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Seungyeon Kim

I am Ph.D. student at Robotics Laboratory in Seoul National University, and my advisor is Frank C. Park. Prior to joining Ph.D program, I completed my M.S. and B.S. with Mechanical Engineering (minor: Economics) from Seoul National University.

My research interests lie in robotic grasping, robot non-prehensile manipulation, deep learning-based visual perception and 3D recognition, and machine learning algorithms on 3D data.

Email: ksy at robotics.snu.ac.kr


Publications
ms
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
Openreview

emmp
Equivariant Motion Manifold Primitives
Byeongho Lee*, Yonghyeon Lee*, Seungyeon Kim, MinJun Son, Frank C. Park
Conference on Robot Learning (CoRL) 2023
Openreview

se2
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
Oral Presentation   •   Paper   •   Code   •   Supplementary   •   Bibtex

dsqnet
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
Paper   •   Code   •   Bibtex

smf
A Statistical Manifold Framework for Point Cloud Data
Yonghyeon Lee*, Seungyeon Kim*, Jinwon Choi, Frank C. Park
International Conference on Machine Learning (ICML) 2022
Paper   •   Code   •   Bibtex

jnp
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
Paper   •   Bibtex

Projects
sr
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.

lane
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).

drl
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.

se2
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.


Education

  • Sep 2021 - April 2024. Student researcher at Institute of Advanced Machines and Design
    • Working in Intelligent Machine System Research Department
  • Sep 2019 - Feb 2024 (expected). Ph.D. student at Robotics Laboratory, Seoul National University
    • Advisor: Prof. Frank Chongwoo Park
  • 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
    • Summa Cum Laude
  • Feb 2013. Gyeonggibuk Science High School

  • 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

  • Template based on Jon Barron's website.