Wenlin Yao is a Principal Researcher specializing in advancing large language models through reinforcement learning and agentic frameworks, with nine years of experience bridging research and production. He has led work on agentic LLMs for strategic reasoning, tool use, and environment interaction at Tencent AI Lab and built end-to-end RL systems for Amazon’s Rufus to improve planning and multi-step problem solving. Now at Microsoft Research, he focuses on translating frontier RL and agent design into robust, interpretable systems that mitigate hallucination and enable self-evolving behaviors. His PhD from Texas A&M underpins a strong theoretical foundation, while internships at BBN and Amazon reflect early hands-on applied research. Wenlin combines deep academic rigor with a track record of shipping scalable AI features in industry, often turning complex RL objectives into practical reward designs and production workflows. Based in Bellevue, WA, he is known for making subtle but impactful improvements in agent reliability and real-world tool integration.
9 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Texas A&M University
Bachelor's degree Software Engineering, Bachelor's degree Software Engineering at Dalian University of Technology
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