Using Attractor Dynamics to Understand Self-Organization in Wiki Work

Martina Balestra

Abstract: Online peer-production is characterized by complex work dynamics across scale. But the relationship between behavior at the localized and collective levels is under-studied and, as a result, the emergence of self-organization in such systems is not well understood. In this talk, I will give an overview of a method that my collaborators and I have adapted from dynamic systems theory that centers on detecting the interdependencies between different types of specialized work to characterize emergent work paradigms. We use this approach to identify and characterize six emergent work dynamics in Wikipedia. Our results show how the underlying relationships between different types of edits influence the work that people do from one edit interval to the next, and inform the collective production of an article. At the end of the talk I will discuss a few ways in which these methods could be used to help us to understand issues relevant to cities.

Bio: Martina Balestra is a Smart Cities postdoctoral research associate at NYU CUSP. She completed her PhD from NYU in 2019, M.S. from Cornell University in 2014, and B.S. from the Olin College of Engineering in 2010. From 2010 to 2012 she worked at the MITRE Corporation as a Systems Engineer. Her research interests are mainly related to computational social science, collective behavior, dynamical systems, human computer interaction, and machine learning.

Securing Infrastructures of Smart Cities

Chenglu Jin

Abstract: Infrastructures like power grids, water treatment systems, and public transportation systems are the foundations for smart cities. However, the security of such systems is usually an afterthought. In this talk, we will talk about how to use cryptographic methods to secure the critical infrastructures in smart cities in an efficient way. In particular, I will present how to secure the systems under the attacks initiated from sensors, controllers, and networks. 

Chenglu Jin is a smart cities postdoctoral associate at NYU CUSP. He obtained his Ph.D. degree from the University of Connecticut in 2019. Before that, he got his master degree from NYU in 2014. During his Ph.D. study, he spent a summer in the Singapore University of Technology and Design to work with world-class cyber-physical system testbeds. His research interests lie in the areas of hardware security, cyber-physical system security, applied cryptography, and security in general.

Wireless Technologies for Urban Applications

Kim Mahler

Kim Mahler received the M.Sc. degree with honors and the Dr.-Ing. degree (magna cum laude) from the Technical University of Berlin, Germany, in 2010 and 2016. He also received the M.A. degree from the Berlin University of Arts/University of St. Gallen in 2014. From 2010 until 2019, he was with the Wireless Communications and Networks department at Fraunhofer Heinrich Hertz Institute HHI in Berlin, Germany. His research interests involve vehicular communications, user-centric 5G developments and millimeter wave technology for drone applications.