oatmeallover

A little about me: I'm a rising senior interested in an ML-focused Stats PhD Education: HYPSM Undergraduate in Statistics with CS minor (Has a great stats program) GPA: 3.6 (I have a documented disability that impairs my ability to function. I've had to take a gap year due to it and it's had an effect on my grades) My lower grades are mostly in challenging cs/stats classes and they're in the B range. I can maybe get this up to a 3.7 my senior year. GRE: I haven't take a practice test, but I did really good on my act (36) so not sure if that means anything? Type of Student: asian woman, first-generation college student Research Experience: 1.5 years in computer vision research my freshman and sophomore year, 1 year theoretical statistics research (diffusion models), summer REU research in ML at a T5 CS/Stat Institution, and will be doing a year of MCMC research over the course of my senior year. no pubs sadly. three internships. Letters of Rec: Maybe one really good one and one pretty good one. I'm hoping to get my last rec letter from my senior thesis advisor Research Interests: ML-related sounds cool, but overall figuring it out I'm thinking of taking a gap year and applying 2025 instead. That way, maybe I can figure out what research I enjoy the most, boost my GPA with better senior year grades, get a publication/ some more research experience, and chill out a little lol. My questions: What schools are reach/target/safety? I'm really hoping to have a good shot at Columbia's or NYU's program, since it's close to home. How can I boost my application? What are some options for what I can do over my gap year? I'm thinking a post-bac. Masters is not really an option financially. General advice/rant I'm overall just feeling really lost about grad school. I love research, and I absolutely love statistics, but I don't know what niche I like the most, I don't know anything about which professors are at which schools studying which things, and I'm worried I'll end up at too stressful of a program or one I don't like. Some general tips would be much appreciated, thank you!