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π¨βπ My research interests are centered around unseen object robotic manipulation, focusing on segmentation, grasping, and placement of novel objects using deep learning.
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I recently completed my PhD under the supervision of Professor Kyoobin Lee at GIST from 2018 to 2024. During my doctoral studies, I interned as an Applied Scientist at Amazon Robotics in Berlin from 2023 to 2024. I am also a two-time recipient of the Samsung HumanTech Paper Awards in 2022 and 2023.
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My research has been successfully applied to Amazon warehouse robots, furniture assembly, and human-robot collaboration. Currently, I am expanding my work on test-time adaptation and foundation models to improve robustness in new domains. Check more details in my personal website
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π¬ Feel free to reach out for collaboration, questions, or just a chat about robotics and AI!
Ph.D. in AI and Robotics | Former Amazon
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GIST, Gwangju Institue of Science and Technology
- Gwangju, Korea
- http://backseunghyeok.com/
- @seunghyeokback
Highlights
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gist-ailab/uoais
gist-ailab/uoais PublicCodes of paper "Unseen Object Amodal Instance Segmentation via Hierarchical Occlusion Modeling", ICRA 2022
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open3d-ros-helper
open3d-ros-helper PublicHelper for jointly using open3d and numpy in ROS
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gist-ailab/SF-Mask-RCNN
gist-ailab/SF-Mask-RCNN PublicSynthetic RGB-D Fusion (SF) Mask R-CNN for Unseen Object Instance Segmentation
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gist-ailab/IITNet-official
gist-ailab/IITNet-official PublicThis is an official implementation for "Intra- and inter-epoch temporal context network (IITNet) using sub-epoch features for automatic sleep scoring on raw single-channel EEG".
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gist-ailab/easy-ros-tutorial
gist-ailab/easy-ros-tutorial PublicROS Tutorial and Examples: Play with the camera and robot using Python
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gist-ailab/deep-grasping
gist-ailab/deep-grasping PublicROS wrapper for DNN based robotic grasping algorithms
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