Do academicians consider Challenges on Kaggle to be research-worthy? I am a somewhat new-ish member of Kaggle competitions with 1 submission. Do academics research via Kaggle challenges/competitions? If so are there any prominent names?

If not why? They provide well annotated training data-sets, and typically do not put any publication restrictions as well.

Perhaps they consider such challenges trivial. Just a query on an academic's perspective on the challenges here.

The only thing I've heard about Kaggle from an academic's perspective is from Graduate School Students at Stanford, who need to participate in a challenge as a part of their coursework (which is pretty cool).
One of the other uses I've noticed (besides publishing papers on a competition itself) is academics using a competition to demonstrate the application of a particular algorithm that they have developed and published.  See Steffen Rendle's libFM (Factorization Machines) winning the Grockit Challenge, and the winning team of academics in the Merck Molecular Activity Challenge with their use of deep learning.