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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 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 Robot | Sr. Researcher at KIMM
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                  KIMM, Korea Institute of Machinery and Materials
- Daejeon, Korea
- http://backseunghyeok.com/
- @seunghyeokback
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  gist-ailab/uoaisgist-ailab/uoais PublicCodes of paper "Unseen Object Amodal Instance Segmentation via Hierarchical Occlusion Modeling", ICRA 2022 
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  open3d-ros-helperopen3d-ros-helper PublicHelper for jointly using open3d and numpy in ROS 
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  gist-ailab/SF-Mask-RCNNgist-ailab/SF-Mask-RCNN PublicSynthetic RGB-D Fusion (SF) Mask R-CNN for Unseen Object Instance Segmentation 
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  gist-ailab/easy-ros-tutorialgist-ailab/easy-ros-tutorial PublicROS Tutorial and Examples: Play with the camera and robot using Python 
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  gist-ailab/QuBERgist-ailab/QuBER PublicQuBER: High-quality Unknown Object Instance Segmentation via Quadruple Boundary Error Refinement 
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