Yonghyeon Lee
About Me
I am an AI Research Fellow at the Korea Institute For Advanced Study (KIAS). Prior to this, I earned my Ph.D. in Robotics Laboratory at the Seoul National University (SNU) under the guidance of Frank C. Park. Further back, I completed my B.S. in Mechanical Engineering and Physics at SNU.
Research Interests: Geometric Data Analysis/Machine Learning/Deep Learning, Robotics, Computer (3D) Vision
Contact: ylee@kias.re.kr, yhlee.gabe@gmail.com
Research Highlights
Motion Manifold Primitives (MMPs)
(Arixv) Isometric Motion Manifold Primitives++
(CoRL 2023) Equivariant Motion Manifold Primitives
Geometric Manifold Representation Learning
(TAG-ML in ICML 2023) Minimum Curvature Manifold Learning
(ICLR 2023) Contractive Autoencoder for Non-Euclidean Data
(ICML 2022) A Statistical Manifold Framework for Point Cloud Data
(ICLR 2022) Isometric Representation Learning
(NeurIPS 2021) Graph Regularized Manifold Learning
3D Scene Understanding & Robotic Manipulation
(RA-Letters 2023) Neural Normal Field for Grasping Transparent Objects
(CoRL 2023) Mechanical Search on Shelves
(CoRL 2022) Equivariant Pushing Dynamics Learning
(T-ASE 2022) Superquadric Primitives for Grasping
News
(Nov4, 2023) Yeah! Our paper on NFL: Normal Field Learning for 6-DoF Grasping of Transparent Objects is accepted at RA-Letters.
(Nov 4, 2023 ~ Nov 12, 2023) I will be at CoRL in Atalanta, US, presenting two posters!
(Aug 30, 2023) Our two papers, Equivariant Motion Manifold Primitives and Leveraging 3D Reconstruction for Mechanical Search on Cluttered Shelves, are accepted at CoRL 2023.
(July 22 ~ Aug 1, 2023) I will be present at ICML in Hawaii, US.
(July 7, 2023) Our paper, On Explicit Curvature Regularization in Deep Generative Models, is accepted at the 2nd Annual Topology, Algebra, and Geometry in Machine Learning Workshop in ICML 2023.
(June 15 ~ July 6, 2023) I will be at the Nonsan Korea Army Training Center.
(Mar 1, 2023) I have become an AI Research Fellow at the KIAS Center for AI and Natural Sciences.
(Feb 24, 2023) Great news! I have successfully completed my Ph.D. program and am thrilled to announce that I will be awarded the Outstanding Doctoral Dissertation Award by the Mechanical Engineering Department!
(Feb 8~10, 2023) I will be present at the KIAS AI Center winter workshop and will give a 30 mins talk on "Geometric Methods for Machine Learning". (slide)
(Jan 21, 2023) Our paper, Geometrically regularized autoencoders for Non-Euclidean data, is accepted at ICLR 2023.
(Nov 4, 2022) I will give a talk for My Ph. D. Thesis Defense Seminar on "Geometric Methods for Manifold Representation Learning" at 4 pm in SNU (301-306), all are welcome! (slide)
(Sep 10, 2022) Our paper, SE(2)-Equivariant Pushing Dynamics Models for Tabletop Object Manipulations, is accepted at CoRL 2022 for an oral presentation.
(July 2022) I received Youlchon AI STAR Fellowship.
(July 17~27, 2022) I will be present at ICML in Baltimore, US, and will give the spotlight talk and poster presentation.
(June 10, 2022) Our paper, DSQNet: A Deformable Model-Based Supervised Learning Algorithm for Grasping Unknown Occluded Objects, is accepted at T-ASE 2022.
(May 15, 2022) Our paper, A Statistical Manifold Framework for Point Cloud Data, is accepted at ICML 2022.
(Apr 15, 2022) I gave a presentation at the 2022 AIIS Spring Retreat and won the 3rd prize for the poster presentation.
(Jan 29, 2022) Our paper, Regularized Autoencoders for Isometric Representation Learning, is accepted at ICLR 2022.
(Sep 29, 2021) Our paper, Neighborhood Reconstructing Autoencoders, is accepted at NeurIPS 2021.