In person: February 28th, 2025, 12pm - 1pm (Refreshments will be served!)
To join via Zoom, please use the following link: https://umich.zoom.us/j/97823527756?pwd=H01BbvtuG5q02Wzb8LJvhUnvijlAIe.1

Abstract:
The rapid advancement of large-scale parallel computing created a surge of interest in developing high-fidelity digital twins for complex systems. However, the computational demands for training these models are immense, requiring vast amounts of data. As the spatial and temporal resolution of simulations increases, even data storage becomes a critical bottleneck. This talk presents how low-rank tensor decomposition methods can be used to exploit the structure in large-scale data. We showcase a diverse array of applications, from 3D turbulent Navier-Stokes simulations to Minecraft gameplay videos, demonstrating the versatility and power of these techniques.

Bio: Doruk Aksoy is a 5th year PhD candidate in Aerospace Engineering and Scientific computing at the University of Michigan, working under the supervision of Prof. Alex Gorodetsky. Prior to joining UM, he studied Mechanical Engineering at Bogazici University in Istanbul Turkey. During his PhD, he worked on developing incremental tensor decomposition algorithms to accelerate scientific machine learning through data reduction.