Yannis G. Kevrekidis

Yannis G. Kevrekidis is a Hans Fischer Senior Fellow at the Technical University of Munich (TUM-IAS), hosted by Katharina Krischer. He holds a joint appointment at Johns Hopkins University’s Department of Chemical and Biochemical Engineering. His research focuses on complex systems modeling, nonlinear dynamics, and equation-free methods, integrating machine learning with multiscale computations.

Education: B.Sc. in Chemical Engineering from National Technical University of Athens; Ph.D. from University of Minnesota, advised by Rutherford Aris and Lanny Schmidt. He has held positions at Los Alamos National Laboratory as a Director’s Fellow and has been a faculty member at Princeton University since 1986, where he contributed to computational dynamics and pattern formation studies.

Research Interests: Pioneered the equation-free approach for multiscale systems, bridging microscopic simulations with macroscopic analysis. Recent work emphasizes combining data-driven methods (e.g., manifold learning) with traditional modeling. Key themes include complex systems, bifurcation analysis, and computational neuroscience.

Awards: Humboldt Prize (1998), Packard Fellowship (1988), and numerous honors from AIChE and SIAM. Currently affiliated with TUM-IAS Focus Group on Complex Systems Modeling and Computation.

Key Collaborations: Includes interdisciplinary projects with experimentalists (e.g., G. Ertl at Fritz Haber Institute) and computational mathematicians (e.g., Ronald Coifman on manifold learning).