ssw1n

This is more like it. Kudos to you !

Missed Distributed and Parallel Computing Area too ! It's a shame, but are the Systems guys forgotten these days with the rise of fancy AI/Machine Learning/Data Sciences Areas?

For the purpose of research and publications, the ability to translate mathematical models into programming environment should suffice: it is not like you have to code up production-ready machine learning engine anyways. Try MATLAB. I have Computer Science / Social Sciences PhD. student friends in Machine Learning / Learning Sciences research, and MATLAB is their platform of choice: simple, easy to get the ideas going, and there exist several toolboxes and packages for machine learning. (Provided that you apply(ied) for Computer Science PhD., I assume that the basic constructs of programming is not foreign to you.) Plus, it has superb data visualization support: it can generate all the fancy graphs that your publication will be using. Another platform you might want to be in would be Python: relatively simpler compared to other platforms (Weka + Java or Weka + CPP) and the machine learning packages are evolving there. And a lot of pretty pretty data visualization packages available too.

Gus_W I am in a similar situation to you and OP. I would really appreciate if you can tell me what your application journey looked like, and what it is like to be back in school after you enroll. I am shooting for next year Fall.

Why don't you try UIUC for grad school? Since you already have publication level Research Work, I assume you know the Professors, and Professors know you. After all, the grad school admission has always been about if the person can do quality research, and you already have Professors you worked with at UIUC who can vouch you for that. And to top it off, UIUC has been consistently been at top of almost all the lists and rankings you can find online, better than all the schools you mentioned you already applied to.