gwynn sturdevant is a postdoctoral fellow at the Laboratory for Innovation Science at Harvard. In her most recent position, she worked on analytical projects in the rail and the aviation sectors including: improving Terminal Arrival Efficiency Rate estimation, developing an algorithm to predict train arrival times in a multi-agency rail operating environment, and developing methods to produce unbiased algorithmic results. gwynn developed an extensive Shiny application to assist in balancing trials as a postdoctoral fellow with Ken Kleinman (University of Massachusetts, Amherst and Harvard University). gwynn has a PhD in Statistics from the University of Auckland, the birthplace of R, where she studied under Thomas Lumley (University of Auckland and University of Washington) and Ross Ihaka. She focused on finding long-term effects, after cessation of treatments, when noisy measurements cross a threshold in biometric data.