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Seoul National University of Science and Technology (SeoulTech) | Seoul, South Korea

• B.S. in Computer Science and Engineering (Major)
• B.S. in Applied Artificial Intelligence (Minor)
• Relevant Coursework:
  • Core CS: Data Structures and Abstract Data Types, Algorithm Design and Analysis, Operating Systems, Computer Architecture.
  • AI & Robotics: Machine Learning, Deep Learnin, Reinforcement Learning, Computer Vision.
  • Math: Applied Statistics, Linear Algebra, Data Analysis.

I am fascinated by intelligence that manifests in the physical world. My goal is to understand and build autonomous agents where reasoning is not just an abstract computation, but a visible behavior that emerges through interaction with reality.

• Physically Grounded Intelligence: Moving beyond static data to create agents that perceive, move, and interact within complex environments.
• Emergent Behavior & Dynamics: Exploring how sophisticated, life-like actions arise from fundamental rules and structural evolution.
• Adaptive Interaction: Investigating the continuous loop between an agent’s internal model and the external world to achieve robust, real-time adaptation.

Ongoing Research Project | 2026 – Present

• Core Concept: Integrating sequential visual reasoning with generative policy modeling to enhance long-horizon planning in robotic agents.
• Objective: Improving the success rates and interpretability of multi-stage manipulation tasks in non-stationary environments.
• Environment: Developed using the MuJoCo physics engine with a Franka Emika Panda arm simulation.

• Languages: Python (PyTorch, JAX), C++, Linux (Ubuntu)
• Robotics & Simulation: MuJoCo, ROS2, Isaac Gym
• AI/ML: Generative Modeling (Diffusion), Reinforcement Learning, Transformer Architectures