AI Thrust Seminar | AI-Enhanced Sequential Decision Making: The Case of Path Planning
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In this talk, I present artificial intelligence (AI)-based sequential decision support frameworks focusing on two path planning cases, including the free-driving route optimization and the career path planning problem. I discuss the utilization of different AI and computing techniques (e.g., deep learning, reinforcement learning, parallel computing, stochastic optimization, etc.) in the establishment of path planning systems. I demonstrate several important theoretical and empirical findings in the two problems and discuss potential ethical issues associated with AI-based decision support systems.
Dr. Keli Xiao is an Associate Professor of Decision Analytics (with Tenure). He is a senior member of the ACM and the IEEE. He received his Ph.D. degree in management from Rutgers University in 2013. Dr. Xiao’s research interests include data mining, machine learning, and their applications in management. His research has appeared in many prestigious refereed journals on data mining and decision analytics, such as IEEE Transactions on Knowledge and Data Engineering (TKDE), ACMTransactions on Information Systems (TOIS), INFORMS Journal on Computing, and ACM Transactions on Knowledge Discovery from Data (TKDD); and numerous international conferences, such as the ACM SIGKDD International Conference on knowledge discovery and Data Mining (ACM SIGKDD), the ACM WebConference (WWW), and the IEEE International Conference on Data Mining (ICDM). He regularly serves as a program committee member of many international conferences on data mining, artificial intelligence, and machine learning, such as ACMSIGKDD, ACM SIGIIR, IJCAI, AAAI, ICML, ICDM, CIKM, etc. He is also an associate editor of several refereed journals, such as Electronic Commerce Research and Applications.