Am I being foolish?

[stat_phd_11]

Shout out to cyberwulf and Biostat_student_22, as well as anyone else who can provide insight.

Currently, I am only applying to 7 biostat phd programs:

Harvard (reach)

Hopkins (reach)

Emory (target)

UPenn (target)

Brown (target)

BU (safety)

Vanderbilt (safety)

Am I being foolish by applying to too few? Is there a chance I don't get into any?  If so, how many more safeties/comforts/reaches should I seek to apply to?

My profile is as follows:

Undergrad Institution: well regarded public undergrad
Major(s): Statistics, Mathematics
GPA in Major:  3.92
Overall GPA: 3.97

GRE Scores (revised version):
Q: 170
V: 158
AW: 4.0

Research Experience: SIBS after freshman year, 1.5 year bioinformatics/biostat research project (summer full time, semesters part time), an intensive biostat REU (4 potential publications, none submitted yet)

Awards/Honors/Recognitions: deans list all semesters, I have attended many statistical/biological conferences (attended 8, presented at 4, won awards at 2)

Programming: R (pretty strong), SAS (moderate), Python (pretty strong)

Pertinent Activities or Jobs: 4 semesters as calculus TA, 2 years as RA

Letters of Recommendation: 1 research prof, 1 class and research prof, 1 class prof (all strong)

Stats Courses taken: SAS, Statistical Computing (R), Probability Theory, Survey Sampling, Environmental Statistics, Multivariate Methods

Proof-based courses: Real Analysis I and II,  Mathematical Statistics

Other courses: Linear Algebra, Diff-Eq, Calc I-III, Bioinformatics, Python

 

Other schools I might consider include:

Washington (reach)

Minnesota (comfort)

Pitt (safety)

UC Davis (safety)

[Biostat_Assistant_Prof]

Looks like a solid applicant profile from my perspective. Based off of this information, your safety's are definitely safety's, but I would even consider your target schools as pretty solid bets. On top of Harvard and Hopkins, I'd include applications to Washington, Michigan, and UNC, and of those 5, I'd be surprised if you didn't get into at least a few.