Thursday, May 19, 2016

Yuri Gurevich's advice to the young theoretical computer scientist

I have always enjoyed reading articles, interviews, blog posts and books in which top-class scientists share their experience with, and provide advice to, young researchers. In fact, despite not being young any more, alas, I feel that I invariably learn something new by reading those pieces, which, at the very least, remind me of the things that I should be doing, and that perhaps I am not doing, to uphold high standards in my job.

Based on my partiality for scientific advice and stories, it is not overly surprising that I was struck by the thought that it would be interesting to ask the EATCS Fellows for
  • the advice they would give to a student interested in TCS,
  • the advice they would give to a young researcher in TCS and
  • a short description of a research topic that excites them at this moment in time (and possibly why).
The EATCS Fellows are model citizens of the TCS community, have varied work experiences and backgrounds, and span a wide spectrum of research areas. One can learn much about our field of science and about academic life in general by reading their thoughts.

I am collecting the answers to the above-listed questions I have received from some of the current EATCS Fellows in a contribution that will appear in the June issue of the Bulletin of the EATCS. Over the next few days, as a sneak preview for that article, I'll post the advice from some of the fellows on this blog. Enjoy it!

Advice from Yuri Gurevich (Microsoft Research)

Advice I would give to a student interested in TCS Attending math seminars (mostly in my past), I noticed a discord. Experts in areas like complex analysis or PDEs (partial differential equations) typically presume that everybody knows Fourier transforms, differential forms, etc., while logicians tend to remind the audience of basic definitions (like what’s first-order logic) and theorems (e.g. the compactness theorem). Many talented mathematicians didn’t take logic in their college years, and they need those reminders. How come? Why don’t they effortlessly internalize those definitions and theorems once and for all? This is not because those definitions and theorems are particularly hard (they are not) but because they are radically different from what they know. It is easier to learn radically different things — whether it is logic or PDEs or AI — in your student years. Open your mind and use this opportunity!

Advice I would give a young researcher in TCS As the development of physics caused a parallel development of physics-applied mathematics, so the development of computer science and engineering causes a parallel development of theoretical computer science. TCS is an applied science. Applications justify it and give it value. I would counsel to take applications seriously and honestly. Not only immediate applications, but also applications down the line. Of course, like in mathematics, there are TCS issues of intrinsic value. And there were cases when the purest mathematics eventually was proven valuable and applied. But in most cases, potential applications not only justify research but also provide guidance of sorts. Almost any subject can be developed in innumerable ways. But which of those ways are valuable? The application guidance is indispensable.

I mentioned computer engineering above for a reason. Computer science is different from natural science like physics, chemistry, biology. Computers are artifacts, not “naturefacts.” Hence the importance of computer science and engineering as a natural area whose integral part is computer science.

A short description of a research topic that excites me at this moment in time (and possibly why) Right now, the topics that excite me most are quantum mechanics and quantum computing. I wish I could say that this is the result of a natural development of my research. But this isn’t so. During my long career, I moved several times from one area to another. Typically it was natural; e.g. the theory of abstract state machines developed in academia brought me to industry. But the move to quanta was spontaneous. There was an opportunity (they started a new quantum group at the Microsoft Redmond campus a couple of years ago), and I jumped upon it. I always wanted to understand quantum theory but occasional reading would not help as my physics had been poor to none and I haven’t been exposed much to the mathematics of quantum theory. In a sense I am back to being a student and discovering a new world of immense beauty and mystery, except that I do not have the luxury of having time to study things systematically. But that is fine. Life is full of challenges. That makes it interesting.

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