What is Predictive Data Science?

Predictive data science is a convergence of the fields of Data Science and Computational Science & Engineering.

Predictive data science is needed for high-consequence applications across science, engineering and medicine, where machine learning approaches based on data alone are insufficient.

predictive data science: connvergence of Data Science and Computational Science & Engineering.

Resources on Predictive Data Science

Download slides [PDF] from Prof. Willcox's invited talk at the 2019 International Congress on Industrial and Applied Mathematics (ICIAM)

Watch [short video] Prof. Willcox explain the importance of Predictive Data Science

Watch the full invited ICIAM talk on Predictive Data Science

Learn more about Predictive Data Science at the Oden Institute

Papers by the Willcox Research Group in Predictive Data Science:

  1. Kramer, B. and Willcox, K., Nonlinear model order reduction via lifting transformations and proper orthogonal decomposition. AIAA Journal, Vol. 57 No. 6, pp. 2297-2307, 2019.

  2. Qian, E., Kramer, B., Marques, A. and Willcox, K., Transform & Learn: A data-driven approach to nonlinear model reduction. In Proceedings of AIAA Aviation Forum & Exhibition, Dallas, TX, June 2019.
  3. Swischuk, R., Mainini, L., Peherstorfer, B. and Willcox, K., Projection-based model reduction: Formulations for physics-based machine learning, Computers and Fluids, Vol. 179, pp. 704-717, January 2019.
  4. Peherstorfer, B. and Willcox, K., Data-driven operator inference for nonintrusive projection-based model reduction, Computer Methods in Applied Mechanics and Engineering, Vol. 306, pp. 196-215, 2016.
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