About Me

Equally comfortable in academia and industry, I focus on technical explorations into the complex questions arising in Applied Mathematics and Statistics. I use my training and experience to work on all levels of a project, from theory to code.

I come alive in applications that involve two main areas: improving lives, and understanding Earth System Science (ESS) models.

My few strong philosophies are:

  • One must push oneself relentlessly to watch, ask, study, try, start again, and stay curious.
  • Working in small teams is best.
  • Project management is crucial.
  • Object Oriented methodology is more than a design framework, it is a great way to interact with others.
  • Talking too much is an indication it is time to write.
  • Machine Learning is a great tool for good, but is best implemented by those with training in stochastic processes and High Performance Computing (HPC).

Areas of Specialization

Mathematics & Statistics

Portfolio

My main interests are Spatial Statistics applied to Climatology, Statistical Learning, Partial Differential Equations, and the Math of Political Redistricting.

Computing

Portfolio

Although I mainly work in R for Statistical Programming and Python, C++, and Fortran for High Performance Computing.

Business Intelligence

Portfolio

My strengths are SQL-based Extract, Transfor, and Load (ETL), AWS E2, and Machine Learning-based Predictive Analytics such as Market Basket Analysis or Neural Networks.

Data Systems

Portfolio

I work with both structured data systems (traditional database architecture) and unstructured data (big data, streaming data, scraped and time-based).

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