I just read an article on Slashdot about the “power of algorithms” (really about involving both humans and machine learning in solving problems, which is a far cry from theoretical study of algorithms, but the article just demonstrates that most people can’t distinguish between the two). My first thought is that the growing awareness that the article summarizes arrived approximately a year and a half too late for me, as the root cause of my problems with graduate schools (both regarding admissions and independent learning opportunities) last year seems to stem from my choice of algorithms as a (“cold”) field of study.

The tide of increased awareness arrives at a perfect time for me to obtain a very cushy job in industry after obtaining my doctorate. Unfortunately, this is (a) not going to be a problem for me in any case, and (b) not really my goal. I want to do good science and creatively solve the big problems. Unfortunately, despite demonstrating considerable talent in the areas I want to go into (of course; I wouldn’t choose them otherwise), I haven’t been able to receive the slightest modicum of institutional training in those fields. In fact, I’ve met active resistance while attempting to procure such training. Autodidacticism is good, but it only goes so far, especially for a verbal learner such as myself.

And I still maintain that the research community is slighting a very powerful field that still has much room to expand.

First, happy Autumnal Equinox and Yom Kippur. If you are fasting, may your fast be an easy one.

On a more personal note, I’ve decided to go into industry post-graduation, which means I will most likely disregard my advisor’s suggestions, tempting as they might be, of taking up a postdoc at CMU. I’ve had a bias for a while, but it’s now definite, and only very strange circumstances will alter my decision. Part of it was more passive recruitment, this time from GE, Exxon-Mobil, and AT&T – all great companies, all great jobs, the credentials that set me apart (in particular, the fact that I had the highest GPA in my class) are taken into account in the hiring process, and I probably don’t need to worry that I won’t pass the interviews if I demonstrate programming and analytical abilities but can’t recite the CYK algorithm from memory (ala Google, which would have been an excellent place to work, and to continue my own research, if it had worked out).

Again, we need to contrast this with the academic response to the same credentials (plus a perfect GRE score, four glowing letters of recommendation, and a model personal statement that the companies didn’t even see!), where rejection from all of the schools that could have given me a real education (for the first time since 4th grade) forced me into Philadelphia, a city I loathe so deeply that I structure my entire schedule to minimize my time there (conflicting frequently with my advisor, who attempts to maximize my time in the lab, which also has the side effect of minimizing my productive time by jamming a 3+ hour daily commute into the works). It’s something that still burns within me, for the effects of the decision are permanent: I’m not receiving earnest scientific training, I’m not working in theory, my efforts to acquire proficiency in other fields are being severely and quite deliberately suppressed, I still haven’t defined my relative proficiencies or limits (or even learned study habits!) because I’m still effortlessly outstripping my class, and on top of it all I’m being pushed into traveling for 3 hours to one of my least favorite places on the planet at every available opportunity. I don’t know if I’ll ever be able to get over it; it’s completely altered the course of my life, my career, and my scientific output, and not in a good way. This is why I can’t even talk about it without the discussion degenerating into a rant. It was just absolutely unjust for someone with my proven ability and purity of intent to be denied a high-quality education, essentially left to wither, on the crux of his scientific career.

It’s not just a bias against past slightings, however. I’d put those aside in terms of career but for one thing, which I am noticing more with every passing day: the career of a scientist is socially constructed. You are nothing if you are not revered by your peers. One of my own theories (my 19th psychological postulate) states that a caste’s attitude towards you is a reflection of its own social values; an immediate corollary is that entire sectors will have rather consistent attitudes towards you over time. I wouldn’t formulate it if I didn’t believe it; my past reception by both sectors is a reflection of the direction my career will take.

And then there’s the research environment. I firmly believe that, for a theoretician, the lab is the last place to go to do research. Einstein had it right – stay in the patent office and devote your mental resources to your theories. Communication is a distraction. Travel is a distraction. The unfamiliar environment is (initially) a distraction. The lack of tools can be a distraction. Relying upon other people can be a BIG distraction if you’re not fortunate enough to end up with people who can be bothered to pull their own weight (a recent journal paper was completed in January, save for one experimental result which I must rely on the UPenn people on our team to produce, as they have the classifier that can produce it. Guess what? It still hasn’t been published!)

Here’s one that most people miss: devoting long stretches of contiguous time to research is a distraction! Think too much about a single approach for too long and you become entrenched in one mode of thought. Again, we have a historical precedent of the effectiveness of just thinking about other things, this time in Edison.

So yes, I do believe that industry would give me a better environment than academia. It also provides a useful fallback option, in the form of a development position, in case I become so disgusted with the way research is done that I decide to leave it altogether.