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Profile Evaluation for Stats PhD


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I'm planning to take a few years off to work first before applying to PhD programs so any advice to make my profile stronger would be appreciated. I'm not too sure where I stand as an applicant to Statistics PhDs.

Undergrad Institution: One of top schools in Canada

Triple Major: Statistics, Pure Math, Mathematical Finance
GPA:  3.92
Type of Student: International
GRE General Test: Haven't taken it yet

Research Experience & Recommendation Letters:

- One semester in number theory with a math professor

- One semester in probability theory with a statistics professor

- One semester in computational statistics with a statistics professor

No papers were published. I did quite a bit of work for the first and third professors so I'm expecting their recommendation letters would be strong. The second recommendation letter might be a bit weaker as I didn't achieve much other than some light experimental coding. 

A bit worried about the no papers published part here...

Relevant Classes 

- Math: Linear Algebra 1 & 2, Real Analysis, Measure Theory, Functional Analysis, Differential Geometry, Group Theory, Galois Theory, Numerical Methods for PDEs, Modular Forms

- Stats: Stochastic Processes 1 & 2, Stochastic Calculus (Measure Theoretic), Mathematical Statistics, Linear Models, Estimation and Hypothesis Testing, Time Series, Bayesian Statistics, Sampling and Experimental Design

- Miscellaneous

     - other mathematical finance courses (extreme value theory etc.), CS courses (neural networks etc.), applied math courses (numerical methods etc.)

     - 4 internships in data science during undergrad and potentially a few years of work experience post grad

I got A in all math and stats classes.

Schools:
Statistics PhDs: Harvard, Stanford, Berkeley, UWashington, Uchicago, CMU, Columbia

Operations Research PhDs: MIT, Princeton

I'm also planning to apply to CS departments where there are cross faculty with stats.

Research Interests:

Not too sure about research interests yet but I'm mainly interested in:

1. Computational and Bayesian Statistics

2. Theoretical/Applied Machine Learning

3. Probability Theory

Edited by Tuan Hiep Do
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You've basically listed all of the most competitive programs in the country.  You might have a chance at them, but this cannot be your entire list of schools.

Your profile is strong in that you have good grades from a good school and a a very strong math background - your research experience is sufficient, but without publications doesn't really stand out (at least from the details you've provided).  I'd widen your range through the top 30 on US News.

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@bayessays Thank you for the reply! Yeah, I should definitely include other schools in the mix as well. Do you have any recommendations on how to boost up my research experience by any chance? I'll be graduating soon... so is contacting profs for voluntary research after graduation a thing? Or should I go back for a thesis master?

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I think your research is fine - research is a big commitment, so I don't think it's worth it to go out of your way to get publications or anything like that.  If you have three letters from tenure-track professors in stats/math at one of the top schools in Canada, and they are very positive letters, you're in great shape.

A master's can definitely help, especially as an international student, but I don't think it's absolutely necessary.

If I were you, I'd just expand your list - apply to additional schools like UT-Austin, Ohio State, Illinois, that are great programs but not at the very top.  See how your results are, and re-evaluate if you need to.

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