I had the pleasure of completing a Ph.D. in Electrical Engineering at ETH Zurich. My dissertation covered two research problems in the realm of human mobility and emerging graph-theoretic properties.

Human mobility and mobile communication

  1. The first part coomprises an analytical model for the emergence of connected clusters mobile wireless network scenarios. You can imagine these scenarios to be people living in a city that carry a smartphone that is able to connect to all other people within a fixed radius. We were able to validate the accuracy of our model based on traces from people visiting a conference as well as people riding taxi cabs in San Francisco and Shanghai.
  2. The second part offers an analytical comparison of paradigms to leverage these communication opportunities for end-to-end communication between two arbitrary people. This analyis was novel as it was the first to explicitly consider the connected crowds predicted by the model introduced in the first part of the dissertation.

From 2011 until 2012, I transitioned to machine learning and worked as a senior researcher at the Paris Lab of Technicolor. I worked with Laurent Massoulié and Marc Lelarge on distributed inference systems based on Bayesian networks.

Machine learning for movie recommendations – preserving privacy

At Technicolor, we designed and evaluated a distributed inference algorithm to provide recommendations for media such as movies or TV shows. Thanks to the Netflix Prize, we had ample data to evaluate our algorithm with. As opposed to the objective of the Netflix Prize, however, our goal was to offer provable privacy guarantees to all users. To accomplish this, we relied on two core tools. First, belief propagation on Bayesian networks allowed us to distribute computations. Second, differential privacy provided the provable privacy guarantees we were looking for. Differential privacy was originally developed at Microsoft Research; more recently, Apple has picked up differential privacy as a research focus.

Human mobility vs. network mobility

From August 2012 until January 2014, I was a senior researcher College of Information and Computer Sciences of the University of Massachusetts (UMASS) in Amherst, MA, where we studied the mobility of people -- with a twist. Rather than just collecting GPS location data, we compared the trajectory of the logical location of the invidiual on the global Internet with their geographic location on planet earth. I led the Nomad Log projectto study the mobility of individuals via an Android app aptly named Nomad Log. The results of this study have been published at SIGCOMM 2014.

Selected publications

Zhaoyu Gao, Arun Venkataramani, James F. Kurose, and Simon Heimlicher:
Towards a Quantitative Comparison of Location-Independent Network Architectures
ACM Sigcomm 2014, Chicago, August 2014.

Simon Heimlicher and Kavé Salamatian:
Globs in the Primordial Soup—The Emergence of Connected Crowds in Mobile Wireless Networks
★ Best Paper Award ★
ACM MobiHoc 2010, Chicago, September 2010.
PDF | Extended PDF

Please refer to the complete list of publications for further information.