Thread by @realscientists

Okay! I’ll kick off Monday AM with a “What’s machine learning?” thread.

I’ll cap off the weekend with a bonus mini-thread about my previous career in astrophysics!

I used to study the formation and mergers of supermassive black holes (SMBHs).

You might know black holes as what’s left behind when massive stars die.

These are “stellar mass BHs” (10s of solar masses, say).

Every galaxy seems to have a BH that’s millions to billions of solar masses. Those are SMBHs.

This is a series of infrared observations of the Milky Way center.

Using Kepler’s laws from physics 101, we know there’s 4 million solar masses of stuff at the common focus of these orbits.

Dr. Andrea Ghez shared a Nobel prize last year for this work.

images.app.goo.gl/UiJX9gBad4JJ8E…

We don’t have orbital data like this for other galaxies, but other evidence like stellar kinematic signatures, we can infer the existence of SMBHs in every galaxy where we have the ability to check.

Anyway, I used to research possible formation scenarios for these SMBHs (we know some billion solar-mass beasts formed in less than a billion years after the Big Bang!)

…as well as the luminous gas signatures around SMBH binaries, which we believe form when galaxies merge.

I had a really good time in astrophysics. My work took me from New York to Munich and back.

I grew a lot in learning to tackle complex & ambiguous research probs, as well as in communication & interpersonal skills—all things that help me in my new career, which I like even more!