I'm preparing to teach an online course on climate science using the Zoom platform. Tentatively called "Climate Science for Climate Activists", it's intended to bring climate activists and environmental progressives up to speed on the basics of Climate Science. I am using the excellent introduction by Professors David Archer and Ray Pierrehumbert of University of Chicago and Oxford University as a start (Global Warming: Understanding the Forecast), which is also available online with video lectures. I'm intending to soften the quantitative aspects some, but will assign homework. The course will be in 10-17 sessions, one or two per week.

Despite continuing to work in the Internet space, my principal means of analysis exploits findings in biotechnology and quantitative ecology. In addition to random projections, I'm studying applications of shrinkage and the LASSO for document-term matrices and regression based upon them.

Doing a bit of stuff with random projections from high dimensional space to two dimensions, these days. Both simple projections, like those described at https://667-per-cm.net/2018/11/20/the-johnson-lindenstrauss-lemma-and-the-paradoxical-power-of-random-linear-operators-part-1/ and much more sophisticated presentations, like those studied and engineered by M. C. Thrun and colleague A. Ultsch, per https://www.researchgate.net/profile/Michael_Thrun/publication/326413234_Investigating_Quality_Measures_of_Projections_for_the_Evaluation_of_Distance_and_Density-based_Structures_of_High-Dimensional_Data/links/5b4c2f0845851519b4c02a63/Investigating-Quality-Measures-of-Projections-for-the-Evaluation-of-Distance-and-Density-based-Structures-of-High-Dimensional-Data.pdf

Grad student pursuing a PhD in mathematics. Outside of math, I'm interested in cognitive science, ecology, permaculture, and political theory.

Interested in Conceptual Space Theory, NLP, analogy & metaphor, and cognitive/developmental robotics. Perhaps Category Theory can help me become a better AI engineer?