DDM Analytics works at the intersection of data, physics, and the field. Every engagement draws on the same foundation: rigorous data practice, machine learning constrained by governing physics, agentic systems that act on what the models know, and equipment we operate ourselves.
Custom machine learning for geoscience and engineering problems: physics-informed neural networks that embed governing equations directly into training, and agentic AI systems with autonomous reasoning, designed for sparse, noisy, and incomplete datasets.
Multi-modal fusion of remote sensing, field measurements, and historical records into coherent geospatial intelligence and risk products that respect the underlying physics.
Digitization, structuring, and quality control of historical field and operational records: archives become analysis-ready datasets, the raw material for physics-informed modeling.
Drone-based surveying with high-precision sensors and advanced surveying equipment, including ground-truth campaigns that validate models against the physical world.
Production data processing and analytics pipelines.
DDM Analytics is a research and development company registered in the System for Award Management (SAM.gov) for federal financial assistance. We pursue federally funded research and development in collaboration with university research groups.
Current research focus areas
Rare earth element exploration in greenfield and brownfield settings, supported by physics-informed neural networks and agentic AI workflows.
Regional liquefaction hazard mapping using physics-informed machine learning.
Converting historical field and operational records into analysis-ready datasets for predictive modeling.
This work is supported in-house by multiple GPU workstations for model development and a professional drone fleet with high-precision sensors and surveying equipment for field data acquisition and model validation.
Have a dataset nobody trusts, an archive nobody reads, or a problem nobody has modeled?