Prof. Urbashi Mitra is looking for multiple postdocs. Given that this is the time of year when the future looks murkiest, these are great opportunities!
I am seeking multiple post-doctoral researchers are sought with expertise in one or more areas: Communication Theory, (Statistical) Signal Processing, Controls, Information Theory, and Machine Learning. In particular, the following expertises are of interest: structured inference (sparse approximation, low rank matrix completion, tensor signal processing, graph signal processing); multi-terminal information theory, or information theory at the boundaries of control or signal processing; distributed control, consensus methods and partially observable Markov Decision Process modeling and algorithms; modern optimization methods; or biological communications, signal processing or information theory.
The successful applicants will be expected to perform innovative translational research, mentor PhD students, give oral presentations, write journal papers, and participate in grant writing and project management. There will be significant opportunities for research leadership and interaction with funding agencies.
Ideally, the successful applicants will start in Summer 2016.
Please have your interested graduate students apply using the following portal:
In addition to a cv and research statement, the applicants are requested to have three letters of reference uploaded to the system as well.
He was hitting the haterade pretty hard:
The vacuum tube was first used to replace previously existing components of long-distance telephone circuits and wireless telegraphy. It was not long, however, before it became clear that the radio-telephone had achieved the stature of the radio-telegraph, and that broadcasting was possible. Let not the fact that this great triumph of invention has largely been given over to the soap-opera and the hillbilly singer blind one to the excellent work that was done in developing it, and to the great civilizing possibilities which have been perverted into a national medicine-show.
I’ve seen this quote excerpted in parts before, but not the whole thing:
I repeat, feedback is a method for controlling a system by reinserting into it the results of its past performance. If these results are merely used as numerical data for the criticism of the system and its regulation, we have the simple feedback of the control engineers. If, however, the information which proceeds backward from the performance is able to change the general method and pattern of performance, we have a process which may well be called learning.
– Norbert Wiener, The Human Use of Human Beings
It is a strange distinction Wiener is trying to make here. First, Wiener tries to make “numerical data” a simple special case, and equates control as the manipulation of numerical data. However, he doesn’t contrast numbers with something else (presumably non-numerical) which can “change the general method and pattern.” Taking it from the other direction, he implies that mere control engineering cannot accomplish “learning.” That is, from numerical data and “criticism of the system” we cannot change how the system works. By Wiener’s lights, pretty much all of the work in mathematical control and machine learning would be classified as control.
I am, of course, missing the context in which Wiener was writing. But I’m not sure what I’m missing. For example, at the time a “control engineer” may have been more of a regulator, so in the first case Wiener may be referring to putting a human in the loop. In the book he makes a distinction between data and algorithms (the “taping”) which has been fuzzed up by computer science. If this distinction leads to drawing a line between control and learning, then is there a distinction between control and learning?