Grad student lore

Writing

  • Clear writing is clear thinking.
  • Most of the effort of writing is rewriting. You have to get something down, but then you have to read it over and over and make improvements.
  • One way to get better at writing is by reading. If you want to be writing research papers, you have to be reading them.
  • It’s not enough to be right. You also have to be persuasive.

Tech tools

  • Spend 95% of your time working with familiar tools, and 5% trying new ones.
  • Any tool that makes it hard to do something essential isn’t the right one.
  • Corollary: Latex beamer is awful. You shouldn’t have to work so hard to use video, arrows, highlights, and so on.
  • For putting latex output into Powerpoint or anything else, you can use latexit (Mac) or KLatexFormula (Windows/Linux/Mac).
  • Use Detexify to search for a latex symbol by drawing it.
  • PDF simulates a piece of paper. It’s terrible for most things done on a computer screen.
  • Automate repetitive tasks. Doing so can be like growing a new arm—painful, but handy.
  • Use version control fanatically. Check in changes atomically, not in huge chunks. Use branches to try new ideas. I have relearned these lessons many times.
  • Learn to track and document all of your work as you go. Use a format based on plain text documents. Those are the only ones that are sure to still work in 20 years.

Research computing

  • Numerical experimentation is more like a laboratory science than math. If you don’t develop a system of keeping meticulous track of what you have done, you will go in circles and make big mistakes.
  • Clarity in coding is more valuable than cleverness.
  • Math is often about the 0.1% of cases that don’t work. Computing should be about the 99.9% that do.
  • If you haven’t tested your package, then I don’t trust it.

Math

  • When you encounter a new idea, start with the simplest example you can fully understand.
  • There’s no sense trying to solve a hard problem if you can’t first solve a simpler version of it.
  • Infinity can be incredibly useful, but in applied math, it can be an unwelcome distraction.