Xinyang Geng is a promising researcher in the field of computer science, focusing on reinforcement learning. He is a PhD student at the prestigious University of California, Berkeley, where he has also worked as a research assistant at the BAIR Lab, and a software engineering intern. Furthermore, Geng has interned at IBM and was a Google Brain Resident at Google. He is an expert in the areas of artificial intelligence, machine learning, and statistics, with a double major in Computer Science and Statistics from UC Berkeley.

At present, Geng's research is centered around reinforcement learning and is supervised by Professor Sergey Levine. He has also worked on the StatNews Project at UC Berkeley as a research assistant. Geng brings to the table an excellent academic background and practical experience in the field of computer science, and his work has been published in several high-profile academic journals.