Yilei Zeng

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About

Yilei Zeng is a researcher at the intersection of machine learning and interactive digital media, with a primary focus on applied ML for game development and education. His most notable contribution is the design and implementation of a pioneering graduate-level course, "Applied Machine Learning for Games," which addresses the game industry's shift toward re-engineered systems that embed machine learning technologies for gameplay operation, analysis, and understanding. This work, published in 2021, has garnered 4 citations and serves as a foundational resource for bridging the gap between academic ML training and industry needs. Zeng’s research emphasizes practical, hands-on learning, equipping students with the skills to integrate ML into modern game engines. His course represents a significant achievement in curriculum innovation, helping to prepare the next generation of developers for an era where intelligent systems are central to game design. Through this work, Zeng has established himself as a key contributor to the growing field of machine learning in gaming, offering a replicable model for graduate education that directly responds to evolving industry demands.