CV

Education

• B.S. in China, Hubei University of Technology, 2017-2021
• MSe. in France, Arts et Métiers ParisTech, 2021-2023
• MSc. in France, Paris-saclay University, 2023-2024

RESEARCH INTERESTS

Robot Learning, Deep Reinforcement Learning, Learning from Demonstration, Simulation-to-Reality (Sim2Real), Human-Robot Interaction, Impedance Control, Optimal Control for Robotics

Professional Skill

• Theory
  • Estimation, Optimal control for robotics, Deep Reinforcement Learning, Imitation Learning, Computer Vision, Impedance Control and Admittance Control Theory
• Languages
  • French - C1
  • English - B2
• Programming:
  • Python; C++; C#; MATLAB
• Software
  • PyTorch, TensorFlow, ROS, PyBullet, Unity 3D, CoppeliaSim, SolidWorks, MUJOCO
• Other
  • Git; Linux; LaTex

Research experience

• Research Project: Assistive Robotics for Human Face Makeup
  • L’Oréal Recherche & Innovation Center
  • Jan,2023-Jul,2023, research intern
  • Duties included:
    • Developed a robotic make-up simulation environment based on an Ur5e robot and multiple RGBD cameras using C++, Gazebo, and ROS
    • Face Detection and 3D Keypoint Information Acquisition in Real-Time with Python and Mediapipe
    • Developed and validated robot control algorithms to implement inverse and positive kinematics control and trajectory planning in simulation and real robots using C++, Python, and Moveit
    • Developed our group’s first deep reinforcement learning framework for robots optimizing makeup skills in a human-like safe way using Python and TensorFlow.
    • Validated the deep reinforcement learning framework in simulation environments built with Gazebo (established our group’s first reinforcement learning validation platform from scratch)
  • Supervisor: Dr.BA Sileye, Dr.LI Tao, Dr.BICHON Jean-Christophe
• Research Project: Frugal and adaptive AI for flexible industrial Robotics
  • Arts et Métiers ParisTech (ENSAM)
  • Sep, 2022-Jan, 2023; academic projects
  • Duties included:
    • Exploited object pose estimation technologies to grasp industrial objects and deployed the grasping algorithm on the collaborative robot with a success rate than 80 %
    • Developed a fast learner neural network pipeline trained from a few datasets in less than 5 minutes, able to efficiently predict grasping locations on a specific object.
    • Validated the grasp pose estimation algo in the simulation and real Doosan Robot using ROS2 and Pybullet.
  • Supervisor: Prof.Richard Bearee

PAPERS AND POSTERS

• [Paper 1] SU Sichen,” Développement du robot assistant pour le maquillage.” Passed the school defenses and was included in the laboratory.

AWARDS, HONORS AND SERVICES

• First Prize Academic Scholarship for undergraduate students at HBUT (Top 1%) 2017-2021
• Second Prize Asia-Pacific Mathematical Modeling Competition Jan. 2020
• Second Prize, China National Student Mathematical Modeling Competition Oct. 2019
• Volunteer in the Media Center of the Athletes’ Village of provincial sports games Oct–Nov 2019