Rate My Professor Rui Liu

Dr. Liu's research specializes in advanced manufacturing, encompassing human-centered machining, tool condition monitoring using machine learning techniques and advanced sensing such as audio signals, machining process optimization to enhance productivity and surface quality, and simulation of material behavior and microstructure evolution during cutting processes. His contributions include calibration-based tool condition monitoring systems for repetitive operations, edge-based algorithms for wear monitoring in milling, and investigations into human visual and tactile perception in machined surface inspection. Key publications include 'A physically based constitutive model for simulation of segmented chip formation in orthogonal cutting of commercially pure titanium' in CIRP Annals (2015), 'An edge-based algorithm for tool wear monitoring in repetitive milling processes' in Journal of Intelligent Manufacturing (2022), 'Calibration-based tool condition monitoring for repetitive machining operations' in Journal of Manufacturing Systems (2020), 'Data-driven smart manufacturing: Tool wear monitoring with audio signals and machine learning' in Journal of Manufacturing Processes (2019), and 'A survey of immersive technologies and applications for industrial product development' in Computers & Graphics (2021). In 2025, he received the National Science Foundation CAREER Award to develop advanced manufacturing workforce training integrating experiential learning and regional collaborations in the Finger Lakes area. His work impacts manufacturing automation, quality control, and skills development in industry.