[PAST EVENT] Managing and Making Sense of Big Data From Urban Networks
Managing and Making Sense of Big Data From Urban Networks
Yanhua Li, WPI
The urban network infrastructure has undergone a fast development and expansion over recent years, which increasingly generates an immense amount of big data, such as human mobility data, human transaction data, regional weather data, and etc. These heterogeneous urban network data bring new challenges in data management, and convey rich information about a city and can enable intelligent solutions to solve various urban challenges, such as urban facility planning, air pollution, etc. In this talk, I present my work on managing and analyzing these urban network data to enable computationally efficient data queries and to improve peoples‘ life quality and city operation systems. A trajectory aggregate query, as a fundamental functionality for measuring urban trajectory data, aims to retrieve the statistics of trajectories passing a user-specified spatio-temporal region. The first work introduces random index sampling framework, that provides approximate answer to trajectory aggregate queries, with guaranteed error bound. In the second work, by analyzing a large-scale electric taxi trajectory data, I investigate an emerging and challenging question to urban planners and electric utility companies, namely, how to strategically deploy the charging stations and charging points in an urban area to minimize the average time to the nearest charging station, and the average waiting time for an available charging point.
Yanhua Li is an Assistant Professor with Computer Science Department and Data Science Program at Worcester Polytechnic Institute (WPI). Before joining WPI, Dr. Li worked as a Post-Doctoral Researcher in Computer Science and Engineering Department at University of Minnesota, Twin Cities, and worked as a researcher in HUAWEI Noah's Ark LAB at Hong Kong. He obtained two Ph.D. degrees in computer science and electrical engineering from University of Minnesota, Twin Cities in 2013, and Beijing University of Posts and Telecommunications in 2009. His broad research interests are in analyzing, understanding, and making sense of big data generated from various complex networks in many contexts, including urban computing, large-scale network data sampling, measurement, and cyber-physical systems. Dr. Li has interned in Bell Labs in New Jersey, Microsoft Research Asia, and HUAWEI research labs of America. He is a senior member of IEEE and a member of ACM.