This past year has rooted millions of us in our homes and our routines. I know every square foot of this place so well, it’s like being a child again.

Here’s an illustration of the groove I have worn. Months ago I bought a bright light to keep my study cheery, which sits on the piano three feet to my right. To turn it on, I just need to touch it. But my arm isn’t three feet long. So to turn on the light I get up from my desk, right?

Wrong. Years ago, for a big birthday, my father gave me a foot-long Georgian silver meat skewer to use as a letter opener. Somewhere along the way this pandemic year, I discovered that if you touch the light with the skewer, it switches on as easily as if you’d touched it with your hand. (My father loved silver, and showed me how it conducts heat and electricity even better than copper.) Two feet (arm) plus one foot (skewer) spans the gap. I don’t get out of my chair.

[27 March 2021]

The greatest change in the applied mathematical landscape in my career, apart from the advance of computers, has been the penetration of probabilistic ideas into every corner of our work. Differential equations become stochastic differential equations; deterministic algorithms become randomized; simulation gives way to uncertainty quantification. When I was a graduate student, hardly anyone outside of statistics departments worked on stochastic problems — certainly none of us numerical analysts in Serra House at Stanford. Nowadays if you don’t, you are old-fashioned.

I got a chance to quantify this trend when I gave the keynote lecture yesterday at the annual meeting of the MIT Center for Computational Science and Engineering. At the end of the question period I asked the audience — about 75 graduate students and postdocs, the CSE leaders of the future — how many of you work on problems with a probabilistic component? We did a Zoom poll, and the answer was 63%.

[16 March 2021]