Prof. Boaz LernerAssociate Professor and Head of the Machine Learning & Data Mining Lab
Department of Industrial Engineering and Management, Ben-Gurion University of the Negev, Beer Sheva, Israel
Speech Title: Utilizing digital traces of mobile phones for understanding social dynamics in urban areas
Abstract: Understanding land use in urban areas, from the perspective of social function, is beneficial for a variety of fields, including urban and highway planning, advertising, and business. However, big cities with complex social dynamics and rapid development complicate the task of understanding these social functions. In this paper, we analyze and interpret human social function in urban areas as reflected in cellular communication usage patterns. We base our analysis on digital traces left by mobile phone users, and from this raw data, we derive a varied collection of features that illuminate the social behavior of each land use. We divide space and time into basic spatiotemporal units and classify them according to their land use. We categorize land uses with a leveled hierarchy of semantic categories that include different levels of detail resolution. We apply the above methodology to a dataset consisting of 62 days of cellular data recorded in nine cities in the Tel Aviv district. The methodology proved beneficial with an accuracy rate ranging from 84% to 91%, dependent on land-use label resolution. In addition, analyzing the results sheds light on some of the limitations of relying solely on cellular communication as a data resource. We discuss some of these problems and offer applicable solutions.
Biography: Boaz Lerner received a B.A. degree in Physics and Mathematics from the Hebrew University, Israel, in 1982 and a Ph.D. degree in Computer Engineering from Ben-Gurion University, Israel, in 1996. He was a researcher at the Neural Computing Research Group at Aston University, Birmingham, UK and the Computer Laboratory of Cambridge University, Cambridge, UK, and now is an Associate Professor in the Department of Industrial Engineering and Management at Ben-Gurion University, Israel, where he established in 2007 and has since headed the Machine Learning and Data Mining Lab. His current interests include machine learning and data mining approaches to data analysis and their application to real-world problems especially in precision medicine and precision agriculture. Lerner has supervised more than 50 graduate students and has published more than 100 papers in journals and conference proceedings. He is the founder and CTO of Panacea, bringing the next generation of clinical trials.