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.
- Jee-eun Lee*, Andrew Bylard, Robert Sun, Luis Sentis, "Grasp Failure Constraints for Fast and Reliable Pick-and-Place Using Multi-Suction-Cup Grippers", submitted 2024
- Jee-eun Lee*, Andrew Bylard, Robert Sun, Luis Sentis, "On the Performance of Jerk-Constrained Time-Optimal Trajectory Planning for Industrial Manipulators", 2024 IEEE International Conference on Robotics and Automation (ICRA).
- Jee-Eun Lee*, Jaemin Lee, Tirthankar Bandyopadhyay, Luis Sentis, "Sample Efficient Dynamics Learning for Symmetrical Legged Robots: Leveraging Physics Invariance and Geometric Symmetries", 2023 IEEE International Conference on Robotics and Automation (ICRA).
- 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 K., Hua Qian, Jee-Eun Lee, Luis Sentis, and Silvia I. Maberti. "Estimating exposures from spray products using robotic simulations." Annals of Work Exposures and Health 67, no. 8 (2023): 979-989.
- 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.
- Language : C/C++, Python, Matlab, C++ CUDA
- Machine/Deep Learning : PyTorch, TensorFlow, Keras
- Operating System: Window, Ubuntu, Xenomai
- ETC : ROS, Mujoco, Pybullet, Dart(Physics Engine), TensorFlow, Stable-Baselines3(RL), Cublas, etc.