Program on Numerical Analysis in Data Science

Novel and efficient numerical techniques are undeniably needed to process and interpret massive data sets generated by modern technological and scientific developments; e.g., surveillance, space observation, medical data. Three overlapping themes in emerging numerical methods for this program are: (i) analysis of deep learning (DL) techniques; (ii) finding underlying dynamics of time dependent data sets; (iii) Randomized Numerical Linear Algebra (RandNLA) algorithms.

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Visiting Research Fellows
Post-Doctoral Fellows
Participation in Workshops