Publications & Preprints
"Topologically-Informed Atlas Learning"
ICRA 2022 (Acceptance 43.1%)
Thomas Cohn, Nikhil Devraj, Odest Chadwicke Jenkins
[ Paper ] [ Project Page ] [ Conference Presentation (ICRA 2022) ] [ Code ]
Topologically-Informed Atlas Learning extends manifold learning to handle data from topologically non-trivial manifolds, by partitioning the manifold into regions with no holes and separately embedding each region. Thus, it constructs an atlas of coordinate charts, preserving both the local and global topology. We use our atlas learning approach to reconstruct human motion and learn kinematic models for articulated objects.
"TSBP: Tangent Space Belief Propagation for Manifold Learning"
Robotics and Automation: Letters (RA-L) + IROS 2020
Thomas Cohn, Odest Chadwicke Jenkins, Karthik Desingh, Zhen Zeng
[ Paper ] [ Project Page ] [ Conference Presentation (IROS 2020) ] [ Code ]
TSBP is a neighborhood graph denoising technique to make manifold learning more robust to data sparsity and noise. We use belief propagation to estimate tangent spaces, and use that information to remove false edges. We apply our technique to simulated robot sensing data and tactile data.
Coordinate Chart Particle Filter for Deformable Object Pose Estimation
[ Project Page ] [ Code ]
By learning a low-dimensional representation of deformable objects with manifold learning, we can then estimate their pose with a particle filter, where particles are constrained along the manifold to reduce the dimension of the search space.
EECS 442 (Computer Vision) Course Projects
[ Project Page ]
Assorted class projects for EECS 442 at the University of Michigan, including fitting homography transformations to warp and combine images, and performing semantic image segmentation with neural networks.
Interactive Drum Lights
[ Project Page ]
A maker project that detects drum notes with a piezoelectric sensor, in order to control LEDs.
I've partially or completely typset my lecture notes for several of the math classes I have taken. I've included links to Google Drive folders containing the PDFs, and links to the git repositories containing the LaTeX source files. (Classes are listed in reverse chronological order.)
- PDF Files LaTeX Source Math 635 (Riemannian Geometry) Taught by Professor Alejandro Uribe in 2021.
- PDF Files LaTeX Source Math 591 (Differentiable Manifolds) Taught by Professor Alejandro Uribe in 2020.
- PDF Files LaTeX Source Math 493 (Abstract Algebra/Group Theory) Taught by Professor Andrew Snowden in 2019
- PDF Files LaTeX Source Math 396 (Honors Analysis II) Taught by Professor David Barrett in 2019
- PDF Files LaTeX Source Math 565 (Graph Theory) Taught by Dr. Danny Nguyen in 2018
- PDF Files LaTeX Source Math 395 (Honors Analysis I) Taught by Professor David Barrett in 2018
- PDF Files LaTeX Source Math 217 (Proof-Based Linear Algebra) Taught by Dr. David Fernández Bretón in 2016