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
Courses:
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
Concerns:
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.
