Adriana Compagnoni: Modeling Language Design for Complex Systems Simulation

The 2013 Chemistry Nobel Prize winners, Karplus, Levitt, and Warshel, were instrumental in constructing the first computational models able to predict the effects of chemical reactions, by combining classical Newtonian physics and quantum physics. Their contribution was a dramatic demonstration of the long-term trend of computational models becoming an essential tool in engineering and science. These models are used to predict the weather and climate change, estimate drug doses in laboratory experiments, anticipate the behavior of the stock market, and represent signal transduction pathways, to name a few examples. They are part of everyday life from recreation to medicine, from finances to education.

Despite its broad spectrum of applications and the vast number of computational models built, model construction remains primarily an ad-hoc activity, where an expert or small team creates a piece of software describing the behavior of the agents partaking in a specific real world scenario being represented.

An alternative scenario consists of a modeling platform based on a specification language where the user builds a model by describing agents' behavior and attributes.

In this talk, I will share our experience in developing a computational modeling platform, its application to simulating antibacterial surfaces, and the fascinating road ahead.