Sentao Miao

Sentao Miao is an Adjunct Professor in the Department of BUS at McGill University, specializing in Operations Management. His research focuses on Big Data & Machine Learning, Optimization Under Uncertainty, Pricing & Revenue Management, Retail Operations Management, and Supply Chain Management. Miao's work involves developing efficient learning and optimization algorithms with applications in operations management, including dynamic pricing, assortment selection, and inventory control. He is affiliated with the McGill Desautels Faculty of Management and contributes to research through various projects and publications.

Sentao Miao is a researcher in Operations Management, focusing on dynamic pricing, revenue management, and inventory control. His work explores the integration of machine learning and optimization techniques to address complex decision-making problems in business environments. Miao's research includes topics such as personalized pricing, demand learning, and privacy-preserving methods in revenue management. He has published extensively on dynamic joint assortment and pricing optimization, online personalized assortment optimization, and adaptive algorithms for multi-warehouse inventory systems. His studies also touch on differential privacy, nonparametric demand models, and the application of advanced mathematical tools like wavelet transforms and quantics-TT approximations.