Hello everyone,
I transferred from one mediocre college in China to Cornell last year and switched my major from Biology into Statistics. I am now a rising senior and not sure about if my profile is strong enough to apply for PhD/MA programs in Biostatistics and /or Statistics in 2020 fall. I didn't know before math capacity is one of the most important factors to be considered in application so the math courses I took was very limited. My advisor gave me some positive feedback and encouraged me to apply for some statistics PhD programs but I am still worried about my background.
Undergraduate Institution: China Agricultural University (transferred) ----> Cornell
Majors: Biological Sciences (previously) ----> Biometry and Statistics (Now)
GPA: 3.84/4.00 (China) --> 3.92/4.30 (Cornell, it is also my major GPA)
Type of Student: International (Asian female)
Courses taken:
In China: (doing good in Bio/Chem but not prominent in my math grades)
Stat: Probability Theory and Mathematical Statistics(A-), Linear Algebra (A-)
Math: Advanced Math A-I (A-, equivalent to Calculus I and II), Advanced Math A-II (B+, equivalent to Multi-variable Calculus and Differential Equation)
CS: Intro to Information and Computational Thinking (Using Python, A-)
At Cornell:
Stat: Probability Model and Inference (A+), Biological Statistics (A), Linear Model with Matrices (A+, graduate level), Theory of Statistics (A+), Categorical Data Analysis (B+), Statistical Computing (A+)
Math: Intro to Real Analysis (A), Numerical Analysis: Solving Linear and Non-linear System (B)
CS: Object-Oriented Programming and Data Structure (Using Java, A-)
Courses will take this fall:
Math: Measure theory (graduate level), Combinatorics, Linear Algebra (upper division, proof-based)
CS: Machine Learning for Intelligent System, Data Structure and Functional Programming
GRE General Test: Q: 169 ; V: 159 (taken 5 days ago, W scores not released yet)
GRE Subject Math: will take this September
Research Experience:
Noise Reduction for Experimental Time-domain Signals (September 2018-Present, National Biomedical Center for Advanced ESR Technology at Cornell);
Machine learning in Brain-Computer Interface and Cybersecurity (January-March 2019, A 7-week research authorized by a professor at Berkeley)
Quantile Regression Analysis for High Dimensional Data: Right-to-Carry Laws and Violent Crime (this summer, supervised by a well-known professor at Department of Statistics at Cornell)
Working Experience:
Data Analyst Intern at China Asset Management co. LTD (June 2018)
Awards: First-class for Academic Excellence (in China), First Prize for Data Castle (a nationwide machine learning competition in China), One year of Dean's List (Cornell)
Letters of Recommendation: Two from the professors who supervised my research, one from my academic advisor (also get 2 A+ in his classes)
School List:
Berkeley Biostats MA (the one with funding) is my dream program. I heard it is more relevant to data science rather than traditional biostatistics but is as competitive as PhD program.
Some PhD programs I am considering would be: UCLA biostats, UC-Davis stats, UCSD biostats (I like California), Emory Biostats, Cornell Stats
My advisor also encourges me to apply for some good PhD biostats program at JHU, UNC, NCSU, Duke, Texas A&M, UW and Umich (I think it is very tough based on my current profile).
I haven't decided yet if I should apply for those programs in 20 Fall or 21 Fall. I know if I apply in 2021, I can take more math courses, even at PhD levels, and do more non-trivial research. But I am nor sure if it is worthwhile to wait for one more year. I cannot make up my mind.
Thank you in advance for your time and advice!