Complex Networks
Dima Fayyad
Applications of AI in the context of complex networks are ubiquitous in our world and throughout our daily lives. We see them in recommendation systems when our friends suggest a restaurant to visit and in fraud detection systems that flag anomalous financial transactions.
They are prevalent in drug discovery systems when searching for a match in the 3D structure of proteins and epidemic modeling systems used to predict the spread of Covid-19. We even see them in the social networks we use for online dating or to make new friends.
Complex networks can model so many human-based processes that the applications of AI in practice are innumerable. The Institute for Experiential AI works with network scientists to develop predictive and descriptive models to help understand the phenomena associated with these types of networks.
