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Undergrad Institution: UC Berkeley Major: Applied Mathematics GPA: 4.0 Type of Student: Domestic Male GRE General Test: Q: 170 (94%) V: 161 (87-88%) W: 5.0 (91%) Programs Applying: Statistics + Data Science Research Experience: - One summer REU in deep learning and natural language processing. This research poured into the school year with a part-time research job. - The following summer, more research on a different project, involving time series analysis. Awards/Honors/Recognitions: PBK + summa cum laude (both of these are just related to my grade) Pertinent Activities or Jobs: Student Researcher, Film Club Treasurer Letters of Recommendation: 1. PI from the math summer REU, who is actually a professor of literature and digital humanities; pretty strong, I would think 2. Program director at research program #2, a professor of math; also pretty strong 3. Teacher for my numerical analysis class; probably less strong, but I wanted at least one recommendation to come from my school. Math/Statistics Grades: analysis (A+), linear algebra (A+), abstract algebra (A+), complex analysis (A), numerical analysis (A), probability (A+), time series, machine learning. All A or higher Any Miscellaneous Points that Might Help: My interest in grad school is in statistical machine learning and sequenced datasets (like time series). Applying to Where: (Color use here is welcome) University of Washington - PhD Statistics / Admitted 02/02/24 / Accepted/Declined UC Davis - PhD Statistics / Admitted 01/20/24 / Accepted/Declined UCLA - MS Statistics / Admitted 03/22/24 / Accepted/Declined UCSB - PhD Statistics / Admitted 02/14/24 / Accepted/Declined UCSD - PhD Data Science / Pending.... / Accepted/Declined Stanford - PhD Statistics / Rejected 02/07/24 -> Admitted to MS on 03/26/24 / Accepted/Declined I'm very grateful to have gotten into UW, which is a competitive program, and while I likely won't attend Stanford due to the cost, it was cool that they kinda accepted me. Still deciding which is the best program; my aim is not academia but a research-oriented job in industry, something I would not really be able to get out of undergrad. I also applied to the west coast, as I want to be reasonably close to family and friends. I wish I could hear back from UCSD, as a data science PhD sounds interesting, but I may end up making a decision before then....

I was fortunate to be admitted into the three programs (in statistics) above. So far, I have been leaning towards Washington, as it is really well-regarded, fits my research interests, and seems like a good path to an industry job. But I have had some slight worries about Seattle location/winters. I visited campus a couple weeks back and liked it quite a bit, but I'm from LA and the sunny weather here is pretty hard to beat; UCSB, while not the strongest program and moreover sort of "niche" in the emphasis on finance, is a winner for weather (except for portions of August). Davis is the in-between choice—still well-regarded but closer to CA weather. All programs have given me pretty standard funding packages, with Washington including an award for starting the program. I consider location pretty important, because staying in one area for five years is a pretty big commitment, though I know time may pass by quicker than I think. At the same time, I also am fully willing to master out if I am not succeeding as I want to be. So it's not a deal breaker! For reference, I am interested in statistical machine learning along with time series/sequenced data analysis. Currently, I'd like to eventually work in LA or SF (went to Berkeley), though I do not know Seattle too well yet. I also have somewhat low vitamin D, hence why I like the sun haha. If anyone lives near these places or has experience with these programs, I would appreciate your input. Another related question is: is it common/feasible to move cities after doing your PhD? Thank you!

I haven't been to Ann Arbor, but >41k/12 months for Berkeley should be doable. Studios are expensive, but a house/apt with roommates (but everyone has singles) should be okay for the area. A nice thing about the bay is that, if you want to do something fun or have a nice day trip, you are already in the area! There is a lot you can do to relax.

I am currently applying to grad school at UCSD, where they have a PhD in Math (specialization in Statistics) and a newer PhD in Data Science. While my original inclination was for the Math PhD, I have last minute started to lean a bit towards the new Data Science program. While I know more about the Math PhD program, as the department has been there much longer than the Data Science school, I realize that my time there might be very math theory-strong; I still have to take those famous math qual exams in algebra and topology. I still want to understand some theory, as research is an interest, but my aim is not to be a professor. I also know that UCSD has a pretty reputable data science program, so the PhD program, even while not as established, likely will be recognized as a strong program. One other thing I consider is that some of the faculty in the data science institute are also faculty for the math department. The deadline for math is Dec 6 (Wednesday), while the deadline for data science is Dec 15 (Friday after next) If you know anything about UCSD and these departments, or just stats/data science PhD programs in general, your input would be appreciated!

Hm Okay! Thanks for letting me know. I think I was considering UCLA MS because I was originally seesawing between doing a phd or doing an ms, and UCLA seemed like a good place to MS since my family lives in LA. But I mean if I were to get into the PhD and I ended up not feeling it after 2 years, I guess I could master out. Don't know how much more competitive it gets though

Undergrad Institution: Berkeley Major(s): Applied Math (concentrated in Data Science) GPA: 4.00 (might dip after my last semester, which is this fall) Type of Student: Domestic Wasian (half white half asian) male Lower Div Courses: Calc 3 (skipped 1-2, A+), Linear Algebra (A+ Intro to data science (A+) ,Intro to CS (A+) Upper Div Courses Linear Algebra (A+) ,Real Analysis (A+), Abstract Algebra (A+), Numerical Analysis (A), Principles of Data Science (A), Probability for Data Science (A+) Current Courses: Machine Learning, Time Series, Complex Analysis GRE: 170Q 161V 5W Research Experience: One summer REU at UCLA in 2022 doing natural language processing on interview transcripts, but have been doing work with the professor ever since during the school year. We made one publication in SIURO. Another summer REU at IPAM (NSF institute) this summer, which was basically revolved around a linear statistical model for navigation. No publication (yet) but plan to present poster at JMM. Both involved applied statistics, time series data, and machine learning. I also presented both at the end of both programs. Letters of Recommendation: 1 from my first REU advising professor. Another from the director of the IPAM research program. The third from my numerical analysis teacher. I think all three should be fairly positive, with the first two being much stronger as they have seen me in a research context. Teaching experience: None officially in classroom Professional experience: Besides the research, not really (though the NLP research I do is in a sense a very flexible part-time internship) Programs Applying: Statistics (PhD and MS) Applying: Stanford, UW, UCLA (MS), UCSD (math + stats), UCSB, UC Davis (MS?) All of my schools are on the west coast, because I would like to be close to family, gf, and my friends. But I was looking at this site and realized just how many programs some people are applying to... I am considering adding two more schools, assuming my recommenders are okay with it. Would that be helpful? I admit, I really want to get into Stanford (and you know, I could even do the MS there) but I know it is incredibly hard to get in. I have a pretty busy schedule because I am wrapping up my studies a semester early, but it would kinda suck if I didn't get into a program I really wanted to get into. But I also think the new schools probably won't be on the west coast