Shixiang Shane Gu

Gu helped robots learn complex movements from fewer physical trials, reducing the time and wear involved in real-world training. He later contributed to instruction-tuned language models and zero-shot chain-of-thought prompting, which showed that a simple reasoning cue could sharply improve performance. He now works on Gemini reasoning.