theKiev

Thank you everyone for the sound advice, and specific programs/individuals to consider. Very much appreciated!

I will be finishing my MS in Operations Research from Georgia Tech next fall, and would like to apply to some Statistics PhDs. I'm primarily interested in: Random Matrix Theory, Stochastic Analysis (possibly Rough Path Theory), Machine Learning Theory, and High-Dimensional Statistics (so still kind of broad). Background Info: Undergrad Institution: Big State School (90 - 100 range in USNews) Major(s): Mathematics
 Minor(s): Computer Science, Economics 
GPA: 3.72 (both cumulative and major, give or take) Type of Student: Domestic/White/Male Grad Institution: GaTech Concentration: Operations Research (MS) GPA (so far): 4.0 
GRE General Test:
 Q: 169 V: 163 W: 5.0
 GRE Subject Test in Mathematics: 880 Programs Applying: Statistics, several math/applied math/OR programs probably. Research Experience: Undergraduate: ~7 Months in the Mathematics Department developing software tools to help several professors visualize some of the concepts they were researching (somewhat like these). Summer internship in Natural Language Processing. Post-undergraduate: Spent about 1 1/2 years at a top 5 business school as a Research Assistant. 1 project resulted in a paper in finance (not a co-author, but my name in a footnote if that means anything). Graduate: Internship at a well-known tech company this summer. Will be working in a lab group starting in August for a few months till I finish. Awards/Honors/Recognitions: Phi Beta Kappa, some small recognitions/scholarships here and there. Letters of Recommendation: 2 from research advisors, 2 from professors who taught graduate classes. Math/Statistics Grades: Undergraduate: Probability (A), Math Stats (B-), Analysis I (A-), Analysis II (A), Econometrics (A-), Operations Research (A-), Machine Learning (A), Intro to Proofs (B+), Calc III (A-), Linear Algebra (A). Graduate PhD taken (all As): Linear Optimization, Nonlinear Optimization, Real Analysis I, Probability I, Stochastic Processes I & II (more applied, but there are proofs), Theoretical Statistics, Probabilistic Graphical Models, High-Dimensional Statistics. Graduate PhD to take: Probability II, Simulation Theory, Algorithms (CS theory course) Schools: NCSU, Washington, Chicago, Duke, Berkeley, Columbia, UCLA, and Yale (small, I know, but a professor of particular interest there). Misc: Given my mediocre undergraduate grades, I'm not sure if there are schools I should add/delete from the above list. Ideally, I’d like to keep it in the 5-8 range. Some of my advisors are certain that some schools will place quite a bit more weight on my undergraduate record versus grad classes/research/gre, but they are a bit vague on which programs those are in terms of Statistics PhDs (obviously I'd like to minimize my applications to such schools).