Behnam Bahrak

Assistant Professor

Data Science : Lessons learned from analysis of a massive mobile phone dataset

  Halls department, Hall 5
  Thursday, 28 December 2017
  15:30 - 16:30


Mobile phones are ubiquitous. In many countries, including Iran, the coverage reaches 100% of the population, and even in remote villages, it is not unusual to cross paths with someone in the street talking on a mobile phone. Due to their ubiquity, mobile phones have the potential to be used as millions of sensors of their environment and provide us with an extremely rich and informative source of data.
The analysis of the massive mobile phone datasets that are gathered by telecom operators has emerged a decade ago as a side-topic of network theory, but with the increasing availability of such large-scale anonymized datasets, it has grown into a stand-alone field of study. In this talk, we discuss successes, continued challenges, and the valuable lessons that we have learned from analysis of a gigantic indigenous mobile phone dataset.


Behnam Bahrak received his bachelor’s and master’s degrees, both in electrical engineering, from Sharif University of Technology, Tehran, Iran, in 2006 and 2008, respectively. He received the Ph.D. degree from the Bradley Department of Electrical and Computer Engineering at Virginia Tech in 2013. He is currently an assistant professor of Electrical and Computer Engineering department at the University of Tehran.