If you are looking for an expert in data engineering, ETL, and cloud platform, who also has experience with python, ROS, UR5 arm, simulation, imitation learning and robotics:
Hi there, nice to meet you!

2021: Researched and implemented deep reinforcement learning and impedance control model for robotics arm behavior control. Experimented in Drake simulator with Haddington Dynamics Dexter Robotics Arm.

2022: Implemented a human teleoperation for Behavior Cloning pipeline that aims to collect expert data and train policy for UR5 pick-and-place actions with a Robotiq gripper. Expert data are collected using VIVE Pro 2. This pipeline will be used for future robotic manipulation tasks.

Assisted mentor with building tensorflow framework to train sequencial data. Performed neural network optimization. Improved deep learning strategies in algorithm.

A team member in the software subteam. Collaborated on the design of a waiter robot for ROBOCUP@HOME competition. Reseached and tested algorithms for supervised learning in computer vision module for the robot. Implemented the manipulation of robot arm, gripper with ROS in Gazebo, designed testing environment in Gazebo for grasping behavior training.

Implemented an image classification algorithm for 10 classes (animals and objects) using Tensorflow framework within 48 hours, got the 4th place.

Trained Unity's ML agents with rewards and punishments to compete with other agents in a capture-ball-game. Click to watch demo.

Implemented and trained a policy in Pybullet for robotics arm pick-and-place actions that aims to achieve robust behaviors when dealing with unknown environments in real-time.

The Mind-Body problem is a debate about the relationship between the human physical body and the mental process takes place in the brain. In my paper I defended Frank Jackson's Knowledge Argument, that our world contains both physical and mental properties, against Physicalism's ability hypothesis.