RESEARCH & PUBLICATIONS
I am committed to advancing research through innovative thinking and collaboration with experts across disciplines. In my free time, I focus on developing ideas that contribute to real-world solutions. On this page, I would like to showcase my research and publications.
A Schur-fire Way to Make Matrix Products Coincide
Status:
PUBLISHED
Abstract:
When are the Schur product and the matrix product of two matrices the same? With the help of Morpheus (from The Matrix) and more, we explore this question and find both mathematical answers and math-memes.
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Authors:
Christopher J. Sciortino B.S., M.S.
Josh Hiller Ph.D
Keith Copenhaver Ph.D
A Procedure to Create Seamless PBR Materials using Photogrammetry
Status:
AWAITING PUBLICATION
Abstract:
Photogrammetry is an amazing tool that allows for high-detail 3D models, along with basic color channels for materials to be generated from a series of high-quality pictures. We explore the procedure used to create a seamless PBR material that can be applied to any mesh, using photogrammetry.​
Swift Triangular Matrix Multiplication
Status:
AWAITING PUBLICATION
Abstract:
Researchers are continuing to investigate methods for optimizing matrix multiplication algorithms due to their rapidly increasing computational complexity with larger input sizes. There is a particular class of matrices where zeroes occupy the lower or upper triangle in a matrix. These are known as triangular matrices, and they have a series of interesting properties! This research explores how we can use these unique properties to improve the runtime of an algorithm that calculates the product of triangular matrices. We’ll propose a new algorithm to multiply triangular matrices known as Swift Triangular Matrix Multiplication.​
Why Zeroes Matter
Status:
AWAITING PUBLICATION
Abstract:
In a world where artificial intelligence is thriving, it's critical that we look for ways to optimize the underlying operations that drive it. The Achilles heel to many forms of AI is the ability to manipulate large data sets, which are often represented as grids of numbers, known as matrices or vectors. When presented with a matrix that has zeroes occupying large portions of their rows or columns, it opens up new opportunities to speed up these fundamental operations. We'll explore different ways to approach finding an inverse and calculating the determinant of a matrix.​