Sen Liu

University of Louisiana at Lafayette, Jiangxi University of Science and Technology

Papers

Total Citations

H-Index

About

Sen Liu is an interdisciplinary researcher whose work spans artificial intelligence, smart manufacturing, and materials science. His research focuses on harnessing cutting-edge AI technologies — particularly large language models (LLMs) and deep reinforcement learning — to transform how scientific discovery and industrial automation are approached. Liu's most impactful contribution, "Knowledge-guided Large Language Model for Material Science" (2025, 14 citations), positions him at the frontier of AI-driven scientific research. By integrating domain knowledge with LLMs, Liu addresses a critical challenge in the post-ChatGPT era: moving beyond generic AI capabilities toward specialized, reliable tools for materials discovery and analysis. Equally notable is his work bridging simulation and real-world robotics. His 2025 paper on Digital Twin Synchronization (7 citations) demonstrates a sophisticated approach to deploying reinforcement learning agents in real-time robotic additive manufacturing — a notoriously difficult transfer problem in smart manufacturing systems. His career arc, beginning with expert-system-based power-line inspection robots (2011), reveals a consistent commitment to intelligent automation across domains. With growing citation momentum and research appearing at the intersection of AI, robotics, and materials science, Sen Liu represents an emerging voice shaping the next generation of AI-augmented engineering and scientific research.