely combination at first, but it’s exactly the niche Oregon State University assistant professor, Rebecca Hutchinson, envisioned. Her research uses machine learning and statistical modeling to help scientists answer questions like: What will happen to monarch butterflies under climate change? What are the habitat requirements of olive-sided flycatchers?
When researchers at Oregon State University created new tools to evaluate the decision-making algorithms of an advanced artificial intelligence system, study participants assigned to use them did, indeed, find flaws in the AI’s reasoning. But once investigators instructed participants to use the tools in a more structured and rigorous way, the number of bugs they discovered increased markedly.
Machine learning is making inroads into chemical engineering, where it’s helping researchers develop new nanoporous materials for a variety of applications.