معرفی
Dr. Ying Lin is an Associate Professor in the Department of Industrial and Systems Engineering at the University of Houston's Cullen College of Engineering. Her research focuses on machine learning applications in healthcare analytics, manufacturing systems optimization, and data-driven decision-making. She leads the Smart Health & INtelligent Engineering Systems (SHINES) Lab, which integrates AI and engineering principles to solve complex problems in healthcare and manufacturing.
Dr. Lin holds a Ph.D. in Industrial and Systems Engineering from the University of Washington (2017), an M.S. in Industrial and Management Systems Engineering from the University of South Florida (2014), and a B.S. in Statistics from the University of Science and Technology of China (2012).
Her research spans healthcare analytics (e.g., drug efficacy analysis, patient trajectory modeling) and manufacturing process optimization (e.g., superconductor quality control, anomaly detection). Recent work emphasizes federated learning frameworks, privacy-preserving data mining, and machine learning for medical decision support. She has published extensively on topics like predictive modeling for treatment strategies in multiple sclerosis and antipsychotic-associated weight gain in children.
Dr. Lin's work bridges healthcare informatics and advanced manufacturing, with a focus on scalable solutions for real-world challenges. Her lab's projects often involve interdisciplinary collaborations and real-world data applications from electronic medical records and manufacturing processes.
