2020 Statistics PhD/MS Profile Evaluation

[TombRaver]

Undergrad Institution : UIUC

Major(s): Actuarial Science 
GPA: 3.94

Minor(s): Computer Science

 

Type of Student: Domestic, Asian Male

 

Math/Stat Grades: 

Numerical Methods (A)

Discrete Math (A+)

Abstract Linear Algebra (A+)

Probability Theory I,II (B+, A)

Stochastic Process (B+)

Machine Learning (A)

Intro to Regression (A)

Some Actuarial math courses (Mostly A)

 

Math/Stat Courses Taking:

Real Analysis, Combinatorics, Time Series, Differential Equations

GRE General Test: 153 V/ 170Q / W unknown yet

 

Programs Applying: Statistics
Research Experience: 1. Did a undergraduate research on pension funds, presented outcomes in a symposium 

                                        2. Currently doing a research about machine learning in financial mathematics

Pertinent Activities or Jobs:  1. Course assistant for Introductory computer science course

                                                     2. Actuarial internship

 

Letters of Recommendation: One professor who supervised the undergraduate research project. I hope I will get two more LoRs from the professors I am currently working with.

Research Interest: Mathematical Statistics, Stochastic Processes, Network Science.

 

Reach School:

CMU, Duke, UPenn, Columbia

 

Target:

UMich, Purdue, UCLA, UIUC, Madison, UC Davis, NC State, NC Chapel Hill 

 

My biggest concern is my weak research experience. All the research experiences I have listed are undergraduate research projects which are supervised by math/actuarial science professors. In addition, my overall GPA might be overstated. I studied overseas in Hong Kong in my freshmen and sophomore year, and I did poorly (~3.5 GPA). This is partly due to the fact that in some courses there's no curve despite that most students were doing poorly. I think a 3.3 GPA in Hong Kong is approximately 3.5-3.6 GPA in US considering the difficulties.

 

 

I'm really unsure of the type of school I am competitive for. Recommendations to my list are appreciated.

 

Thanks!