David R. Palmer

Postdoctoral Fellow
Harvard SEAS
Pierce Hall 307A
        
dpalmer@seas.harvard.edu
David R. Palmer

I am a postdoc in the Mahadevan Lab at Harvard. I am interested in the geometry and dynamics of topological defects in optimization problems. More broadly, I work at the intersection of applied geometry, optimization, and physics. I will be on the academic job market in fall 2024.

I completed my PhD in the Geometric Data Processing Group at MIT, working with Professor Justin Solomon. My work applied convex relaxation techniques to simplify challenging geometric optimization problems featuring topological barriers. I was lucky enough to work with many excellent collaborators, including outstanding undergraduates.

Prior to my PhD, I studied math at Cambridge and computer science at Harvard. I have interned at Pixar Research, where I helped build geometry and physics simulation tools for artists, and at Flagship Labs, where I was in the inaugural class of AI Fellows.

In my spare time, I enjoy singing, improv comedy, baking breads and pastries, and (in a prior life) keeping bees.

I am grateful to be supported by the NSF Mathematical Sciences Postdoctoral Research Fellowship. While at MIT I was generously supported by the Hertz Fellowship and the MathWorks Fellowship.


Publications

Homotopy Classification of Knotted Defects in Bounded Domains
Homotopy Classification of Knotted Defects in Bounded Domains
Yuta Nozaki, David Palmer, Yuya Koda
(in submission)
ArXiv
Lifting Directional Fields to Minimal Sections
Lifting Directional Fields to Minimal Sections
David Palmer, Albert Chern, Justin Solomon
SIGGRAPH 2024, Denver
Paper | ArXiv
Relaxing Topological Barriers in Geometry Processing
Relaxing Topological Barriers in Geometry Processing
David Palmer
PhD Dissertation, MIT Department of Electrical Engineering and Computer Science, 2023
Thesis
DeepCurrents: Learning Implicit Representations of Shapes with Boundaries
DeepCurrents: Learning Implicit Representations of Shapes with Boundaries
David Palmer*, Dmitriy Smirnov*, Stephanie Wang, Albert Chern, Justin Solomon
(* denotes equal contribution)
CVPR 2022, New Orleans
Paper | ArXiv | Project Page | Video
Maximum a Posteriori Inference of Random Dot Product Graphs via Conic Programming
Maximum a Posteriori Inference of Random Dot Product Graphs via Conic Programming
David Wu, David Palmer, Daryl DeFord
SIAM Journal on Optimization 2022
ArXiv
Sum-of-Squares Geometry Processing
Sum-of-Squares Geometry Processing
Zoë Marschner, Paul Zhang, David Palmer, Justin Solomon
SIGGRAPH Asia 2021, Tokyo
Paper | ArXiv | Video
Frame Field Operators
Frame Field Operators
David Palmer, Oded Stein, Justin Solomon
Symposium on Geometry Processing 2021, Online
Paper | ArXiv | Code | Video
Hexahedral Mesh Repair via Sum-of-Squares Relaxation
Hexahedral Mesh Repair via Sum-of-Squares Relaxation
Zoë Marschner, David Palmer, Paul Zhang, Justin Solomon
Symposium on Geometry Processing 2020, Online
Paper | PDF | Code | Video
Algebraic Representations for Volumetric Frame Fields
Algebraic Representations for Volumetric Frame Fields
David Palmer, David Bommes, Justin Solomon
ACM Transactions on Graphics 2020
Paper | Code
Toward Computing Extremal Quasiconformal Maps via Discrete Harmonic Measured Foliations
Toward Computing Extremal Quasiconformal Maps via Discrete Harmonic Measured Foliations
David Palmer
AB Thesis in Computer Science 2015, Harvard University
PDF