Osung Seo is a fourth-year doctoral candidate in the Cognition, Brain & Behavior program at Syracuse University. His research broadly concerns understanding and mechanisctically describing human cognitive behaviors such as category learning, through the lens of various computational models. His ultimate goal is to identify patterns out of the seemingly chaotic human behaviors and formally describe them.
Under the guidance of his advisor, Dr. Michael Kalish, his dissertation project focuses on examining the potential effects of unlabled instances on dimensional attention shift during semi-supervised learning. He aims to study how dimensional attention changes over the course of learning, under a scenario where corrective feedback is only rarely provided. Although his learning scenario, called semi-supervised learning, is the most frequent type of learning in real life, research focus has been almost exclusively placed on supervised learning and unsupervised learning. He proposes an experimental paradigm where dimensional attention shift is likely to be observed and the results will be analyzed with both human category learning models and machine learning model. Throughout this project, he expects to discover more about human semi-supervised learning.
During his free time, he enjoys watching horror films and exploring the variety of exquisite cuisines offered around the Syracuse area. Osung also loves traveling and experiencing the cultural and geographic variety of the United States and around the world. His favorite vacations are his trip to the Big Bend and Zhangjiajie and he plans to go back as much as possible in the future.