Data just keeps getting bigger.

With the growing size of data analysis problems, we need faster and more efficient methods to learn effectively. Often this means limiting memory overheads, or parallelizing previously sequential computations. Regardless of the requirements, one thing is clear; data tasks are not getting any smaller.

I researched for years at the High Performance Computing and Graph Analytics Laboratory at RPI in Troy NY before obtaining my PhD in July of 2023. During this time I worked with the Department of Energy and Sandia National Labs as well as with many notable researchers from the fields of high performance computing, network science, and machine learning to create efficient primitives for large-scale graph analysis. I have publications across SIAM and Nature journals, as well as conference submissions at SIAM, Complex Networks, and AAAI. I would love to bring this experience to any interesting projects you may have!