Brandon Gusto, Ph.D.
Principal Research Scientist
From undersea acoustics to thermonuclear supernovae. Dr. Gusto specializes in computational physics, optimization, and scientific software.
About
Dr. Gusto is a Principal Research Scientist and Department of Defense SMART Scholar. His expertise spans modeling and simulation, optimization algorithms, software development, machine learning, and signal processing.
His research goes beyond developing new algorithms. Dr. Gusto architects and delivers production-quality scientific software built for high performance computing. This software often depends on MPI, performance portable GPU libraries, and popular scientific computing libraries.
Expertise
Scientific Computing
Development of scalable, high-performance software for numerical simulations and data analysis pipelines.
Multifidelity Bayesian Optimization
Novel optimization schemes combining multi-objective optimization with multifidelity surrogate models for efficient design space exploration.
Computational Fluid Dynamics
High-fidelity CFD simulations for engineering applications.
Acoustic Signal Processing
Algorithm development for acoustic analysis, beamforming, source localization, and noise characterization in complex environments.
Skills
Projects
Selected research projects and software contributions demonstrating applied expertise.
Multi-Fidelity Bayesian Optimization
Optimization + MLExtended random embedding Bayesian optimization to leverage multi-fidelity data sources for high-dimensional problems. Introduced a multi-armed bandit approach for intelligent embedding selection using Thompson sampling.
DDT in Type Ia Supernovae
CFD + MLLarge-scale DNS campaign (27,791 simulations) exploring deflagration-to-detonation transition in thermonuclear supernovae. Developed neural network classifiers achieving 97%+ accuracy for predicting detonation formation from hotspot configurations.
Hybrid Adaptive Multiresolution
CFD + HPCNovel mesh adaptation method combining block-structured AMR with multiresolution analysis for reactive flow simulations. Achieves significant speedups through solver-adaptive techniques that replace expensive calculations with interpolation in smooth regions.
Publications
- "A hybrid adaptive multiresolution approach for the efficient simulation of reactive flows." Computer Physics Communications, vol. 274, 2022.
Contact
Interested in collaboration or have questions about Dr. Gusto's research? Get in touch.
brandonlgusto@protonmail.com