General-Kernel Augmented Lagrangian Methods for GPU-Accelerated Nonlinear Programming
A general-kernel augmented-Lagrangian framework for large-scale, degenerate nonlinear programs on GPUs.
Research Projects
Selected research projects, newest first. Each page links to the associated papers, talks, slides, and code.
GPU-Accelerated Bregman Douglas–Rachford Splitting for Discrete Optimal Transport
A scalable first-order solver for large-scale discrete optimal transport on the GPU.
Enabling Workforce Intelligence through Occupational Taxonomy Alignment
Aligning occupations across taxonomies via Fused Gromov–Wasserstein over a global task meta-network.
Wasserstein Motifs: Optimal Transport for Ecological Network Alignment
A rigorous, scalable optimal-transport framework for aligning food webs and extracting interaction backbones.
Networked Competitive Bivirus SIS Models: The Discrete-Time Case
Equilibrium analysis and simulation of two competing viruses spreading over networks in discrete time.