Yijia Jin grew up in Beijing, China and chose to come to the U.S. as an international student during high school.
“I went to a very stressful, competitive high school in Beijing. [My parents] wanted to give me a more varied experience—a chance to explore and experiment,” Jin said.
A family friend attended The Dock Mennonite Academy, a private, Christian school in Pennsylvania, and, inspired by their experience, Jin applied and was placed with a local host family. “The Mennonite community was very kind and close knit,” she recalled. “I was included in all the family activities—baby showers, funerals, weddings, church.”
Jin stayed in Pennsylvania through high school, going home to Beijing for winter and summer holidays.
“I grew a lot,” said Jin, who is now a first-year student in the M.S. in Data Science program at Columbia University. “I became more open-minded, not afraid of unfamiliar people and situations, less afraid to step out of my comfort zone, more adventurous.”
Jin returned to the U.S. for her undergraduate studies and majored in mathematics, computer science, and photography at New York University (NYU). She credits her studies in the visual arts with helping her to formulate ideas and better express herself, skills she considers valuable for her work in data science.
“Before you take a picture you think about the relationship between the audience and the image—what do you want that relationship to be? What do you want to express? This has influenced how I think about my data science work. What is the relationship between the product and the user? It makes you think about the purpose of the product you are developing. It also affects how you present the information to your client. This relationship is part of the art of expression.”
Jin graduated from NYU in 2020 and returned to China to work as a machine learning engineer for HiThink Financial Services, a stock trading platform. She works on user attributes, demographics, and online behavior data using machine learning, natural language processing, and deep neural networks to make inferences, predictions, and recommendations.
She decided to pursue her master’s degree in data science at Columbia for more advanced, professional training in neural networks and deep learning. “I’m enjoying the emerging topics such as reinforcement learning and deep learning in biomedical imaging. I also really appreciate the opportunity for hands-on experience to test our algorithms.”
After graduation, Jin plans to return to China to be closer to her family, to put her new skills to work, and to pursue entrepreneurial ideas. “I’m thinking about maybe starting a TikTok channel where I teach older people to use their smartphone devices,” she said. “China has a high aging population, and I think I have the skills to explain this well.”
— Karina Alexanyan, Ph.D.