Under-Investigated Fields
matthewmcateer.me
Under-Investigated Fields
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Re: Under-Investigated Fields
#2Transfer learning is no longer under-investigated. Just look at how the NLP and CV communities get state of the art results
Re: Under-Investigated Fields
#3> While it’s easy to point to areas in computer science that might be over-researched (after all, Machine Learning conferences often get more papers than they can effectively review), there are still areas that are neglected with respect to their potential benefit.
It would be worth considering what drives people towards researching particular areas, even if it might seem kinda obvious. I.e. it might be tempting that it's visions of fame, loot & prizes, but I think to most people it is obvious on some level that they personally won't get any prominent position in these fields. I think it's partly a question of discoverability (say I'm a student, how do I learn about these topics, and that there are practical ways to work on them?), partly perceived prestige.
Also, getting into a particular PhD or similar currently means thinking years in advance -- I'm not talking learning/studying here, but connections, bureaucracy and applications, having paper "proofs" you know something etc. You notice some interesting area towards the end of your studies. It's too late to move even not that much from what you're doing (e.g. move from cognitive science to computational neuroscience) without wasting additional precious years. And that for entering not particularly rosy world of academia.
Myself (not academically nowadays), I see myself searching for a middle ground between overcrowded fields (where I will probably do relative "grunt work" at best) and fields that are so obscure as to be not viable. The fear of having no steady income is too real.
Re: Under-Investigated Fields
#4Applied category theory and uncertainty logic could be added to math.
Re: Under-Investigated Fields
#5Transfer learning is no longer under-investigated. Just look at how the NLP and CV communities get state of the art results
Transfer learning is absolutely under-investigated. The current results in CV are awesome but they only pertain to CV. There’s little underlying theory that helps you apply it to other areas. Mine, for instance, which is robotics manipulation.
Re: Under-Investigated Fields
#6Usually things are be under-investigated because they're hard.
Re: Under-Investigated Fields
#7I think it's weird to suggest that programming languages are under-investigated, and the discussion he gives of it makes me question his conclusions about other fields. There are vastly different paradigms completely orthogonal to the hierarchy in that image the author uses. I don't think getting people to stop using assembly/C/fortran/cobol/php/whatever is a research problem.
Re: Under-Investigated Fields
#8Anyone know if there's been research into terraforming via asteroid/comet impacts and trying to simulate that?
Re: Under-Investigated Fields
#9Anyone know if there's been research into terraforming via asteroid/comet impacts and trying to simulate that?
PBS Space Time covered the idea a bit in a recent video https://www.youtube.com/watch?v=FshtPsOTCP4. They had some numbers but I don't think they referenced any formal research in that one.
Re: Under-Investigated Fields
#10I think it's weird to suggest that programming languages are under-investigated, and the discussion he gives of it makes me question his conclusions about other fields. There are vastly different paradigms completely orthogonal to the hierarchy in that image the author uses. I don't think getting people to stop using assembly/C/fortran/cobol/php/whatever is a research problem.
I had the same reaction.
There are easily thousands of people working on building higher-level programming languages/models. A very short and very incomplete list of entire subcommunities of PL working on languages that are higher-level than java/python:
1. The ML family -- OCaml, SML, Scala, F#. I think it's very fair to say that these are "higher-level" than imperative OO languages. And you can definitely get a job writing OCaml or Scala or F#...
2. A whole bunch of programming languages/primitives/paradigms aimed at making concurrency/parallelism/distributed systems easier. Erlang, X10, session types, Manticore, etc. Rust might even belong here.
3. Programming languages that incorporate resource/complexity analysis.
4. Literally decades of work on visual programming languages (which have mostly resulted in modern IDEs and teaching tools like Scratch).
5. behavioral types
6. linear types (again rust kind of fits here)
7. dependent types
8. I would also argue that systems like tensorflow and pytorch are really a sort of programming language -- they have a very different model of computation than the host language. Just because they don't have a parser/compiler/etc. doesn't mean they aren't a programming language, imo.
9. Tons of other stuff that doesn't fit in the major categories above (e.g. netkat).
10. I mean even SQL belongs in this list.
Even for language/models listed above that don't have large adoption, the ideas are often incorporated into more mainstream languages in one way or another. So there are significant projects developed in each of these types of languages (with the exception maybe of behavioral types and session types).
Higher-level programming Languages is one of the most explored areas of Computer Science -- if anything, it's an over-explored field.
This is less a list of "underexplored ideas" and more a list of "over-hyped ideas with over-crowded communities". Every item on the CS list is the sort of thing that an ungrounded undergrad research intern would want to work on.
Some of the descriptions in other fields have a similarly dilettante vibe to them. E.g.,
* Bio: math bio is a huge community and all those folks are well-trained in chaotic dynamics. you can say it's under-explored, but there are probably hundreds of people working on this right now and at least thousands have in the past few decades.
* Math: there's a section on subspace packing with a side-story about a proof assistant and the author doesn't even mention Hales...
* physics: Building machines to automate experiments is definitely the sort of thing people get paid to do whenever there's a large enough market (and even sometimes when there isn't). similarly, Nuclear-powered propulsion is underexplored... as long as you don't count the militaries of the major nuclear powers, that is.