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!