Advice on Devloping Skills

There is a lot that goes into impactful research in mathematics (and in particular research in Theory of Computing). From learning / reading / proving / writing / presenting, there are many skills that are worth being cognizant of and developing. Spending time reading/watching advice on developing these skills, and thinking how to incorporate said advice into your process will likely yield long-term benefits for your research. Here is a smattering of such advice I found useful/informative:

• Ellis Herskowitz on Reading, Presenting and Listening to Theory

• Anupam Gupta on presenting theory

• Talk by Ryan O’Donnell on doing/reading/presenting theory (see also part 1c)

• Nicole Wein on doing theory as an early-stage PhD

• Ravi Vakil’s three things exercise for attending talks

• Ravi Vakil’s general advice (for math PhD students)

• Terry Tao on career advice (multiple blog posts)

• Terry Tao on writing papers (multiple blog posts + pointers)

• Manuel Blum on graduate research

• Oded Goldreich on How to Write a Paper

• Srinivasan Keshav on How to Read a Paper

• Ian Parberry on How to Review a Paper (in TCS)

• Jean-Luc Doumont on Creating Effective Slides (see more of his talks online)

• Donald Kunth, Tracy Larrabee, and Paul M. Roberts on Mathematical Writing

• List of Resources from the Learning Theory Alliance

Bonus: Don't forget to add powerful inequalities / theorems to your toolkit. For example, see:

• TCS Inequalities Cheat Sheet (Laszlo Kozma)

• The Multiplicative Weights Update Method

Feel free to let me know of more such sources!