Jan Galkowski

At the Azimuth project I am writing blog articles, starting with a series on Petri net programming. My plan is to study math and science and then teach it to colleagues in software development. We need more scientists to solve the myriad of problems that beset the human race, and the world of programmers provides a large recruitment base for the sciences. In the process I hope to develop myself as a scientist!

I am a statistician and engineer working for *Akamai Technologies*. I live with my wife, Claire, in Westwood, MA. I did undergraduate physics at Providence College, and received a Masters in E.E. and Computer science from MIT. I worked 17 at IBM in their Federal Systems Division, developing software for embedded systems, but, later, doing test engineering of quantitative software for avionics. I’ve run my own business, worked as a database developer, both on contract and for universities, and joined Akamai in 2007 in their Cambridge, MA headquarters.

I’m an active student of climate science and Bayesian methods. You can learn more about me here.

At the Azimuth project I am writing blog articles and hope to collaborate on quantitative and statistical problems pertaining to climate and combating environmental degradation. I am also keenly interested in models of the Internet and users on it.

“Warming slowdown? (part 1 of 2)” The idea of a *global warming slowdown* or *hiatus* is critically examined, emphasizing the literature, the datasets, and means and methods for telling such. Also available at the Azimuth Project wiki.

“Warming slowdown? (part 2 of 2)” The idea of a *global warming slowdown* or *hiatus* is critically examined, emphasizing the literature, the datasets, and means and methods for telling such.).

“Bayesian inversion of commingled tonnage of municipal solid waste to isolate components” Bayesian inversion to recover latent components in mixtures is a standard technique, with wide application. Yet, apparently, it is not well known. Frequentist methods for doing this are known as algorithms for *blind source separation*.

- Bayesian statistics, especially computational challenges, tutorials
- Time series and state-space methods, especially looking for new problems to solve using Kalman-Rauch-Tung-Striebel-type algorithms as taught by Durbin, Koopman, Harvey, and Ooms
- Climate science
- Statistical and mathematical methods for field and observational sciences
- Use of quantitative methods to improve resource management, e.g., solid waste management
- Stochastic search and optimization; stochastic engineering

- Examining HadCRUT4 improvements using MOS ensembles, a Bayesian bootstrap, or the Bayesian ANOVA described at my blog post.
- Statistical problems involving trends in estimating sea level rise.
- Inferring latent causes and relationships regarding the drinking water supply in the town of Sharon, MA and, more generally,
- Developing techniques which facilitate interpretation of data gathered by volunteers in the field and natural settings censored by seasonal availability
- Paul Pukite’s and Graham Jones’
*sloshing**model*for ENSO and evaluating it

empirical_bayesian@ieee.org jan@westwood-statistical-studios.org bayesianlogic.1@gmail.com

category: members