fatcat2 Posted August 8, 2023 Posted August 8, 2023 Mainly concerned about my low? GPA and unsure of the strength of my rec letters. Not super familiar with statistics phd admissions either so I'm not sure where I stand as an applicant for these programs. Any advice would be appreciated. Will also be applying to ~10 EE/CS PhD programs, this post is just for stats. Undergrad Institution: UC Berkeley Double Major: Computer Science and Applied MathGPA: 3.65 (major gpa above 3.7)Type of Student: domesticGRE General Test: not planning on applying to programs that require it. Research Experience: Worked in deep learning research for a year, co-author of paper accepted at ICML. Industry research internship one summer in machine learning, and currently leading a ML adjacent research project with a bit more of a theory component. Broadly interested in statistical machine learning, high dimensional statistics, information theory, but I also find myself becoming more and more interested in other areas of statistics as I learn more about it like bayesian inference and causal inference. Letters of Recommendation: Strong letter from industry research internship - wrote the draft myself and pretty sure they are submitting it as is. Assistant CS Prof: I feel that I didn't contribute as heavily to the ICML project as I could have, and most of the efforts were led by a masters student. So I'm not sure how much the ICML name will really help my application. The letter will be at least decent/good but definitely not the outstanding kind that can get you into anywhere. Very well established EECS prof: For the project that I'm leading, I meet mostly with a grad student to discuss progress and don't have as many interactions with the professor. Hoping to turn it into a publication by the end of this year, aiming to have a preprint asap. Mostly focusing on this component of my app for the rest of the year. Hopeful that this can potentially be a strong letter.Relevant Classes Probability & Random Processes (A), Real Analysis (A-), Convex Optimization (A-), Linear Algebra&Differential Equations (A), Multivariable Calc (A-), Signals&Systems(A), Graduate Information Theory (A-), Machine Learning (B), Artificial Intelligence (A-), Data Science (A), Mathematical Statistics (currently taking), Numerical Analysis (currently taking), Abstract Algebra (to take this fall), Complex Analysis (to take this fall). A-/A in other CS courses with a few B+. Schools: Current list for stat phd. very interested in the first five but unsure of chances: Columbia, UW, UMich, Yale, U of Toronto, UNC Chapel Hill, NCSU, Wisconsin-Madison, UPitt, ASU MS/MA Statistics: Columbia, UW, U of Toronto Also will apply for around 10 EE/CS PhDs and also considering operations research PhDs
dirichletprior Posted August 11, 2023 Posted August 11, 2023 (edited) Your GPA is definitely on the lower end for Columbia, Yale, UW, and UMich, but your research experience and coursework are on par. In general, I would recommend applying to many programs (provided you are interested in the research there). The T20 Statistics PhD programs are incredibly competitive nowadays and accept 5-10% of applicants. Edited August 11, 2023 by dirichletprior
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