Undergrad Institution: UC Berkeley (large public school) Major(s): Applied Math Minor(s): Data Science GPA: 3.8 overall, 3.75 major
Type of Student: Domestic Asian Male
GRE General Test: Q: 166 V: 167 W: Not released yet but 4.5-5.5 expected GRE Subject Test in Mathematics: N/A (not offered in 2021 anymore due to Covid-19)
Programs Applying: Statistics PhD
Research Experience: (At your school or elsewhere? What field? How much time? Any publications or conference talks etc...)
None really, am doing a directed reading program where I will be self learning a topic of my choosing (stochastic differential equations) while supervised by a 3rd year Math PhD student
Relevant Coursework: Real Analysis, Numerical Analysis, Bayesian Inference, Linear Modeling, Time Series, Probability Theory, Statistical Methods, Linear Algebra, Abstract Algebra, computer programming in python, data science foundations (basically doing stats in Python)
Awards/Honors/Recognitions:
Dean's list every semester
Pertinent Activities or Jobs:
Math tutor and study group leader: led classroom style study groups twice a week for Calc II (Calc BC equivalent) where I prepared worksheets, and lesson plans
Quantitative Consulting at large financial firm: worked with ML model validation and analyzing parameters and model assumptions
Letters of Recommendation:
Stats Prof - knows me fairly well has been guiding me with grad school apps past year
Stats Prof - also knows me fairly well
Math prof - real analysis professor, seems to like me pretty well, am currently in his course
Any Miscellaneous Points that Might Help:
All my letters of recs are from assistant profs, so nobody too established
Applying to Where: Stats unless stated otherwise
UCSB
USC (Data science and Operations)
UCLA
Northwestern
Yale
Columbia
Penn
Duke
University of Washington, Seattle
Any other recs for schools?