Mathematics for Natural Sciences

Tangent.to brings rigorous quantitative and physical methods to complex problems in the natural sciences, from agriculture and ecology to hydrology and the earth sciences.

Background

With a PhD in civil engineering, postdoctoral research in agriculture, and experience as a professor, I combine the rigor of engineering and physics with a working knowledge of natural systems. My expertise spans numerical ecology, agricultural and soil modeling, hydrology, and geophysical earth-science modeling, with occasional applications in the health sciences.

Approach

I apply quantitative and physical methods (statistics, machine learning, and mechanistic modeling grounded in physical laws) to the dynamic, nonlinear systems found across the natural sciences. The work bridges the precision of engineering and physics with the complexity of real agricultural, ecological, hydrological, and geological systems, producing tools and workflows that respect both mathematical rigor and the context of each domain.

Services

As an independent consultant, I work with research institutions, industry partners, and government agencies to:

• Develop predictive statistical and machine-learning models and decision-support systems
• Build physics-based, mechanistic models with calibrated uncertainty
• Deliver reproducible, production-grade computational environments
• Provide quantitative expertise across agriculture, ecology, hydrology, and the earth sciences

The focus is on delivering science-based, reproducible solutions that turn complex data into well-founded conclusions and decisions.

Philosophy

Good science requires good tools. Complex systems demand sophisticated analysis, but that analysis must remain accessible and interpretable. My work emphasizes reproducibility and automation not for their own sake, but to ensure consistency and to focus human expertise where it matters most: interpretation and decision-making.