I'm just wrapping up a double masters in neuroscience and machine learning, and I was wondering if it was possibly to basically do the equivalent work of a phd, publish 5-6 papers on your own?
The topic I'm really getting interested in is at the intersection of Wetware Computing (https://en.m.wikipedia.org/wiki/Wetware_computer), Neuromorphic Computing, and Deep Learning. I've found some programs like the iPhd at University of Washington, but I can't find too many professors who would be willing to allow me to work on these topics on my own.
Would it be feasible to work on my own for a few years, assuming finances weren't an issue, and publish a few noteworthy papers and open source work? Would that basically be the equivalent of what a PhD is supposed to signal?
> Would that basically be the equivalent of what a PhD is supposed to signal?
Signal to whom? Probably not, in my estimation, but maybe -- it depends on what you're attempting to accomplish.
Enrolling in a formal, traditional Ph.D. program has lots of benefits; getting to work under a mentor is only one of them. Perhaps the most significant is that you become part of a network of peers: you surround yourself with people whom you can bounce ideas off of. Also, there will generally be lots of visitors passing through, with lectures and opportunities to go out to dinner with the speakers afterwards -- also invaluable learning perspectives.
Unfortunately interdiscplinarity is a difficult thing: most faculty only know their own discipline. (University administrators love interdisciplinary research, but impressing them is irrelevant before you have a tenure-track position.)
> and publish a few noteworthy papers
Noteworthy to whom?
It sounds like you want to pioneer a new research area that nobody works on. Would you be satisfied to do work that, in some abstract sense, is worthy of taking note of? Or is it important to you that other people actually notice? If the latter, then you almost certainly want the backing of an advisor and of an institution.
In general, professors tend to appreciate students who take the initiative and seek out their own research projects. Depending on your long-term goals, I would recommend seeking out professors who work in one of the topics you mentioned, and depending on their response, consider enrolling in their Ph.D. programs.
Best of luck!
I don't know much about CS PhD programs, but in biomed, solo publications are very rare, just due to the amount of resources needed. Also, you lose the credibility of an institution, and your work will be more heavily scrutinized, or just thrown out for being too much work to review.
As to whether it would be the "equivalent" or a PhD, it won't get through a resume parser, and won't get you a teaching position or even a postdoctorate position, but companies probably won't care.
At least in Australia, you need to begin a PhD before, or at least very close to, when you start working on this stuff. So if you go this route, make sure you talk to an interested professor+university before you go off for a few years and work on stuff. The reason being is that universities get a large award from the government when students complete a PhD, and so all of the work you publish has to be “part of” your degree - you can’t bring a large amount of work along from elsewhere.
On the other hand, there are very promising research directions precisely in the intersection of neuroscience and deep learning (e.g. biologically plausible credit assignment problem, learning algorithms of the brain, objective functions in the brain, sensori-motoric integration, etc). It's rare to find a person with solid understanding of both fields, especially in academia.
If I were you I would look at residency programs at big companies (Google Brain, Facebook AI fellowship, etc). Also, there's a company called Numenta which is probably looking for people with your skills (they are trying to reverse engineer neocortex' algorithms). From what I heard, those places give you some freedom to choose your own problems, encourage publishing papers, and provide very bright people as mentors.