January 5, 2009 · 5:59 pm

Best of the Year

I didn’t make any best-of-the-year lists, but I support the idea. I also support new year’s resolutions, but I’m not going to write about mine.

But the internet picks up the slack.

FlowingData has a 5 Best Data Vis of the year list, which I’m fond of. It includes the beautiful Streamgraphs of Byron and Wattenberg. Their technical report has some fun applications of combinatorial optimization to aesthetics.

Streamgraph at the box office

Lance Fortnow has a nice Complexity Year in Review on the Computational Complexity Blog. Unfortunately, I don’t have a beautiful illustration of Prasad’s result that Unique Games Conjecture implies semidefinite relaxations have optimal approximation ratios.

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December 30, 2008 · 7:16 pm

Harvey Milk, Mathematician

Movie I sawI had time to see a movie on Christmas day! And it turned out to be a great movie, Milk, with great acting by Sean Penn and many others. It is a true story of the first openly gay politician elected to public office in California.

It was mentioned only in passing in the movie, but it turns out that Harvey Milk was a mathematician. He wasn’t publishing research papers or teaching calculus classes as an academic professor, but, as he mentions in the movie, before getting into politics, he worked in insurance. Wikipedia has a little more to say about this: Milk was a “actuarial statistician”, and after that, but before becoming a political organizer,

Milk abruptly stopped working as an insurance salesman and became a researcher at the Wall Street firm Bache & Company. He was frequently promoted despite his tendency to offend the older members of the firm by ignoring their advice…

Milk was a quant! Any quants looking for a change of pace, Milk is an inspiring example of what a person did in 8 years, without doing a bit of activism before turning 40. I came across this youtube video of a speech Milk gave, that has some music mixed under it and motion graphics layered on top.

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December 24, 2008 · 9:43 pm

Holiday Viewing

It’s been snowing in Seattle for a week now, and that never happens. Things were already getting quiet around here for the holidays, but now there are almost no cars on the roads and it’s been really quiet. I’ve been watching healthy algorithm videos to pass the nice, quiet time:


Gaussian Process Basics
David MacKay

GP Covariance Functions
Carl Edward Rasmussen

Unnatural Causes
California Newsreel

The Trap
Adam Curtis

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December 19, 2008 · 5:46 pm

Combinatorics of Malaria Eradication

Malaria infecting a mosquito

I’ve got at least 3 interesting blog posts worth of material on TCS applications for fighting malaria, but I haven’t had time to pen even one of them. Here is an abbreviated version:

Malaria is a major disease, something like the #3 infectious disease globally, and the #1 cause of both death and disability in many parts of Southern Africa.

The Gates Foundation is leading the charge to attempt to eradicate malaria from the world, and many national governments and NGOs are also involved in the fight.

There is a history of malaria eradication attempts, and the historic lesson is this: don’t start a fight with malaria unless you’re going to win.

Continue reading →

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December 13, 2008 · 6:43 pm

IHME and the two words of good journalism

The investigative journalist I.F. Stone once told an assembly of aspiring writers, “I am going to tell you a number of things, but if you really want to be a good journalist you only have to remember two words: governments lie.”

Exaggerate is a more diplomatic way to put it, and that’s how the headlines read regarding a new IHME report that came out in Lancet on Thursday. Here is the local edition, from the Seattle Times: Continue reading →

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December 5, 2008 · 3:39 pm

Florence Nightingale: Health Metrics Pioneer

Diagram of the causes of mortality of the army in the east

Nightingale's Coxcomb


Science News recently ran an article on the health statistics work and data visualization work of Florence Nightingale.  It’s fun for me to learn about this history, since I am such a recent immigrant to the land of health metrics. Nice quotes from Nightingale’s statistical mentor in the piece, too:

You complain that your report would be dry.  The dryer the better. Statistics should be the dryest of all reading.

The graphics in the Science News article are from an educational project of the Statistics Lab at the University of Cambridge called Understanding Uncertainty. It seems like Nightingale’s coxcomb it is a well debated form of infoviz over at the Edward Tufte Discussion Board.

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December 4, 2008 · 1:10 am

Midwest Theory Day and Me

I’ll be talking about “Theoretical Computer Science in Global Health” as the invited speaker at the Midwest Theory Day this Saturday (Dec. 6). It sounds like it will be a fun workshop, a one day deal at Northwestern Univesity. If you’re in the area, I think you should come on by.

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December 1, 2008 · 11:14 pm

Theory in Wikipedia

wikiScott Aaronson’s recent blog post about improving the state of computer science articles in Wikipedia has been generating some buzz this week. I’m happy to buzz along. Yay for Wikipedia!

Here are my top picks from Scott’s wishlist for the motivated encyclopedia writer:

  • Sketching algorithms
  • Streaming algorithms
  • Sparsest cut
  • Metric Embedding
  • Glauber dynamics
  • Average case complexity
  • Conductance (probability)
  • Max-flow min-cut

Frequent Wikipedia contributor David Eppstein also has his own todo list that you can draw inspiration from.

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November 26, 2008 · 4:28 am

MCMC in Python: PyMC for Bayesian Probability

I’ve got an urge to write another introductory tutorial for the Python MCMC package PyMC.  This time, I say enough to the comfortable realm of Markov Chains for their own sake.  In this tutorial, I’ll test the waters of Bayesian probability.

Darwin's other Bulldog

Tom Bayes

Now, what better problem to stick my toe in than the one that inspired Reverend Thomas in the first place? Let’s talk about sex ratio. This is also convenient, because I can crib from Bayesian Data Analysis, that book Rif recommended me a month ago.

Bayes started this enterprise off with a question that has inspired many an evolutionary biologist: are girl children as likely as boy children? Or are they more likely or less likely? Laplace wondered this also, and in his time and place (from 1745 to 1770 in Paris) there were birth records of 241,945 girls and 251,527 boys. In the USA in 2005, the vital registration system recorded 2,118,982 male and 2,019,367 female live births [1]. I’ll set up a Bayesian model of this, and ask PyMC if the sex ratio could really be 1.0.

Continue reading →

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November 21, 2008 · 6:03 pm

Google Flu

Have yinz already seen Google Flu? It’s a project by google.org, in collaboration with the Center for Disease Control and Prevention (CDC). It’s been getting healthy press coverage for the last two weeks or so. And, if you want to dig deeper, a draft manuscript on their approach is also available.

The headline result of this approach to tracking flu outbreaks is that it is fast: google.org can observe flu trends two weeks before the CDC. And it is accurate enough, with correlations of 0.85-0.98 between the search-result-based estimate and the gold-standard rates produced by the CDC.

I’ll tell you what’s wrong with it, but first let me praise it.

Continue reading →

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