Hey, I’m Josh Mōller-Mara. I’m an th year PhD candidate studying Neural Science at NYU, currently living in San Francisco. Before that, I was a triple-major in Computer Science, Cognitive Science, and Statistics at UC Berkeley.
Interests and Research
I’m interested in neuroeconomics, decision-making, Bayesian statistics, computational reproducibility, and free software.
My research in neuroeconomics as a PhD student revolves around risk. Specifically, how do mice and rats make decisions under risk? And can we compare their preferences across time and between species?
Answering these questions requires a large amount of data. So, in the Erlich Lab in Shanghai, I helped to design and build a high-throughput rodent experimental system that automated the process of collecting and analyzing hundreds of thousands of behavioral choices. Here I applied my background as a Linux systems administrator, using an infrastructure-as-code approach to ensure systems were reliable and reproducible. Some of the tools I used were Ansible (and occasionally Docker), Clojure (for backend real-time analyses), ClojureScript + React/reagent (for a front-end dashboard for our system), MariaDB, RabbitMQ, and Nix (for reproducible analyses).
To infer preferences from choices, I designed and wrote Bayesian statistical models in Stan and R. For more on this check out my Society for Neuroeconomics 2021 poster.
Technology
I exclusively use free and open-source software. (Check out the GNU project’s explanation on why free software is important.) I believe that free software is more accessible (especially considering socioeconomic status) and reproducible than proprietary counterparts, and importantly it encourages mutual cooperation and the sharing of knowledge.
To this end, I use Emacs for my text editor (check out mollermara.com for blog posts on Emacs), GNU/Linux (NixOS) for my operating system, and programming languages like R (instead of MATLAB). Check out more of what I use on my /uses page.