Prof. Keshav’s Aphorisms – Its a great collection of advice on everything related to research and some on life too. Its a must read for CS researchers.
How to Have a Bad Career in Research/Academia – By Prof. David Patterson
It contains advice starting from being a graduate student till the post PhD period. It also has some links on good writing tips, giving a talk etc. If you are a researcher, you should definitely give this a read.
Advice to a Young Scientist – By E.W.Dijkstra
I covered the points made by EWD in this blog post. Its truly inspiring!
Advice on Research and Writing – By Mark Leone
Its a good collection of advice on how to conduct research and how to communicate it. Its mostly for computer science researchers.
Research Advice – Adam Wierman (Caltech)
An assortment of advice to become a researcher: from applying in a graduate school, being a grad student to paper writing, giving a talk, refereeing papers
Being a Computer Scientist – ACM Committee on Status of Women in CS
How to succeed in Graduate School: A Guide for Students and Advisors – By Marie desJardins
Its a very comprehensive set of advice for graduate students talking about things a student will face during their time in school and how to tackle each of those. It also list some advice for advisors about dealing with students, maintaining their schedule etc. Good read!
How to read a paper – By Prof. Srinivasan Keshav
Very good for novice researchers.
How to write a systems paper – By Prof. Srinivasan Keshav
Its a very interesting article on writing a systems paper. Very well written and without going into any technicality, it delivers the message loud and clear.
How (and How Not) to Write a Good Systems Paper
It talks at length about what a good systems paper should have, things to keep in mind while writing one and so on. Its a good read that will be helpful especially when you start writing a paper and are wondering “is there a checklist of things to do?” ’cause this article provides just that.
Scientist v/s Inventor
An interesting view on novelty v/s reproducibility – two things a scientist deals with everyday and which leads to a confusion regarding his role as opposed to an inventor.