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Interesting description of the system of academic computer science research and no doubt crucial for some computer science students. For funding, I got tuition but no stipend. For an advisor, I didn't want one or really have one. On paper I had two advisors, but I brought my own problem, did my own research, both for the dissertation and some publishable research I did before the qualifying exams, and didn't want, need, or get any advice from either of my advisors. The best I got from my Ph.D. work was just terrific, fantastically good, powerful, valuable material. But there was a downside: I was attacked by some profs who resented me, wanted me to fail, and tried hard to have me fail. The actual academic work, including the research, was easy; most of the effort was just defending myself from attacks. I do not now nor have I ever had any desire to be a college professor. I got a Ph.D. to be better qualified for a good career in applied math and computing I had going before my Ph.D. Now I'm in business for myself. Math is not all there is to my business, but it is an advantage, likely a crucial one. The math is some math I derived together with some advanced pure math, a bit amazing, long in some advanced textbooks but not well appreciated for its potential for applications. The business is based on computing, and I've written all the code, all in Microsoft's .NET (which I like). The computer science used is just (a) the heap data structure used as a priority queue and (b) AVL trees for a cache. At one point I make use of LINPACK -- downloaded the Fortran version; got the Bell Labs program F2C to translate the Fortran code to C; compiled the C code as a DLL; and call it with Microsoft's platform invoke. I've published in applied math (optimization), mathematical statistics (multivariate, distribution-free), and artificial intelligence. I didn't publish my dissertation research because I wanted, maybe, to SELL it and certainly didn't want to give it away. |