I am a machine learning researcher at Boeing Korea Engineering and Technology Center (BKETC). At BKETC, I have been working on developing vision-based AI models for aircraft manufacturing such as embodied vision-language model, document understanding, and anomaly detection.
I received my PhD in robotics perception at Robot Learning Laboratory in Seoul National University (SNU), Korea, in 2024, under supervision of Prof. Songhwai Oh . I received my BS in Electrical and Computer Engineering from SNU in 2017.
My research interests are focused on vision-based robot learning and semantic perception. Also, my research interests include embodied navigation AI, multi-modal semantic perception, robotics, VLM for embodied system, document understanding, and anoamly detection.
Commonsense-Aware Object Value Graph for Object Goal Navigation Hwiyeon Yoo, Yunho Choi, Jeonho Park,
and Songhwai Oh. IEEE Robotics and Automation Letters (RA-L), 2024 40th Anniversary of the IEEE Conference on Robotics and Automation (ICRA@40), 2024  
paper
General-Purpose Deep Reinforcement Learning Using Metaverse for Real World Applications National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (MSIT), 2023-
Implementation of a vision-based object goal navigation algorithm for embodied agents in real robot navigation.
AI Technology for Guidance of a Mobile Robot to its Goal with Uncertain Maps in Indoor/Outdoor Environments Ministry of Science and ICT (MSIT), 2019-2023
Development of a vision-based path following navigation algorithm for embodied mobile robots with sparse implicit memory.
Development of a vision-based path following and homing navigation algorithm for embodied mobile robots with building semantic map.
Development of a vision-based object goal navigation algorithm for unknown environments for embodied mobile robots using semantic graph memory.
BioMimetic Robot Research Center - Biomimetic Recognition Technology Defense Acquisition Program Administration and Agency for Defense Development (ADD), 2016-2021
Development of an insect-like compound eye camera prototype.
Development of light-weight computer vision models on the compound eye: objectness estimation, semantic segmentation, ego-motion estimation, depth estimation, and 3D environment reconstruction.
Realistic 4D Reconstruction of Dynamic Objects Ministry of Science and ICT (MSIT), 2017-2019
Development of a 3D point cloud matching algorithm.
Development of a 3D human motion reconstruction algorithm by using human part segmentation and tracking.