Research

 

I am interested in stochastic processes and modeling in biological systems, the interplay of structure and dynamics in networks, and Bayesian inference and inverse problems. My work relies heavily on linear algebra, non-equilibrium thermodynamics, optimization, and computational topology.

I currently work on variational inference problems, noise propagation in biological networks, self-organizing edge flows, and functional form game theory (with exciting applications to multi-agent training and visualization). My published work includes the study of extinction events and large deviations, geometric solutions to moment closure problems, and the characterization of network structure in tournaments. I also work on data visualization techniques that summarize the interactions of competing agents.

 
 

Highlights

 

The Network HHD: Quantifying Cyclic Competition in Trait Performance Models of Tournaments

A. Strang, K. C. Abbott, P. J. Thomas (SIREV 2021) 

Solutions to the Minimum Variance Problem using Delaunay Triangulation

A. Strang (SIAM Journal of Discrete Mathematics 2021) 

The Network HHD: Quantifying Cyclic Competition in Trait Performance Models of Tournaments

A. Strang, K. C. Abbott, P. J. Thomas (SIREV 2022) 

Solutions to the Minimum Variance Problem using Delaunay Triangulation

A. Strang (SIAM Journal of Discrete Mathematics 2021) 

Principal Trade-off Analysis

A. Strang, D. SeWell, A. Kim, K. Alcedo, D. Rosenbluth (arXiv 2022)

Sparse Reconstructions from Few Noisy Data:
Analysis of Hierarchical Bayesian
Models with Generalized Gamma Hyperpriors.

D. Calvetti, , M. Pragliola, E. Somersalo, A. Strang (Inverse Problems 2021)

Publications