报告人：ChaojieLi 澳大利亚悉尼新南威尔士大学

报告时间：9月1日9:00

报告地点：腾 讯 ID：155 572 322 密 码：123456

主办单位：数学与统计学院

欢迎光临！

报告摘要：Big data analysis has been widely applied to capturing business opportunities involving human behaviour modelling which enables a more realistic solution for engineering practitioners in energy management problems and other industrial sectors. This talk will present a tutorial on how to model the problems of energy management from a data-driven perspective. Moreover, the efficient computational algorithms for solving complicated optimisation model will be discussed in a large-scale. Game theoretical models will be highlighted for challenging issues including demand side management, demand response of EV management, multi-energy trading mechanism design and distributed renewable energy integration in the smart grid while the corresponding highly efficient computational algorithms will be introduced for solving these challenges in a distributed way.

Dr. Chaojie Li received the B.Eng. degree in electronic science and technology and the M. Eng. Degree in computer science from Chongqing University, China, in 2007 and 2011, respectively, and received the PhD. Degree from RMIT University, Australia in 2017, where he was a research fellow for one and a half years. He worked as a senior algorithm engineer at Alibaba group for one year. At present, He is a senior research associate at UNSW at Sydney. His current research interests include graph representation learning, distributed optimization and game theory in smart grid, big data analysis, and cyber security.