# Hello World!

Oh, hello there! I see you've found the 'blog' portion of my website. I've been getting more into web development recently (relative to whenever this was posted), mostly because I'm tired of hearing the architecture and web-dev people at my work go on about flask, Werkzeug, oAuth, javascript, Angular, React, etc., etc., and having no idea what it is they're talking about! So building the blog (and the rest of the website, in general) is my humble attempt at trying to force myself to learn some new things. And so far, I have! Even just getting a bare-bones website online was its own ordeal - should I host it at Heroku, AWS, GCP, WebFaction, or build my own server? (I decided to go with pythonanywhere; they made it pretty painless.) Where do I buy a domain name? What the hell should I name it? How do I create a CNAME record? How do you set up a "naked domain"? Can I create a redirect from my old GitHub pages site to the new site? (Spoiler alert: yes.)

And that's just to turn the damn thing on! What about actually building the website? I'd made some super simple static pages before that were basically just some paragraphs about me, a link to my resume, and an out-of-date picture, but this time I wanted to do it for real. So I started looking at flask, basically tripled my previous knowledge of HTML/CSS, and now I'm starting to get into javascript, which I have literally never touched before. So I think I've been pretty successful at forcing myself to learn new things so far.

## Anyway...

But I don't envision that this blog will be solely about my foray into web dev. I also have a lot of ideas about data science, machine learning, AI, math, and astro(particle) physics; and experiences in academia, industry, (the transition between the two,) travel, etc. that I want to share. I don't promise that I will be able to serve these "insights" with any regularity, but at least I'm making an effort, you know?

So what will I talk about first? (This post obviously doesn't count.) Should I talk about using pandas and matplotlib to analyze and visualze some dataset? Maybe discuss recent advancements in reinforcement learning? Should I wax poetic about the various types of black holes (Schwarzchild, Kerr, Reissner-Nordstrom, ...). Perhaps I might explain what this means:

\begin{align}\mathcal{L} =& -\tfrac{1}{4} F_{\mu\nu}F^{\mu\nu} + \overline{\psi} \gamma^\mu \left(i\partial_\mu - ieA_\mu\right) \psi \\ &+ \tfrac{1}{2} \partial_\mu\phi^\dagger\partial^\mu\phi - y \phi \overline{\psi}\psi + h.c. + V(\phi) \end{align}

I'll figure something out. And if you're reading this and have something you want to hear about, leave it in the comments section (which does not exist as of this writing... I will get on that, I promise), or email me.