Shenghan Guo
Assistant Professor, School of Manufacturing Systems and Networks
Shenghan Guo is an assistant professor in the School of Manufacturing Systems and Networks at Arizona State University. Her research centers around knowledge-informed data analytics and domain-aware AI models. She strives to innovate data and AI-driven solutions that revolutionize automation, autonomy, and human-centricity in manufacturing processes and systems. She is experienced in statistical quality control, prognostics, and data mining. She has handled multiple research datasets from manufacturing fields, particularly those with complex properties, such as in-situ thermal video and multi-sensory data streams. The current applications of her research include in-situ prognostics, customized additive manufacturing, and manufacturing worker monitoring and training. Her lab hosts an OPTOMEC Aerosol Jet Printer for high-resolution, flexible 3D printing, supporting experiments in electronic printing/packaging, human-machine interactions, and AI-assisted fabrication of new materials/structures.
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Adjacent segment disease (ASD) remains a significant and poorly understood complication of lumbar spinal fusion surgery. This project aims to develop a convolutional neural network (CNN) model informed by clinical knowledge to predict ASD risk based on preoperative lumbar MRI scans and patient information. By integrating imaging data with clinical risk factors, the model seeks to address a critical gap in decision making tools for neurosurgeons.