Good Research?

1. Eamonn Keogh, How to do good research, get it published in SIGKDD and get it cited!

2. Bill Freeman, How to write a good CVPR submission

Communication/Information Theory Textbooks I Pretend to Have Read from Cover to Cover

1. R. W. Heath Jr. and A. Lozano, Foundations of MIMO communication

2. T. M. Cover and J. A. Thomas, Elements of Information Theory

Math Books I Really Enjoyed

1. J. M. Steele, The Cauchy-Schwarz master class: an introduction to the art of mathematical inequalities

2. R. L. Graham, D. E. Knuth, and O. Patashnik, Concrete mathematics

3. S. Axler, Linear Algebra Done Right

4. J. H. Hubbard and B. B. Hubbard, Vector calculus, linear algebra, and differential forms: a unified approach

5. David J.C. Mackay, Information theory, inference, and learning algorithms

Great Articles

1. D. E. Knuth, T. Larrabee, and P. M. Roberts, Mathematical writing (Particularly, I find points 15 and 26 in Sec. 1 helpful)

2. Z. C. Lipton and J. Steinhardt, Troubling trends in machine learning scholarship (the criticism is relevant to PHY layer research as well)

3. M. Dohler, R. W. Heath, A. Lozano, C. B. Papadias, and R. A. Valenzuela, Is the PHY layer dead?

4. D. E. Knuth, Two notes on notation

5. C. Shannon, The bandwagon (these days, machine learning is the "bandwagon")

6. D. Slepian, On bandwidth

7. Thomas Lam, 100 Questions: A Mathematical Conventions Survey

Useful Tools

1. webPlotDigitizer

2. Connected Papers

3. Matrix Calculus

4. Table Generator

Useful Advices

1. I am an editor for a lousy paper and I found a better algorithm than theirs. Must I share it with them?

2. What is the best "last slide" in a thesis presentation?

3. Is it okay to mention we're citing an article only because a reviewer told us to?