Dr. Craig Grosch
Research Consultant, MSU Institute for Cyber-Enabled Research
1450 Biomedical Physical Sciences Building
grosscra@msu.edu
Bio: Dr. Craig Grosch is a Research Consultant at the Institute for Cyber-Enabled Research. Before joining ICER, Dr. Grosch received his Ph.D. in applied mathematics from Michigan State University, where he studied compressive sensing, sparse Fourier transforms, and algorithms for solving high-dimensional partial differential equations.
Dr. Grosch also has experience with analysis of datasets related to transit, demographics, and socioeconomic indicators from work with partners at Johns Hopkins University as well as experience linking computational fluid dynamics solvers with machine learning workflows from work at Lawrence Livermore National Laboratory.
Research and technical skills:
- Mathematical data analysis
- Prototyping and analysis of fast algorithms
- Data processing and machine learning pipelines and workflows
- Technical expertise in Python, MATLAB, R, C/C++, Mathematica, shell scripting
- Scientific expertise in numerical partial differential equations, in particular spectral and finite element methods; compressive sensing; sparse data analysis; dimensionality reduction; high-dimensional function learning; signal processing; and fast Fourier transforms
Selected publications:
- Gross, C., Iwen, M., Kämmerer, L. et al. Sparse Fourier transforms on rank-1 lattices for the rapid and low-memory approximation of functions of many variables. Sampl. Theory Signal Process. Data Anal. 20, 1 (2022).
- Gross, C., Iwen, M.A., Kämmerer, L. et al. A deterministic algorithm for constructing multiple rank-1 lattices of near-optimal size. Adv Comput Math 47, 86 (2021).