Ioannis “Yannis” Kevrekidis is an expert in modeling and dynamic behavior of complex systems who pioneered the equation-free approach to complex systems modeling, which incorporates data mining and machine learning techniques. His models have aided scientists in studies about how clusters of neurons synchronize; the swarming patterns of insects; the development of bubbles in fluidized reactors; and the phenomenon of urban sprawl.

Kevrekidis’s work focuses on modeling and algorithm development toward the study of complex dynamics. His techniques and applications have transformed the ways in which scientists and engineers perform computer-assisted modeling of such complex systems. Kevrekidis aims to improve healthcare by developing computer models to help oncologists study patient outcomes as well as how cancer cells move and interact with other cells. He is currently adding on to his equation-free approach, linking it with modern data mining and machine learning techniques in what could be called an “equation-free and variable-free” approach.

Kevrekidis joined Johns Hopkins University as a Bloomberg Distinguished Professor in 2017 from Princeton University.