Fall 2020 Statistics PhD Application Evaluation

[TombRaver]

Hi all,

I am a senior undergraduate student and going to graduate in the coming December. I am considering applying PhD programs in statistics for fall 2020. I want to do Machine learning or network data analysis for my PhD. My biggest concern is that my background is not very statistically oriented and I hope I could get some advice. Any feedback would be greatly appreciated!!

Undergrad Institution: University of Hong Kong (Freshmen, Sophomore),  UIUC
Major(s): Actuarial Science
Minor(s): Computer Science
GPA: 3.56(HKU)/ 3.94 (UIUC)

Type of Student: Domestic Asian Male

Statistics Courses: Linear Regression(A) , Statistical Machine Learning (A), Stochastic Processes (A), Probability Theory I (B), Probability Theory II (A)

Math Courses: Numerical Methods (A), Linear Algebra (A+), Real Analysis (?)

Computer Science Courses: Java Programming (A), Data Structure (A), Discrete Math( A+) , Data Mining (A), System Programming (?), Database Systems (?)

GRE: haven't taken yet

 

Research Experience:

1. Group undergraduate research on optimal investment strategies for pension plans. Made a poster and presented it in a actuarial science symposium

2. Contacting professor and hopefully will do a research on Machine learning

 

Work Experience:

Actuarial Internship at AIG. Worked on coding for pricing and some demographic analysis on pension plans

Recommendation letters: Should be fairly standard. 

 

School List: Need advice on where to apply. None of my friends are pursuing PhD so I have no idea which tier I should aim. 

 

I am really worried about my GPA before I transferred to UIUC. The courses at HKU were much harder and the professors were stricter in giving good grades as well. The average for probability theory I was C because the professor was new to the school and he made the exam extremely hard. Any comments are appreciated. Thanks in advance!!