Hi 👋, my name is Rich.

Here are some words that describe me in the dim, reducing light that nouns emit – writer, reader, scientist, programmer, educator, leader – but the best way to get to know me is to in-person, preferably on a walk or over a cup of matcha.

My expertise is at intersection of environmental data science, geospatial programming, water resources, climate change, policy, and technology. I’ve developed models that predict where wells will go dry during drought and decision-support tools for natural resources management. I’ve automated California municipal water quality reports, helped build the nation’s largest publicly-accessible spatial database of water system spatial boundaries, and co-founded the Water Data Lab, a group within Convolve Coperative. I also co-developed R for Water Resources Data Science and I occasionally write (informally) about data. My work has appeared in Nature, the Los Angeles Times, NewScientist, and Newsweek.

Currently, I lead data and software teams in the energy sector. We build tools to help utilities adapt to climate change, assess wildfire risk, and make equitable electrification investments.

This website is built with blogdown and Hugo, and deployed using Netlify. My blog posts are released under a Creative Commons Attribution-ShareAlike 4.0 International License.

Thanks for being here.

Another day, another blog

Automate SMS and MMS with R, Twilio, Docker, and Github Actions

Here we’ll deploy a Docker container running R that sends an SMS (short message service, aka “text message”) via the Twilio API, and orchestrate the code to run on a timer with Github Actions.

Although Docker has been around for years, Docker in the data science community doesn’t seem as widespread as git, which I attribute to the fact that many data scientists learn to program and work independently. However, as data scientists increasingly collaborate with others or aim to make their work more reproducible, Docker deserves an equal place alongside git in the practitioner’s toolkit.

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