This project from RSS 2024 develops whole-body control policies for humanoid robots that can express human-like motion. It combines imitation learning from motion capture data with reinforcement learning fine-tuning in Isaac Gym simulation, followed by sim-to-real transfer to physical hardware. The system uses PyTorch-based deep RL (rsl_rl, legged_gym) to train expressive motor skills.