Fall 2019 Profile Evaluation & School Suggestions - Statistics PhD

[Martingale]

Undergraduate Institution: University of Virginia

Major//Minor: Statistics (Interdisciplinary BA with a concentration in Econometrics) // Physics

Cumulative GPA: 3.83

Major GPA: 3.84

Student Type: Domestic White Male

GRE General Test: TBD

Classes: 

   A+: Mathematical Probability

   A: Calc 3, Macroecon, [Physics-motivated programming class teaching C], Regression Analysis [with SAS], Data Analysis with Python, [Stats class teaching R], [Stats class on database usage/manipulation focusing on SQL], Statistical Machine Learning, Intro Physics 1, Ordinary Differential Equations

   A-: Astrophysics 1, Intro Physics 2, Linear Algebra, Stochastic Processes

   B+: Modern Physics, Intro Mathematical Statistics

   In progress: Basic Real Analysis, Statistical Physics, Nonparametric Statistics, Survival Analysis and Reliability Theory, Applied Time Series

 

Programming Experience: R, SAS, Python, C, MATLAB, SQL, Minecraft Redstone

 

Research Experience: I worked in the Chemistry Department from my very first semester through the end of my first summer performing research on signal analysis; model fitting to fluorescence lifetime decay data; decomposing mixed spectral data into individual absorption spectra; and various simulations including photon absorption rates, effects of various diff eqns on proposed systems, and effects of arbitrary optical filters on data collection. I also worked on interfacing the data collection instruments with different programs. Since then, for the past two years I've been working in the Biomedical Engineering Department focusing primarily on image analysis techniques and novel ways to analyze the resulting data (in broad strokes). During this time, I have also worked on different projects in the lab including simple cellular system simulations; creating data visualizations for 3D cellular systems from 2D slices, among other data presentation methods; and ratiometric analysis for different nanoparticles.

Research Interests: As you can see, I have bounced around working on several different subjects. Broadly, my interests are in applications of methods or techniques across disciplines. Statistics is in everything, and I want to see how bringing together different fields can improve the methods of both parties. For example, I found great enjoyment when I found parallels between statistical analysis of video games and bio systems and was able to use ideas from the former to enhance the latter (if only slightly). I realize this is very vague, but I'm an undergraduate student; what do you expect? I am definitely more applied-oriented, and I'm very open to learning about other applications of statistics in any field.

 

Publications: 

   Submitted before deadlines: Between third and sixth author on a paper which uses a 3D graphic of mine and uses a simulation technique of mine [minor to moderate impact journal]. Third author on a review paper of vessel analysis methods [minor impact journal]. First co-author on the paper about my primary research and the statistical techniques developed to analyze the data [moderate to high impact journal]

   Most likely submitted in December: Between third and sixth author on a paper which uses data gathered using my program [moderate impact journal].

 

Teaching Experience: I was a TA for a graduate level chemistry course my second semester of my first year, and I was a TA for the intro stats class. For what it's worth, I've been a private tutor in statistics for two semesters.

Teaching Interests: My greatest passion is teaching. I absolutely want to go to a program where I will have greatest opportunities to teach.

 

Letters of Recommendation: Strong letter from a statistics junior faculty member with whom I've worked since Fall 2017 as a TA and throughout this summer developing new course materials for the intro stats class. Strong letter from a statistics faculty member whose class I took, and with whom I have maintained a dialogue since Spring 2018. At this point she's very familiar with me, my interests, and my abilities. Lastly, a very strong letter from the head of the lab I've been working in for 2 years (Senior faculty in the BME department).

 

My Questions: I don't have GRE scores yet so let that be a variable. Assuming I get at least a 166-168 on the Quantitative section, and I don't flub the others, what range of schools are within my reach? I am extraordinarily confident that I will be accepted to UVA, but what do you think my upper limit is? My second question would be for a list of schools, if possible, you think could align well with what you believe my interests are. Geographically, I want to go to a school on the east coast where it snows in the winter. I do realize that cuts out a large portion of schools ranked between UVA and Stanford.

 

I apologize for the rather lengthy post, but with more data comes a stronger conclusion, right? I'm happy to answer any questions, and thank you very much for any comments, remarks, critiques, or advice.

 

[Stat Assistant Professor]

Your profile looks pretty strong. I would say you have a very good shot at a school like Penn State, NCSU, or a school of that caliber. It may be worthwhile to try a couple of top-tier programs like Carnegie Mellon or Duke.

Are you also interested in Biostatistics PhD programs? I think you have a very good shot at good Biostatistics PhD programs on the east coast (e.g. UPenn Perelman, UNC Chapel Hill, Emory... maybe even Harvard).

[Martingale]

Thank you very much for your reply; it's very helpful to get an outside perspective, and I appreciate your time.

I've read a bit elsewhere on the subject, but what is the difference between statistics and biostatistics programs? I imagine biostats is more applied, the courses are ones more applicable to biological settings, and the research focuses are geared towards bio fields, but is there much beyond that? Is there a significant difference in post-grad opportunities between the two programs? In my head I see biostats programs as somewhat limiting the scope of my post-grad life compared to a stats PhD, but I'm sure it's not so cut and dried.

I'm going to give Harvard a shot (for several reasons besides its name & rank), but as I'm sure you know already, I have to choose between the biostats and the stats programs in my application. Given my profile, is one significantly more realistic than the other for me? I won't make my decision wholly based on this, but it obviously helps guide me. I'm only picking Harvard out of the schools that offer both programs because both of its programs are very and similarly competitive, but I do have this same interest for the other schools as well.