Carmel Fiscko

Biography

Carmel Fiscko’s research interests are in controls, reinforcement learning, data science, optimization, and network theory, with applications to understanding influence mechanisms in connected multi-agent systems. Fiscko’s research aims at understanding such influence mechanisms in a networked society. Her goal is to characterize how influencers impact the decisions of individuals, and as a result, manipulate the direction of group behavior. The phenomenon described by this research goal arises across many domains critical to human interactions. Social media is an obvious example, where websites promote desirable content and moderators control for spam and harassment. Finance is another relevant domain, where massive multi-layered networks of consumers, businesses, banks, and governments exchange transactions. Recent instability in the cryptocurrency markets demonstrates perfectly how local agents act selfishly and at odds with regulations if any exist. Further examples can be found in power grids and cyber-physical systems, where networks of power producers and consumers must be regulated for stability subject to real-world constraints of heterogeneous infrastructure. These are critical problems that could benefit from understanding processes that induce outcomes for social good and prevent malicious actors from causing harm.