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👋 Hi, I am Jee-eun Lee (이지은) <🏠|🎓|📄>

I am a PhD student in Aerospace Engineering and Engineering Mechanics at UT Austin, advised by Professor Luis Sentis. My research interests lie in Robotics, focusing on Trajectory Optimization and Robot Representation Learning.

📄 Publications

  • Jee-Eun Lee*, Jaemin Lee, Tirthankar Bandyopadhyay, Luis Sentis, "Sample Efficient Dynamics Learning for Symmetrical Legged Robots: Leveraging Physics Invariance and Geometric Symmetries", ICRA 2023 accepted
  • Jee-Eun Lee*, Tirthankar Bandyopadhyay, Luis Sentis, "Adaptive robot climbing with magnetic feet in unknown slippery structure", Frontiers in Robotics and AI, 2022
  • Shin, Mi*; Qian, Hua; Lee, Jee-Eun; Sentis, Luis; Maberti, Silvia, ”Consumer product spraying exposure assessment using robotics”, Environmental Science Technology, Under Review
  • Riley Bowyer*, Jacob Oestrich, Noa Thouard, James Barker, Jee Eun Lee, Luis Sentis, Tirthankar Bandyopadhyay, ”In-Situ Foothold Evaluation for a Magnetic Climbing Robot”, Australasian Conference of Robotics and Automation, December 2021
  • Jee-Eun Lee and Jaeheung. Park, ”Kinematic Parameter Calibration for Humanoid Robot Using Relative Pose Measurement in Walking Motion,” 2019 16th International Conference on Ubiquitous Robots (UR), Jeju, Korea (South), 2019, pp. 712-717, doi: 10.1109/URAI.2019.8768785.
  • Cheongjae Jang*, Jee-eun Lee, Sohee Lee and F. C. Park, ”A minimum attention control law for ball catching,” Bioinspiration biomimetics, Volume 8608, pp 154-165, 2015, doi:10.1088/1748-3190/10/5/055008
  • Cheongjae Jang*, Jee-eun Lee, and F. C. Park, ”On the Role of Attention in the Control of Human and Robot Movements,” in Proc. 16th International Symposium on Robotics, Research, Singapore, 2013.

💻 Skills

  • Language : C/C++, Python, Matlab,
  • Machine/Deep Learning : PyTorch, TensorFlow, Keras
  • Operating System: Window, Ubuntu, Xenomai
  • ETC : ROS, Dart(Dnamics Engine), Pinocchio

Jee-eun Lee(이지은)'s Projects

ase389 icon ase389

Software Stacks for the class ASE 389 DCSN/CTRL HUMAN-CENT ROBOTS

dm_control icon dm_control

DeepMind's software stack for physics-based simulation and Reinforcement Learning environments, using MuJoCo.

mujoco icon mujoco

Multi-Joint dynamics with Contact. A general purpose physics simulator.

mujoco_menagerie icon mujoco_menagerie

A collection of high-quality models for the MuJoCo physics engine, curated by DeepMind.

ompl icon ompl

The Open Motion Planning Library (OMPL)

pinocchio icon pinocchio

A fast and flexible implementation of Rigid Body Dynamics algorithms and their analytical derivatives

pnc icon pnc

Planning and Control Algorithms for Robotics

rossy_utils icon rossy_utils

Useful util functions library for Robot SW System (RoSSy)

sdlp icon sdlp

Seidel's LP Algorithm: Linear-Complexity Linear Programming for Small-Dimensional Variables

symloco icon symloco

reinforcement learning for symmetrical locomotion

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