asphalt_2015_

I'm not 100% on how the departments break down at the universities, or what the policy is for applying to multiple departments, but I was thinking: Cornell ORIE, Columbia IEOR / Stats, CMU Stats/ML, GA Tech OR, Penn (both programs are in Wharton and seem to be pretty small, though the network data science center looks interesting), Duke Statistical Science, Michigan OR/Stats. I don't really know of too many others like Cornell and Columbia that emphasize optimization and applied ML, though I'm definitely interested in OR programs which have good coverage in both areas.

Hi, I'm looking to apply to OR/Stats programs (interested in OR, optimization, stats/machine learning) and a profile evaluation would be super helpful. My biggest worry is that I don't have a very strong proof-based math background: I'll be taking more during my senior year, and don't know if that by itself is a good enough reason to take a year off and work before starting a PhD. I'm ultimately interested in applied stats, optimization, algorithmic game theory, or some mix thereof. Hoping to apply to places like Cornell, Columbia, CMU, GA Tech, Penn, Duke, Michigan, as well as other OR programs. The new IDSS program at MIT would ultimately be my ideal program, though it's just starting out. GPA: 3.74 Program: Operations Research (includes financial engineering, applied probability, etc) at a top US university Coursework: Probability & Stochastic Systems (A), Statistics/ML (A), Theoretical Machine Learning (A), Advanced Calc (B+)/Linear Algebra (A-), Diff E. (A-), Optimization (B+), various CS courses, advanced microeconomics courses (A-/A), others Research experience: no publications, independent applied statistics project with a conference presentation (sole author), ongoing work with research advisor from last summer. I'll be taking a grad statistics course in the fall, as well as more proof-based math courses. Won't be able to take real analysis until the spring.