Tianyi Gao

University College London, Dalian Minzu University

Papers

Total Citations

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About

Tianyi Gao is a rising researcher at the intersection of advanced manufacturing and intelligent robotics, with key contributions in **concrete 3D printing** and **deep reinforcement learning for robotic control**. In their highly cited 2021 work, "3D Concrete Printing with Variable Width Filament" (7 citations), Gao pioneered a novel approach to additive construction that eliminates the need for traditional molds—addressing long-standing inefficiencies in labor, cost, and quality. This work positions them at the forefront of intelligent construction methods that promise to reshape the building industry. More recently, Gao has expanded into **robotic path planning**, publishing "Deep Reinforcement Learning for Robotic Arm Path Planning in Multi-Obstacle Environments" (2024, 4 citations). Here, they introduced a state representation technique that enables robotic arms to navigate complex, obstacle-laden environments with unprecedented accuracy. By bridging material science and AI-driven automation, Gao is contributing to a future where construction and manufacturing are both more flexible and autonomous. Their early citation impact, combined with the timeliness of their research, marks them as a promising voice in smart infrastructure and robotics.