Algorithms & Frameworks
Production-ready methods that power inversions, data fusion, and interactive products.
O(n2.5) Kronecker Methods for Large Inverse Problems
GMD, 2013Reduces dominant multiplications by exploiting Kronecker structure in state/observation operators, enabling materially larger state vectors and faster UQ on commodity hardware. Demonstrated on continental-scale CO₂ flux estimation with practical implementation guidance.
Sparse×Sparse Covariance Multiplication for Inversions
GMD Discuss., 2016Memory-aware, parallel sparse-sparse multiplication tailored to inversion covariances/Jacobians, improving throughput and cache behavior in production pipelines for trace-gas estimation. Preprint details hybrid parallelization and triangular/dense-target variants for HQHᵀ patterns.
Sign-Aware Jaccard Correlograms & PSD Kernels
Technical noteA bounded, scale-invariant similarity for mixed-sign signals that cleanly separates **phase (sign)** and **magnitude** disagreement. The induced negative-type distance yields valid PSD kernels for kriging/GPs and interpretable maps that distinguish phase vs. amplitude anisotropy.
Census-Tract Agent-Based Decarbonization Model
DocsTract-level ABM simulating household adoption of EVs, efficiency upgrades, and solar under configurable policy instruments (income targeting, stacking, timing). Integrates ACS demographics and grid pathways, reporting equity, cost-effectiveness, and leverage metrics across parallel runs.
Bayesian / Geostatistical Inversions (Fortran Core)
CodeFortran-based inversion core implementing covariance construction, H·Q·Hᵀ operators, and parallel drivers for large atmospheric problems. Includes batch/parallel scripts and modular source layout for operational deployment in production pipelines.