I am a sophomore at the University of Southern California, studying Computer Science and Applied Mathematics and working as a Student Researcher in the LiraLab and the GLAMOR Lab under the guidence of Professors Erdem Biyik and Jesse Thomason.

I aim to develop deep reinforcement learning algorithms enabling robots to: (1) learn efficiently from minimal explicit and implicit feedback—such as demonstrations, corrections, and comparisons—and (2) continuously adapt and improve across diverse tasks and environments. My work is rooted in imitation learning, incorporating techniques from Reinforcement Learning with Human Feedback (RLHF) and Lifelong Learning in Decision Making (LLDM).

My goal is to pursue a career in academia. While I am currently deepening my technical expertise to further narrow down my research trajectory, I am strongly committed to building a robust theoretical foundation in deep reinforcement learning, robotics, control, and information theory. My present research focuses on analyzing and advancing state-of-the-art sample-efficient methods for robotic systems.

Fun Fact: I was a competitive FPV drone racer and was part of the Korean National Drone Racing Team in 2021 and 2022.

Other Interests

• I am part of the 3D4E (3D for All) organization where I do CAD modeling.
• I am the Head of Operations at the SC Garden where I design efficient and automated systems that grow tomatos, strawberries, and other produce!
• I am working towards a minor in Cognitive and Developmental Psychology. I find much inspiration from Psychology when it comes to my research.