Hi everyone,
I'm interested in a PhD program in statistics and/or machine learning. I am a junior as of fall 2016 but think I should give myself a head start. Any feedbacks will be much appreciated!
Undergrad Institution: Carnegie Mellon
Major: Statistics and Machine Learning, Math
GPA: 3.95
Type of Student: International (Chinese)
Courses and Background:
Undergrad level: Calculus 1-3, Differential Equation, Abstract Algebra, Linear Algebra, Real Analysis 1,2, Discrete Math, Combinatorics, Stochastic Calculus, Discrete-Time and Continuous-Time Finance, Mathematical Statistics and Inference, Modern Regression, Advanced Statistical Methods, Data Mining
Graduate level: Machine Learning (PhD), Graphical Models, Statistical Computing (All A's)
GRE Score: V - 165 Q - 170
GRE Math: Haven't Taken
Computing: R, Python, C, Matlab; Scripting: Latex
Research Experience: I don't have any REU's due to my nationality
Research Assistant for a project in operations research and statistics.
(Probably) research assistant for modeling infectious disease
Summer Undergraduate Research Fellowship in statistics and algorithmic trading
Will be working on a senior thesis based on my summer research
Other Relevant Experience
Teaching Assistant for Intro to Computer Science
Grader for Statistical Inference and Proof-based math
Math Tutor
Honor: same old, same old...dean's list
Letter of Recommendation: I'm still working on this part
My boss (my SURF and thesis advisor)
TBD
TBD
Thinking about applying for:
Stanford (...dream?)
Berkeley (reach)
Chicago (reach)
Princeton ORFE ( unorthodox, but I'm interested in statistical methods in finance )
Duke
UMich
NC State
Columbia
and of course, CMU
I'm afraid that this list is too front-heavy, and I'm really looking forward to any advice and suggestions!