dstatsapp2020

Hey everyone, I'm planning on applying to a PhD Stats program to start in Fall 2020 and I am looking for application evaluation and advice. I personally feel like the schools I'm looking at are overreaches for me and I should reset my expectations. I just graduated with a Data Science degree. The program was split between computer science (with emphasis on machine learning and databases) and statistics. I want to pursue the data science route, and I feel like going into statistics is the best way to do so (I also feel more statistically inclined). I'm looking for a program with more emphasis on statistical applications rather than theory. I'm not too set on what type of research I'm interested in, but I know that I'd be interested in research in bio stats and a combination of statistics and social sciences. I know my grades aren't the best, which is why I want some feedback. I performed a lot better in my upper division classes, so I don't know how much my grades will affect my application since they don't exactly stand out. Undergrad Institution: UC Irvine Major: Data Science GPA: 3.628 Student Type: Domestic Asian Male GRE General Test: Verbal 156, Quant 168, Writing 4.5 Courses: Math: Intro to Linear Algebra (B+), Multivariable Calculus (B+), Discrete Math (A) Stats: Project in Data Science Intro to Probability & Statistics (3 quarters, B/B+/B-), Statistical Methods for Data Analysis (3 quarters, B/A+/A+), Intro to Bayesian Data Analysis (A+), Multivariable Statistical Methods (A), Statistical Computing & Exploratory Data Analysis (B) Computer Science: Data Structures (B), Machine Learning & Data Mining (A), Intro to Data Management (B), Algorithms (B+), Intro to AI (A-), Information Retrieval (A), Programming in C++ (A-), Programming in Java (A-), Intro to Software Engineering (B+), Intro to Computer Organization (A), Information Visualization (A) Programs Applying: PhD in Statistics Research Experience: Took a project class in Data Science but used ongoing research as my project. Work included the full data cleaning process, data mining, implementing models using machine learning to help classify. Aim is to have it published, but the work isn't done yet. Worked with a professor to take statistical models regarding PFAS chemicals and visualize them. Built a website from scratch to house the visualizations as a tool for other researchers to use. In the process of publication. Currently doing machine learning (computer vision) research at an institute. Awards/honors: Dean's Honor List for a couple quarters. Programming Experience: Python, R, SQL, C++, Java Teaching Experience: NA Letters of Recommendation: I will have one from a public health professor (has a MS in Stats from UC Davis and a PhD in PubHealth from UW). Will get another letter from my current research advisor (got a PhD in CS from NYU). The last one will either come from my advisor on my DS research project or the professor that oversaw the project in DS class. Only concern with this letter is that my advisor is a PhD student. He knows me much better than my professor, but the professor works in Statistics (former UW faculty) and my advisor isn't in a Stats program. Applying to where: Currently an incomplete list: University of Washington (definitely my top choice, but I know it's one of the best to attend and my chances of admission is probably slim) UCLA Columbia Duke UC Santa Cruz (because of their emphasis on Bayesian Statistics) UC Irvine UMichigan UOregon Northwestern If anyone has any other suggestions regarding schools I'd appreciate it. Any suggestion/feedback would be absolutely amazing. Thanks!