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[D] What should I do?

Hi, I’m a math major at the University of Alberta, with a 3.8 gpa.

I’m not anything super special, and I think that my ability to math is pretty subpar and I’m probably not capable of doing a PhD in math. ML is something that always interested me (read a good chunk of Pattern Recognition and Machine Learning and all of Reinforcement Learning over the past year, worked as a MLE for a small stint) but I have 0 research experience.

My big pluses would be:

  • 3.8 GPA in mostly pure math isn’t too shabby (got a B- in Real Analysis II though, which looks very very bad for PhD applications in pure math)
  • A+ achieved in the introduction to machine learning course offered at my university
  • Currently on the final stretch of an internship at LinkedIn as an Infra SWE, built a cute little compiler which generates linear algebra kernels for sparse tensors
  • Going to intern at Jane Street Capital next summer (prestige wise it’s pretty much the best an undergrad could do in terms of SWE)

My big minuses would be:

  • 0 research experience
  • B- in Real Analysis II (got an A in Real Analysis I though)
  • Have not written the GRE (pretty much limits me to masters programs in Canada I think)

I’m mainly concerned with getting a PhD anywhere, I’m not too concerned with getting a PhD at somewhere prestigious. I have 3 semesters left in my degree, all of which are light (I have 4 very difficult math courses left, 1 CS course (compilers), 2 english courses and 4 arts courses which I plan to break into semesters of 4, 4, 3 courses). I have some background in compilers (read a good portion of Engineering A Compiler while I was at LinkedIn in order to do my project) which might be an interesting intersection. I’m taking a Reinforcement Learning class next semester, and I’m preparing to knock it out of the park.

What should I do within my last 3 semesters in order to maximize my quality of PhD acceptances come the end of my undergrad?

submitted by /u/OriginalMoment
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.