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Profile Evaluation & Program Recommendations, PhD Statistics

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Undergrad Institution: Rice University  (if anybody has questions about programs here, reach out!)

Major: Statistics

GPA: 3.68 / 4.33

Type of Student: Domestic

GRE General Test: 169 quant, 163 verbal, 4 writing

GRE Subject Test in Mathematics: N/A

Research Experience: 

(1) Since August: applying ML to neuroscience problems with professor who does lots of ML
(1) REU in Biostatistics, no publication
(2) Designed, ran and analyzed survey for Houston Parks Department


Currently enrolled in a Bayesian statistics course and functional analysis, planning to take abstract algebra and topology next semester

Parallel Programming (A)
Statistical Machine Learning (A)
Neural Networks (A)
Probability (B-)
Honors Linear Algebra (B+)
Data Science Tools (A)
Functional Programming (A-)
Algorithms and Data Structures (C)
Intro CS (A+)
Experimental Design (A+)
Linear Regression (A+)
R Programming (A+)
Honors Analysis (C+, as a sophomore)
Intro to Optimization (B)
Probability & Statistics (A-)
Honors Calculus IV (A)
Honors Calculus III (B)

Dual credit from high school:
Linear Algebra (A)
Differential Equations (A)

Letters of Recommendation:

(1) Advisor for Biostat REU, who is also on the UW Biostat faculty
(2) Professor from Data Science Tools course, which I currently TA
(3) Either undergrad advisor or professor who taught my ML class (different from professor I'm currently doing research with)

Work experience: NA

Applying to:  

PhD Statistics Programs

Dream: CMU, Berkeley, UW

Other: Michigan, UNC Chapel Hill, Madison (?), Wharton (?), Cornell (?), Columbia (?),  UCLA (?), UC Davis (?) advice please




1. Lower grades in more mathy classes, not much research
2. I have no clue where to apply. I feel like I have typically done well in applied courses but that I'd like to get more into theory, which I've struggled with. I enjoy optimization and ML theory.

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