If you are interested in NLP
, then I would focus on two aspects of listed PL
disciplines:
- Syntax & Semantics - as this is incredibly closely realted to the NLP field, where in most cases the understanding is based on the various language grammars. Searching for papers regarding
language modeling
,information extraction
,deep parsing
would yield dozens of great research topics which are heavil related to the sytax/semantics problems. - logic programming -"in good old years" people believed that this is a future of AI, even though it is not (currently) true, it is still quite widely used forreasoning in some fields. In particular,
prolog
is a good example of language that can be used to reson (for examplespatial-temporal reasoning
) or even parse language (due to its "grammar like" productions).
If you wish to tackle some more ML
related problem rather then NLP
then you could focus on concurrency
(parallelism) as it is very hot topic - making ML
models more scalable, more efficient, "bigger, faster, stronger" ;) Just lookup keywords like GPU Machine Learning
, large scale machine learning
, scalable machine learning
etc.