Graduate admissions is a genre. Committees read hundreds of files, fast, looking for specific signals — and most applicants are guessing at what those signals are.
I finished my PhD at an R1 in 2026, taught graduate methods and statistics there, and went through the fellowship and application gauntlet recently enough to remember exactly how it works. I review applications the way a methodologist reviews a design: what claim is this file making, what's the evidence, and where does it fail to hold up?
Line-level edit plus structural rebuild where needed — the argument of the essay, not just the prose. Two rounds.
Framing, contribution, and methods sections that read as competent to faculty reviewers. This is where strong files quietly die.
What to cut, what to foreground, and an honest read on where your profile lands — reach, match, and safety, with reasons.
For current graduate students: design, measurement, and analysis consulting from someone who teaches it.
Discovery calls are free. Send your materials and your deadline; I'll tell you what's realistic.
Applying this cycle? Start early.