I graduated from my undergraduate degree about a year ago and took a job in industry. While completing that degree, I did research with a professor related to machine learning. However, after finishing that project, I don't think ML is where I'd want to do my research if I decide to reenter the academic world.
The advice I've received regarding applications to grad school is to be reading papers of a professor I want to work with, at least with enough understanding to suggest a new idea/direction of my own. However, I don't really know exactly what I'd like to research, but I do have some general topics I'm interested in (categories on the level of "robotics" or "cyber-physical systems") --- figuring out what areas are still active research and what is ancient history is a bit harder than when I could just turn to my advisor and ask "what/who is at the cutting edge in this field?"
Aside from just "jump in the deep end and keep reading until it makes sense," are there methods or techniques that might help me build context or evaluate the areas I'm interested in?