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Seungyeon Kim
I am postdoctoral researcher at Robotics Laboratory in Seoul National University,
advised by Frank C. Park.
Prior to joining postdoctoral program, I completed my Ph. D., M.S., and B.S. with Mechanical Engineering (minor: Economics) from
Seoul National University.
My research interests lie in prehensile and non-prehensile robotic object manipulation, visual perception and
3D object recognition from vision sensor data, machine learning algorithms on 3D data, and geometric machine
learning methods including group equivariant models.
Email: ksy at robotics.snu.ac.kr
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T2SQNet: A Recognition Model for Manipulating Partially Observed Transparent Tableware Objects
Young Hun Kim*, Seungyeon Kim*, Yonghyeon Lee, Frank C. Park
Conference on Robot Learning (CoRL) 2024
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Leveraging 3D Reconstruction for Mechanical Search on Cluttered Shelves
Seungyeon Kim*, Young Hun Kim*, Yonghyeon Lee, Frank C. Park
Conference on Robot Learning (CoRL) 2023
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Equivariant Motion Manifold Primitives
Byeongho Lee*, Yonghyeon Lee*, Seungyeon Kim, MinJun Son, Frank C. Park
Conference on Robot Learning (CoRL) 2023
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SE(2)-Equivariant Pushing Dynamics Models for Tabletop Object Manipulations
Seungyeon Kim, Byeongdo Lim, Yonghyeon Lee, Frank C. Park
Conference on Robot Learning (CoRL) 2022
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DSQNet: A Deformable Model-Based Supervised Learning Algorithm for Grasping Unknown Occluded Objects
Seungyeon Kim*, Taegyun Ahn*, Yonghyeon Lee, Jihwan Kim, Michael Y. Wang, Frank C. Park
IEEE Transactions on Automation Science and Engineering (T-ASE) 2022
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A Statistical Manifold Framework for Point Cloud Data
Yonghyeon Lee*, Seungyeon Kim*, Jinwon Choi, Frank C. Park
International Conference on Machine Learning (ICML) 2022
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On the Encoding Capacity of Human Motor Adaptation
Seungyeon Kim, Jaewoon Kwon, Jin-Min Kim, Frank C. Park, Sang-Hoon Yeo
Journal of Neurophysiology (JNP) 2021
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Object Grasping and Manipulation Skills for Stable Housekeeping Service
Project Leader
The goal of the project is to develop skills to enable various household tasks, specifically,
to develop a skill that can grasp various tableware and objects on the table.
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Deep Learning-based Lane Detection Algorithm from LiDAR data
Project Leader
The goal of the proejct to develop a neural network architecture that recognizes 3D lane
information from LiDAR data (3D point cloud + point-wise intensity).
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Deep Reinforcement Learning Algorithm for Industrial Robot
Project Leader
The goal of the proejct is to develop safe and efficient reinforcement learning algorithm for
high-gain position controller-based industrial robots.
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Artificial Intelligence-based Automated Painting Robot System
Project Member (Role: Visualization)
The goal of the project is to develop an artificial intelligence-based smart painting robot
automation system for automobile factories.
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Education
Feb 2024. Ph.D. degree in Mechanical Engineering, Seoul National University
- Advisor: Prof. Frank Chongwoo Park
- Thesis: Learning for Vision-Based Object Manipulation: A Shape Recognition-Based Approach
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Slides
- Outstanding Doctoral Dissertation Award
Feb 2019. M.S. degree in Mechanical Engineering, Seoul National University
- Advisor: Prof. Frank Chongwoo Park / work closely with Prof. Sang-Hoon Yeo
- Thesis: On the Encoding Capacity of Human Motor Adaptation
Feb 2017. B.S. degree in Mechanical Engineering and Minor in Economics, Seoul National University
Feb 2013. Gyeonggibuk Science High School
- One-year early graduation
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Teaching Experiences
Teaching Assistant, Geometric Methods for High-Dimensional Data Analysis (M3239.006800), SNU, 2022F
Teaching Assistant, Dynamics (446.204A), SNU, 2018F
Teaching Assistant, Introduction to Robotics (M2794.0027), SNU, 2017S
Undergraduate Student Instructor, Basic Calculus 1 (033.016), SNU, 2015S
Undergraduate Student Instructor, Basic Calculus 2 (033.017), SNU, 2014F
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