Summary
Tianyi Zhou is a machine learning researcher and Visiting Assistant Professor with eight years of experience bridging academia and industry, currently based in Seattle. He has an extensive publication record (~130 papers) across top venues in ML, NLP, CV, and AI, and has held roles at MBZUAI, University of Maryland, Google, and University of Washington. His recent work probes how human learning principles (curriculum, curiosity, exemplar selection) can improve robustness and generalization of modern models, while also advancing controllable generative AI, synthetic data, self-evolving systems, and human-AI teaming. He develops methods around LLMs, multimodal foundation models, and reinforcement learning with an eye toward efficient, trustworthy, and environmentally friendly hybrid intelligence. A PhD from the University of Washington, he combines deep theoretical grounding with practical collaborations across industry labs and global universities.
8 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at University of Washington
English