Nuri Kim

Nuri Kim

Assistant Professor
Department of Electronics Engineering
Jeonbuk National University

At Neural Robot Intelligence Laboratory (NuRI Lab), we explore how robots can develop world models to make informed decisions, utilize visual navigation for goal-directed movement, and leverage 3D Gaussian Splatting for enhanced spatial perception. Our research integrates techniques from task and motion planning, semantic mapping, skill chaining, and multi-modal perception to build robots that can operate robustly in real-world environments and collaborate effectively with humans.

Education

Seoul National University

Ph.D. in Electrical & Computer Engineering

Mar 2016 - Feb 2023

Advisor: Prof. Songhwai Oh

Korea University

B.S. in Electrical Engineering

Mar 2012 - Feb 2016

Graduated with Highest Honor (GPA: 4.2/4.5)

News

Mar 2025

Joined Jeonbuk National Univ. as an Assistant Professor in Electronics Engineering.

Sep 2024

SEA accepted to Knowledge-Based Systems.

Mar 2023

Start working @ SAIT autonomous car team.

Feb 2023

Invited talk @ KAIST.

Dec 2022

Successfully finished Ph.D. Thesis Defense.

Dec 2022

Oral presentation at CoRL 2022.

Sep 2022

TSGM accepted to CoRL 2022 as an oral presentation.

Publications

SEA Overview

Semantic Environment Atlas for Object-Goal Navigation

Nuri Kim, Jeongho Park, Mineui Hong, and Songhwai Oh

Knowledge-Based Systems, Volume 304, 25 November 2024, 112446

PDF arXiv
TSGM Overview

Topological Semantic Graph Memory for Image-Goal Navigation

Nuri Kim, Obin Kwon, Hwiyeon Yoo, Yunho Choi, Jeongho Park, and Songhwai Oh

Conference on Robot Learning (CoRL-22) Oral presentation

Project Page PDF arXiv Code Video
VGM Overview

Visual Graph Memory with Unsupervised Representation for Visual Navigation

Obin Kwon, Nuri Kim, Yunho Choi, Hwiyeon Yoo, Jeongho Park, and Songhwai Oh

International Conference on Computer Vision (ICCV-21)

Project Page PDF Code Video
IDNet Overview

Learning Instance-Aware Object Detection Using Determinantal Point Processes

Nuri Kim, Donghoon Lee, and Songhwai Oh

Computer Vision and Image Understanding (CVIU-20)

PDF Code
Text2Pickup Overview

Interactive Text2Pickup Networks for Natural Language-Based Human-Robot Collaboration

Hyemin Ahn, Sungjoon Choi, Nuri Kim, Geonho Cha, and Songhwai Oh

IEEE Robotics and Automation Letters (RAL-18) and IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS-18)

PDF Video

Talks

Advanced Sensing Technologies for Physical AI

Invited Talk, KETI, Jan 2026

What Are World Models? The Next Frontier of Physical AI

Invited Talk, Seoul AI Foundation, Dec 2025

Understanding LLMs and the Future of AI

Invited Talk, Jeonbuk National University, May 2025

Semantic Visual Navigation for Embodied Agents: A Graph-Based Approach

Invited Talk, KAIST, Feb 2023

Slides

CoRL 2022 Review

Lab Seminar, Seoul National University, Jan 2023

Slides

Oral Presentation of TSGM

Conference on Robot Learning, Auckland, New Zealand, Dec 2022

Video Slides

Honors and Awards

Brain Korea 21 Plus Scholarship

Seoul National University

2019-2021

Great Paper Award

Korean Institute of Information Scientists and Engineers

2017

Lecture & Research Scholarship

Seoul National University

2016

Graduate with Great Honor

Korea University

2016

Creative Challenger Scholarship

Korea University

2015

National Scholarship For Science and Engineering

Korea Student Aid Foundation (KOSAF)

2014-2015

Teaching

Image Processing

Jeonbuk National University

Spring 2026

Introduction to Robot Learning

Jeonbuk National University

Fall 2025

Computer Science and Programming

Jeonbuk National University

Fall 2025

Professional Service

Associate Editor

  • International Conference on Ubiquitous Robots (UR) 2025

Conference and Journal Reviewing

  • ECCV 2026
  • CVPR 2026
  • TPAMI 2025
  • IROS 2024–2025
  • ICRA 2024
  • UR 2022–2025
  • T-RO 2020–2023
  • RA-L 2022

Projects

Physical AI (2025-Present)

Establishment of a Leading Physical AI Model and Proof of Concept (PoC)

Funded by National IT Industry Promotion Agency (NIPA).

  • Designed a Physical AI innovation lab to establish leading Physical AI capabilities.
  • Developing Physical AI learning technologies required for the deployment of humanoid intelligent robots in existing manufacturing industries.

Navi AI (2019-2023)

Development of AI Technology for Guidance of a Mobile Robot to its Goal with Uncertain Maps in Indoor/Outdoor Environments

Funded by the Ministry of Science and ICT (MSIT).

  • Developed an indoor environment navigation robot that works even in unknown environments by leveraging semantic understanding when maps are unavailable.

SW Star Lab (2019-2023)

Robot Learning: Efficient, Safe, and Socially-Acceptable Machine Learning

Funded by the Ministry of Science and ICT (MSIT).

  • Developed a robot navigation technology capable of predicting crowd trajectories and performing social actions in various crowd cluster scenarios.

Brain AI (2019-2023)

Brain-Inspired AI with Human-Like Intelligence

Funded by the Ministry of Science and ICT (MSIT).

  • Developed a reliable object detector in occluded environments.

Giga 4D (2017-2020)

Real-time 4D reconstruction of dynamic objects for ultra-realistic service

  • Collected 3D point cloud data for dynamic object registration and alignment.

Quant (2020-Present)

Personal Project: Quantitative Trading

  • Development of algorithms for finding an optimal portfolio ratio.