4

This question already has an answer here:

I am an electrical engineering undergrad with an interest in communication theory, networks, signal processing and optimization. I have PhD offers from two groups - one working in communications & networks and another working in statistical signal processing, compressive sensing & community detection. How do I decide between the two? It is my opinion that currently communication theory and networks have become a mature field with not much scope for rapid growth or fundamental path-breaking research, while the work in the other group is quite more "in vogue" due to machine learning based applications and has the potential to solve more fundamental problems.

A comparison between the two areas with regards to future research and job opportunities would be great.

marked as duplicate by Wrzlprmft, scaaahu, Bob Brown, henning, user3209815 Mar 21 '17 at 12:36

This question has been asked before and already has an answer. If those answers do not fully address your question, please ask a new question.

  • You are correct about the second group's research being more "in vogue," but don't discount the in vogueness of network research; in particular, distributed optimization of networks is quite a hot topic right now. – Mad Jack Mar 21 '17 at 14:40
  • Topic is one thing. An equally important factor is the supervisor. I know of a big professor who let his senior students supervise junior PhD students. In other words, he doesn't interact with PhD students until they become competent. They are others where students are 'thrown' into a group and students teach themselves -- no supervision. Yet in another example, a colleague of mine, who regularly recruits top undergraduate students, produces graduates with poor publications. Another colleague graduates poorer undergraduate students with top publications. – Prof. Santa Claus Mar 21 '17 at 21:05