Columbium Technologies LLC is a Cincinnati-based research, design, and product development company. We bridge the gap between abstract machine learning and physical reality.
The core thesis: Domain knowledge and statistical rigor are complements, not substitutes.
We reject the “black-box” application of generic ML pipelines to scientific problems. Instead, we architect models where physical constraints are structurally encoded—via specialized kernel selection, tailored likelihood functions, and conservation-law priors. The result is a system that is physically grounded and robust by design.
Core Competencies
| Domain | Methodology & Stack |
|---|---|
| Surrogate Modeling | Sequential and adaptive learning, Bayesian Neural Networks, Uncertainty Quantification |
| Experimental Design | Sequential/Adaptive DOE, Expected Improvement (EI), Knowledge Gradient |
| Research Automation | Multi-agent LLM systems, RAG for technical literature, automated data extraction |
| High-Performance Computing | C++20 (Template Meta-programming, SIMD), Python (JAX, PyTorch, DuckDB), cuda |
| Production Deployment | Azure ML, AWS SageMaker, GitHub Actions CI/CD, Containerization |
Engagement Model
We focus on quantifiable outcomes. We do not deliver “pilots” or generic reports; we deliver measurable engineering results. If a project’s objective cannot be mathematically or operationally quantified at the outset, we will collaborate with you to define those metrics before work begins.
Contact
For inquiries or discussions, talk to us:
Email: hello@columbium.io