Yiran Jia

After graduating from the University of Washington Seattle with a degree in economics, Yiran began working as a data analyst at a healthcare organization. She encountered various complicated real-world statistics problems during her work, which motivated her to start learning about algorithms like segmentation and regression analysis in her free time. Later she decide to enroll part-time in a mathematics program at the University of Washington Bothell, where she had the opportunity to work on medical imaging reconstruction problem, which was motivated by the goal of lowering the exposure of x-ray dosage on cancer patients. In the last summer, she participated an NSF REU at UCLA and had the opportunity to explore generative models in machine learning for the applications in computer graphics. While seeing the robust performance among different algorithms, she started getting to know some underlying challenges and therefore went to UCSD mathematics department to build a deeper theoretical foundation and explore her interest in high dimensional data analysis. As a first-generation student, she is grateful for the support she received from her mentors during her undergraduate study. Meanwhile, she was an English conversation facilitator who worked on advancing equitable access to academic activities for international students. She was also a peer health educator at the Green Dot Program. She is grateful to be supported by Sloan Fellowship, and hopes to become a mentor one day to inspire others in pursuing science.