People / Students / Class of 2025
Seung Jae (Jae) graduated from the University of California-San Diego with a degree in Probability and Statistics in 2023. Taking statistics class, programming language R was mainly used to conduct projects and assignments aimed at deriving the significance of result values through data import, preprocessing, and testing function libraries. While studying statistics in college, he displayed enthusiasm for integrating statistics other disciplines. Departing from general statistics classes, which mainly covers theories and calculations, his experience in an independent study group enabled him to attain a profound understanding of statistics as well as a realization of the importance of intricate machine learning concepts by analyzing selected papers. This group-based class allowed him to explore various machine learning models, including Convolutional Neural Networks, Neural Networks, and GAN, conducting theoretical and practical experiments with applications closely aligned with real-world scenarios in the industry. To gain practical insights into the application of academic knowledge in the field, Jae engaged in internship programs in Korea after completing military service before resuming his studies in the U.S. Firstly, his internship at the lab in Sungkyunkwan University provided him with valuable experiences in the application of machine learning and data science. Within this lab, he conducted a project focused on predicting soccer game results, utilizing data from the top five soccer leagues supplied by Kaggle. This project afforded him direct exposure to distinctions between prediction and classification, diverse approaches within machine learning techniques, and the intricacies of data preprocessing and modeling. Applying techniques such as PCA, SVM, ANN, and CNN, to soccer game predictions enhanced comprehensive understanding of predictive programs. This project involved creating data science codes on diverse libraries on Python. He recognized the significant impact of data quality and appropriateness on the accuracy of the model, reinforcing the importance of proper data scraping. Furthermore, during internship at the research center at Kiwoom Securities, he assumed responsibility for scraping data related to the industries of electronics, steel, utility, and mobile service providers. Throughout this process, he selected relevant information, such as financial statements, graphs from newspaper articles, or tables from data disclosed through the Data Analysis, Retrieval, and Transfer System (“DART”), media, official websites of entities, or corporate annual reports. This information served as the basis for reports published in Research Analytics. Jae's academic major, coupled with field internship experiences, have provided him with valuable insights into the realm of Data Science. Through the master's program in Machine Learning and Data Science at Northwestern University, he hopes to enhance his competencies in data science and broaden his proficiency in additional computer science aspects, such as methods and algorithms. This path will position him to into an innovation leader in the data-centered industry, allowing Jae to accomplish his overarching career goals.
