People / Students / Class of 2025
Kaiyuan Deng graduated from the University of Minnesota with a major in Statistics and a minor in Mathematics. During his undergraduate studies, he developed a strong foundation in math, statistics, and programming, which led to his interest in data. He believes that by studying data one can extract insights that are meaningful to business and help people explore the world more effectively. With his curiosity in the field of data, he joined the Private Equity Company Hongtai APlus for an internship in June 2023 in Beijing. In this internship, he developed M&A and IPO exit prediction models utilizing post-investment valuation, post-investment holdings, and exit coefficients, as well as P/S and P/E ratios. He also applied PCA to reduce the dimensionality of various attributes of stocks and used K-means clustering based on price-to-earnings ratio and dividend yield to classify stocks. Recently, Kaiyuan has continued to apply his machine-learning capabilities at Lanzhou University. He used Random Forest and SVM models to predict the effect of antiretroviral drugs on HIV treatment and optimized the model parameters using a hyperparametric grid search to improve the accuracy of the XGBoost model to 88.7%. Not only that, Kaiyuan developed his skills as a data analyst at ZTJ GROUP OF CHINA and Beijing Seeyon Internet Software Corporation. He optimized and cleaned data using SQL, and used A/B testing to evaluate the effectiveness of different design options when building office system interfaces, which ultimately led to significant improvements in customer satisfaction. These experiences have given Kaiyuan a deeper understanding of how data can be used in real life. In the MLDS program at Northwestern University, Kaiyuan hopes to further enhance his programming skills as well as develop excellent business sense. He looks forward to enhancing his ability to solve complex business problems through real-world case studies and interactions with industry experts in the program, as well as laying a solid foundation for a future career in data science.
