John May

Dr. John May

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16 years, 311 days
Maplesoft
Pasadena, California, United States

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I have been a part of the Mathematical Software Group at Maplesoft since 2007. I have a Ph.D in Mathematics from North Carolina State University as well as Masters and Bachelors degrees from the University of Oregon. I have been working on research in computational mathematics since 1997. I currently work on symbolic solvers and visualization as well as other subsystems of Maple.

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These are Posts that have been published by John May

In this series of blog posts, I have picked on Baseball win-loss records already.  Looking for other sources of things that might or might not be random, I decided to look at lottery draws.  Since I live in Canada, the obvious lottery to look at is the national Lotto 6/49.

A lotto 6/49 draw consists of drawing 6 numbered balls from...

If you are interested in listing to me ramble for an hour about integration algorithms, it looks like the recording of the Webinar I gave in early September has been posted to the academic webinar archive: Theory and Practice of Symbolic Integration in Maple. I tried to make it a broad introduction for someone with...

I have gotten some comments about my new avatar, including a few commenting that while my picture is clear on the blog contributors sidebar, it is "blurry" on my blog posts. I just wanted clear this up.  I am not in the witness protection program; I just really love singular values.  My new avatar, just like my old one, is a rank 4 approximation of a picture of me using the singular value decomposition.

In a series of posts now imported to the Maplesoft blog (starting here), I have been talking about pseudo-random number sequences, but since part of what kicked off this series was a paper on true random number generation (with LASERS!) I thought I would share some routines I wrote that alllow you to use the two main true random number sources available on the web (neither using lasers, sadly).

In this post I'll introduce is a nice visual test of randomness from signal processing. The main idea of this test to look at how a random sequence correlates with itself.

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