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!

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), UIUCMajor(s): Actuarial ScienceMinor(s): Computer ScienceGPA: 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!!