Class of 2025: Reilly Oare named College of Engineering Outstanding Master's Student
Reilly Oare found her passion in using machine learning to improve stream habitat restoration. Her research helps environmental agencies make smarter decisions, while her love for the outdoors continues to inspire her work.
Name: Emma “Reilly” Oare
College: College of Agriculture and Life Sciences/College of Engineering
Major: Biological systems engineering
Hometown: Warrenton, Virginia
Favorite Hokie memory: “We had collected some crawdads from the stream and put them in a holding tank. When we came back a short while later, one had decided to jump ship, with our undergrad researcher quipping, ‘Is he supposed to be there?!’ We quickly worked together with the entomology student to provide care to the crawdad and get him back in the tank. We still don’t fully understand how he got out, but it showed the sense of community and care that we all had.”
Reilly Oare grew up surrounded by nature, which fostered a love for the outdoors. When she began rock climbing at age 13, it further ignited her passion. "That was when it really clicked that I cared about our natural world and preserving the environment because I loved getting to be outside so much," she shared.
Finding home
Her academic journey began at NC State, where she initially pursued environmental engineering. However, it wasn't the right fit. "I realized that was not what I thought it was, and the program wasn’t right for me," she explained.
The turning point came when she transferred to Virginia Tech and discovered the biological systems engineering program, which has homes in both the College of Engineering and the College of Agriculture and Life Sciences. The department’s variety of classes, small class sizes, and research opportunities allowed her to tailor her major to be exactly what she was hoping for.
Research rocks
Oare’s decision to stay at Virginia Tech for her accelerated master's program was influenced by her positive undergraduate experience and the supportive community within the department.
Her research focuses on applying data-driven solutions, specifically machine learning, to predict a stream habitat characteristic called embeddedness. Embeddedness is the extent to which rocks are covered or sunken into the silt of the stream bottom, affecting both the stream environment and the amount of sediment in the streambed. The goal of her work is to streamline the process of identifying streams with poor habitat conditions, as well as streams that are likely to benefit from interventions like gravel addition.
“Her approach has already improved our ability to predict the amount of fine sediment in streambeds," said Associate Professor Jon Czuba. “She has done so by applying multiple AI and machine learning models, assessing the utility of each one, and further extracting useful information on important variables to inform our understanding of the underlying processes.”
By predicting embeddedness, Oare’s model can help decision-makers in watershed management, such as the Virginia Department of Environmental Quality, avoid unnecessary expenditures and focus efforts on streams that truly need restoration. Her research also contributes to the broader field of ecological engineering by combining machine learning and watershed management to solve complex ecological challenges.
Balancing passions
Outside of class, Oare is still an avid rock climber, spending hours each week at the climbing gym and outdoors. Oare also has a passion for pottery, knitting, and other crafts.
Oare's experiences at Virginia Tech have not only prepared her for a successful career but also continued to foster an even deeper appreciation for the natural world and the importance of preserving it.