Ioannis Kevrekidis

Ioannis Kevrekidis is a Bloomberg Distinguished Professor at Johns Hopkins University, holding appointments in the Department of Chemical and Biomolecular Engineering, Applied Mathematics and Statistics, and the Department of Urology in the School of Medicine. A pioneer of equation-free computation, his research bridges computational science, machine learning, and complex systems modeling. He has contributed foundational work in multiscale computations, nonlinear dynamics, and data-driven discovery of physical laws. His interdisciplinary efforts span protein folding, electrochemistry, reaction engineering, and climate science.

Education: BS in Chemical Engineering from National Technical University of Athens (1977), PhD in Chemical Engineering from University of Minnesota (1981). Previously served as Pomeroy and Betty Perry Smith Professor of Engineering at Princeton University until joining JHU in 2017.

Research focuses on developing novel algorithms for modeling complex systems, integrating machine learning with traditional computational methods. Notable contributions include the equation-free approach, which enables macroscopic modeling without explicit equations, and recent advancements in combining this with variable-free machine learning techniques.

• Recent work includes AI-driven discovery of climate tipping points, protein folding simulations, and cancer treatment optimization.
• Recipient of National Academy of Engineering membership, Packard Fellowship, and numerous AIChE/SIAM awards.
• Active collaborations with institutions globally, including Max Planck Institute, Yale University, and Zuse Institut Berlin.

Teaching excellence recognized through Princeton’s career Teaching Award. Currently a Senior Hans Fischer Fellow at Technical University of Munich and Einstein Visiting Fellow at Freie Universität Berlin.