I am from electrical engineering background and I want to do PhD in machine learning. But machine learning is a multi-disciplinary field and available in many departments. So I am bit confused that from which department I should pursue PhD and what is the difference in PhD programs in different departments. Should I pursue PhD in machine learning in computer science department or from electrical departments. Thanks.

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    Commented Sep 4, 2020 at 12:26

4 Answers 4


Firstly, keep in mind that some institutions actually have their own machine learning departments (for example, Carnegie Mellon University). That being said, in general, Machine Learning falls under the umbrella of Computer Science and Statistics / Applied Math. It's typically not considered a subset of Electrical Engineering unless you're working in robotics or very narrow cases of building specialized hardware for machine learning algorithms.

If you are interested in doing a PhD in machine learning, you will most likely be applying to either a Computer Science, Applied Mathematics, or Robotics program.

  • This is factually wrong, most of the ML professors in my uni graduated in EE PhD. Even the ones in the CS department. Commented Feb 15, 2021 at 5:46

It's not about the department. Choose an adviser that is good in machine learning (ML). He/she might be in CS or EE. In my university, there are staff members in both departments who can supervise ML projects. Choose someone who fits your interest and work style; see recent question regarding selecting an adviser.


You didn't provide enough information to know, but if your statistics department offers ML classes, do that. After having been in machine learning for a while, I'm realizing that a solid background in statistics does at least two things: 1) you are more likely to realize statistical characteristics of your data that are important for model selection and feature engineering 2) you are in a better position to comprehend your data in a manner your peers will not

Remember, machine learning is about training algorithms to recognize patterns. Statistics is about making inferences about data. Pair them together and you're unstoppable.


In addition to previous fantastic answers, here is what I think:

  • Note that there are universities where both Electrical Engineering and Computer Science are combined into one department. One famous example is EECS, UC Berkley. In such a case, it really doesn't matter. You will be working under the umbrella of EECS or CSEE.

  • Further, another thing is that it is not what the PhD is going to be or what they offer. It is "you" who will decide what do you want to do in your PhD. Is it going to be a PhD in applied machine learning or theoretical machine learning? Is it specific to robotics or computer vision? and such like. Go through the websites of your favourite (and targetted) universities department, and choose wisely.

  • Remember, in the end, it is the work that speaks, which has a direct correlation of the quality of guidance and trainings you have got during your PhD. Not the university.

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