MAE Seminar: Reconcilable Differences

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Yannis Kevrekidis, Ph.D.
Bloomberg Distinguished Professor
Department of Chemical and Biomolecular Engineering, Department of Applied Mathematics and Statistics, Department of Urology
Johns Hopkins University

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Abstract: I will discuss several old and new examples of extracting dynamic models from data using techniques from manifold learning/machine learning. I will then focus on the problem of matching different models of the same data/phenomenon: the construction of data-driven diffeomorphisms that map different realizations of the same "truth" to each other. I will discuss several different cases: matching models across scales and across fidelities, matching physical models with ML ones and matching different neural network models. I will also describe a useful tool for the data-driven construction of such "mirrors," matching systems to each other: a local conformal auto-encoder.

Bio: Yannis Kevrekidis is the Bloomberg Distinguished Professor in the Departments of Chemical and Biomolecular Engineering, and Applied Mathematics and Statistics and in the Johns Hopkins University School of Medicine’s Department of Urology.

Kevrekidis is a member of the National Academy of Arts and Sciences and has been a Packard Fellow, an NSF Presidential Young Investigator and a Guggenheim Fellow. He holds the Colburn, the Wilhelm, and the Computing in Chemical Engineering awards of the AIChE; the Crawford Prize and the W.T. and Idalia Reid Prize of SIAM; and a Senior Humboldt Prize. He has been the Gutzwiller Fellow at the Max Planck Institute for the Physics of Complex Systems in Dresden and a Rothschild Distinguished Visitor at the Newton Institute at Cambridge University. He is currently a senior Hans Fischer Fellow at IAS-TUM in Munich and an Einstein Visiting Fellow at FU/Zuse Institut Berlin. In 2015, he was elected a corresponding member of the Academy of Athens. He also holds a career Teaching Award from the school of engineering at Princeton University.

Kevrekidis earned a bachelor’s degree in chemical engineering at the National Technical University in Athens and a doctorate form the University of Minnesota’s Department of Chemical Engineering and Materials Science. He arrived at Johns Hopkins in 2017 after serving as the Pomeroy and Betty Perry Smith Professor in Engineering at Princeton University, where he was professor of chemical and biological engineering, senior faculty in applied and computational mathematics and associate faculty member in mathematics. 

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