Arman Maesumi

arman_maesumi@brown.edu

I am a third year Computer Science PhD student at Brown University, where I am advised by Professor Daniel Ritchie. My work is supported by the NSF Graduate Research Fellowship Program.

I received my BS in computer science from The University of Texas at Austin in 2021, where I did research with Professor Chandrajit Bajaj.

My research interests lie at the intersection of machine learning, computer graphics, and 3D computer vision. In my free time I enjoy creating 3D art, cooking, and playing chess.

I am broadly interested in the interplay between geometry and deep learning, primarily in the context of visual computing:

1) Deep learning for geometry: applying learning-based methods to problems such as shape analysis, deformation, synthesis.

2) Geometry for deep learning: using ideas from differential geometry to augment neural network training and inference; for example, solving variational problems like "what's the smoothest interpolant between two points in latent space?"

Arman Maesumi, Dylan Hu, Krishi Saripalli, Vladimir G. Kim, Matthew Fisher, Sören Pirk, Daniel Ritchie
ACM Transactions on Graphics (Proceedings of SIGGRAPH), 2024
[ project page / pdf (34mb) / arXiv / code / bibtex ]

We learn a denoising diffusion model that can produce multiple types of parametrized noise functions and blend between them spatially, even without spatially-varying training data.

Arman Maesumi, Paul Guerrero, Vladimir G. Kim, Matthew Fisher, Siddhartha Chaudhuri, Noam Aigerman, Daniel Ritchie
SIGGRAPH Asia, 2023 (Conference Track)
[ project page / pdf (30mb) / arXiv / bibtex ]

Given a set of landmark meshes, our method extracts a 2-d deformation subspace from a pretrained non-mesh 3-d generative model, which facilitates exploration of continuous variations between the landmark meshes.

The probability density function and moments (OEIS A279055) of the area of stochastically generated inscribed geometry are derived.

Preliminary findings were presented at TUMC 2017.

In my free time, I enjoy creating 3D renderings and physical simulations using various software. More can be found here. The programs and tools that I use include: Blender, Cinema 4D, RealFlow, Vray, Octane, Arnold, Krakatoa, and more.

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