Michael Paciullo

Hi! I’m Michael Paciullo, a recent graduate from NYU, software engineer, and researcher. I have past experience in numerical linear algebra, physical simulation, and computer graphics, and I am always looking to learn and build!

I worked at NYU’s Geometric Computing Lab as an undergraduate, learning about the finite element method and contributing to polysolve, a linear and non-linear solver API. I worked on another matrix factorization project at the Flatiron Institute, the research division of the Simons Foundation.

I am currently working at Standard Practice, building AI for healthcare! Feel free to connect with me on any of the social media links below. For any industry-related inquiries, please contact me via LinkedIn. For academic inquiries, feel free to email me.

news

Jul 17, 2024	First day at Standard Practice AI!
May 22, 2024	Published this website, and looking for new opportunities!
May 15, 2024	Graduated from NYU with a BA in Computer Science and Mathematics.

latest posts

May 22, 2024	Site's built. What's next?

selected publications

Implementing and Benchmarking a Parallel LDL^T Factorization with SYCL

Michael Paciullo, and Geraud Krawezik

2023

Bib PDF

@techreport{ldlt-factor,
  author = {Paciullo, Michael and Krawezik, Geraud},
  title = {Implementing and Benchmarking a Parallel $LDL^T$ Factorization with SYCL},
  institution = {New York University},
  year = {2023},
}

Scaling the Finite Element Method to Small Problems with Dense Linear Solvers

Michael Paciullo, Daniele Panozzo, and Teseo Schneider

In Inquiry , 2024

Bib PDF

@inproceedings{dense-assembly,
  author = {Paciullo, Michael and Panozzo, Daniele and Schneider, Teseo},
  title = {Scaling the Finite Element Method to Small Problems with Dense Linear Solvers},
  booktitle = {Inquiry},
  institution = {New York University},
  year = {2024},
}