As a Computer Science and Engineering major with a Studio Art minor, Rolina Qu (she/her) spent her summer in the Undergraduate Research Apprenticeship Program (URAP) exploring big questions in artificial intelligence. Under the guidance of Dr. Andrew Perrault, Qu focused on making AI training faster and more efficient through a process called dataset distillation. Dataset distillation helps improve AI systems by greatly decreasing the amount of time spent on training them.
“My research looks at ways to make this process better by using what we’ve learned about how neural networks behave during training,” Qu explains. “It’s exciting to work on something that could make AI systems more efficient and effective.”
For Qu, research is about freedom and curiosity.
“I enjoy the ability to engage my curiosity to its fullest degree,” she says. “Being able to bring together everything I’ve learned and use it to improve something or discover something new in this rapidly growing field is especially fulfilling.”
Her experience has also taught her resilience.
“Research is very difficult but very engaging in a distinct way, and I enjoy it quite a lot,” Qu reflects. “I hope to continue researching in the future.”
Expected to graduate in Winter 2025, Qu’s work shows how undergraduate researchers are helping advance AI, one algorithm at a time.