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A Day of Celebration in Honor of Bradley Efron's Birthday
May 24, 2018 - 8:30am
Jen-Hsun Huang Engineering Center (04-080) ● Mackenzie Room, third floor ● 475 Via Ortega, Room 300

Brad Efron has been at Stanford for more than fifty years and has represented the Statistics Department, as well as leading the Mathematical and Computational Science program, for the past 30. He is best known for proposing the bootstrap resampling technique, which has had a major impact in the field of statistics and virtually every area of statistical application.

"I had a very complicated idea called 'the combination distribution' for explaining the jackknife, but the more I worked on it the simpler it got, until I was left with what seemed like almost nothing at all. And that was the bootstrap."

He has made seminal contributions to many areas of statistics, and his thinking has influenced many scientific disciplines including medicine, physics, astronomy, biology, economics, sociology, and computer science. More importantly, Brad always makes statistics fun, engaging, and important. This day-long celebration of our friend and colleague will bring his former students and collaborators back to the Farm for an Efron-centric series of presentations to thank him for sharing with us his kindness, generosity, irreverent humor, and encouraging spirit.

Plan Your Visit: Accommodations, Maps, Parking & Directions

8:30a Continental Breakfast
9:15a Welcome – Rob Tibshirani and Trevor Hastie
9:30a Arthur Peterson, Jr., University of Washington: "Censored data, randomized trials, and the teaching of statistics: Some contributions by Brad to science (and to me)"
10:00a Gary Simon, New York University: "Gerrymandering:  How bad is it?"
10:30a Morning Coffee Break
10:45a Ronald Thisted, University of Chicago: "Reproducing Shakespeare"
11:15a Abhinanda Sarkar, Mysore Royal Academy: "Reflections on the Efron view of statistics in the modern world"
12:00n Lunch @ Sequoia Hall, Jacaranda Courtyard
1:30p Terry Therneau, Mayo Clinic: "Simple problems and unexpected answers"
2:00p Samuel Kou, Harvard University: "Optimal shrinkage estimation in heteroscedastic hierarchical models: Empirical Bayes and beyond"
2:30p Afternoon Coffee Break
3:00p Omkar Muralidharan, Google: "Empirical Bayes with multiple data streams"
3:30p Stefan Wager, Stanford University: "Quasi-oracle estimation of heterogeneous causal effects"
4:00p Closing Remarks