Hyeongwoo Nam

Hyeongwoo Nam

Integrated M.S./Ph.D. Student, Mechanical Engineering
Machine Learning & Control Systems Lab, Yonsei University

I study how robots can remember, reason about, and act in the physical world with foundation models. I am interested in organizing a robot’s accumulated experience, such as observations, conversations, and notes, into a memory that LLM and VLM agents can search and reason over, and in turning such knowledge into reliable plans through structured world models and symbolic planning.

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Portrait of Hyeongwoo Nam

Research Interests

Education

Yonsei University

Sep 2023 – Present

Integrated M.S./Ph.D. in Mechanical Engineering · Advisor: Prof. Jongeun Choi

Yonsei University

Mar 2017 – Aug 2023

B.S. in Mechanical Engineering

Research Experience

Project Manager, NRF Basic Research Laboratory (BRL) Project

Jul 2026 – Present

Spatial Intelligence for Robotic Autonomy: From World Reasoning to Precision Control

National Research Foundation of Korea · Machine Learning & Control Systems Lab, Yonsei University

Publications

Conference Papers

  1. OntoPlan: An Ontology-Grounded Scene Representation and Agentic Framework for Scalable Robot Task Planning

    Hyeongwoo Nam, Woongje Cho*, Juwon Kim*, Jongeun Choi†

    NeurIPS 2026Conference on Neural Information Processing Systems, 2026

    Paper arXiv Project Code

    * Equal contribution   † Corresponding author

Journal Articles

  1. Data-Driven Driver Training via Counterfactual and Language-Based Guidance in Racing Scenarios

    Jonghak Bae, Hyeongwoo Nam, Kunhee Ryu, Jihye Lee, Jinsung Kim, Hokyun Chun, Jongtaek Han, Jongeun Choi

    IEEE Access 2025IEEE Access, vol. 13, pp. 170181–170199, 2025

    Paper

  2. Scale-Equivariant Object Perception for Autonomous Driving

    Taekhyung Cho, Hyeongwoo Nam, Jongeun Choi

    IEEE T‑IV 2025IEEE Transactions on Intelligent Vehicles, vol. 10, no. 9, pp. 4361–4370, 2025

    Paper

Honors & Awards