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About mlking

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    2019 Fall
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  1. Undergrad: one of the UT schools (I'm also currently in the combined master's program after I finished my bachelor's in May) GPA: 3.95 GRE: V 159, Q 170, AW 4 Relevant Courses (all As and A+s): standard calculus sequence, linear algebra, prob and stats, probability theory (no measure theory tho), stochastic processes, probabilistic graphical models (currently taking analysis 1 and self-studying measure theory) Rec Letters: from 3 research advisors; 1 I worked under during freshman & sophomore year (big name EE guy; letter should be decent); 2 junior professors currently supervising me (since senior year), letters should be very strong. Research: Worked on 1 EE project, 3 CS projects; one CS paper from last year was rejected multiple times, now on ArXiv and under submission to a workshop; one paper (3rd author) submitted to AISTATS; currently 2 papers (first author) will submit to ICML in January 2019. Currently my list includes about a dozen schools that are top 50 on csrankings.org: Tier 1: Stanford, MIT, Berkeley, Princeton, Columbia, Yale, Caltech Tier 2: UCI, UT Austin, JHU, BU Tier 3: UMass, UT Dallas I lean towards theory (applied probability, Bayesian non-parametrics, stochastic optimization), hence statistics programs, but I'm not sure if my math coursework is sufficient. I also like coding and think I'm pretty good at it. I'm having a hard time deciding, especially for schools where faculties I'm interested in are affiliated with both departments (I guess whichever is easier to get in would be fine for me; I heard stats programs might be comparatively easier). I have a feeling I may be reaching too high, and I would appreciate suggestions for more tier 2 and 3 schools.
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