Howoong Jun

I'm a Ph.D candidate at Robot Learning Lab (RLLab) of Seoul National University, supervised by Professor Songhwai Oh.

Before the Ph.D course, I received B.S. degree and M.S. degree from Electrical and Computer Engineering, Seoul National University, 2017 and 2019 respectively. During my master's course, I was adviced by Professor Beomhee Lee. Previously, I was a research engineer/manager at SK Telecom in 2019-2022.

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TL;DR 📝

  • B.S. in Electrical and Computer Engineering (Combined minor: Bio-Engineering), Seoul National University (2010-2017)
  • M.S. in Electrical and Computer Engineering, Seoul National University (2017-2019)
  • Research Engineer / Manager, SK Telecom (2019-2022)
  • Ph.D Candidate in Artificial Intelligence, Seoul National University (2021-present)
  • Research 🔬

    I'm interested in spatial intelligence for robotics. Most of my research is about improving robot intelligence through spatial information. Some papers are highlighted.

    Renderable Street View Map-Based Localization: Leveraging 3D Gaussian Splatting for Street-Level Positioning
    Howoong Jun, Hyeonwoo Yu, and Songhwai Oh
    International Conference on Intelligent Robots and Systems (IROS), 2024
    paper / video

    Introduce a new method for street-level localization that first utilizes 3D Gaussian splatting in street-level localization problem

    RNR-Nav: A Real-World Visual Navigation System Using Renderable Neural Radiance Maps
    Minsoo Kim, Obin Kwon Howoong Jun, and Songhwai Oh
    International Conference on Intelligent Robots and Systems (IROS), 2024
    paper / arXiv / video

    Propose a robust visual localization and navigation framework in real-world environments, utilizing a mapping that directly integrates observed visual information into the bird-eye-view map

    EventPointNet: Robust Keypoint Detection with Neuromorphic Camera Data
    Howoong Jun, Sangil Lee, and Songhwai Oh
    International Conference on Control, Automation and Systems (ICCAS), 2022
    code / paper

    Propose a new network framework for keypoint detection using neuromorphic camera data

    Visually Grounding Language Instruction for History-Dependent Manipulation
    Hyemin Ahn, Obin Kwon, Kyungdo Kim, Jaeyeon Jeong, Howoong Jun, Hongjung Lee, Dongheui Lee, and Songhwai Oh
    International Conference on Robotics and Automation (ICRA), 2022
    project page / code & data / arXiv

    Propose history-dependent manipulation, which aims to enable a robot to refer to its task history when executing a series of pick-and-place operations instructed by language instructions

    Goal-driven Navigation for Non-holonomic Multi-robot System by Learning Collision
    Howoong Jun, Hanjun Kim, Beomhee Lee,
    International Conference on Robotics and Automation (ICRA), 2019  
    Paper

    Propose a reinforcement learning based multi-robot collision avoidance approach by learning collision

    Professional Experience 🧑🏻‍💻

    Autonomous and Systems Research Institute, Seoul National University
    2023 ~ Current
    Researcher
    sktelecom SK Telecom Co., Ltd
    2019 ~ 2022
    Manager & AI Researcher
    ICT R&D Center, New Mobility TF, Autonomous Vehicle Project
    AIX Center, Mobility Labs, HD Map Update Project (Road Learner)
    T3K, 5GX Location Labs, VLAM Project
    seoho Seoho Electric Co., Ltd
    2012 ~ 2014
    Skilled Industrial Personnel

    Teaching Experience 🧑🏻‍🏫

    Robot Programming
    Instructor
    Department of Robotics, Kwangwoon University
    2022 Spring
    iotaibd IoT, AI, and Big Data (M2177.004900_001)
    Teaching Assistant
    College of Engineering, Seoul National University
    2021 Spring, Fall
    intro_to_robot Introduction to Robotics (430.452A_001)
    Teaching Assistant
    ECE, Seoul National University
    2017 Spring

    Honors, Awards, Scholarships 🏆

  • AI Graduate Scholarship, SK Telecom (2017, 2018)
  • National Science and Engineering Scholarship, Korea Scholarship Foundation (2010, 2011, 2014, 2015, 2016)
  • Volunteer Service Award, ECE, Seoul National University (2012)

  • This website is cloned from Jon Barron's page