学术报告第201538期

报告题目：Case Studies in Big-Data and Decision  Science

报 告 人：叶荫宇 教授（美国斯坦福大学）

报告时间：2015年7月3日下午4:00

报告地点：南一楼中311室

邀 请 方：“多谱信息处理技术”国家级重点实验室

Abstract：

We  present three case studies driven by online, uncertain and massive data. We show  how analytical decision models and numerical algorithms can be used to achieve  efficiency and optimality

1)      The personal vehicle is expected to evolve  into a device distinct from what exists today. In particular, plug-in electric  vehicles (PEV) will have flexible charging options, and may be capable of  transmitting electricity back to the grid, or discharging. We construct an  automated algorithm/mechanism for a fleet of PEVs that efficiently organizes  distributed electricity utilization.   

2)      Information or prediction market is a  place where information is aggregated via market for the primary purpose of  forecasting events, or the probability that an event will occur. We design a  mechanism to organize such a market effectively.

3)      Service location based on geographic data,  where we provide a fast algorithm to partition a convex region on a region into  multiple sub-regions such that each piece has two density measurements  equalized. Applications include redistricting, surveillance covering, vehicle  routing, service region drawing, Big-Data and Decision  Science