How to Win a Hackaton by Daniel Lee Visit https://rstats.ai/nyr/ to learn more. Bio: Daniel Lee is a computational Bayesian statistician who helped create and develop Stan, the open-source statistical modeling language. He has 20 years of experience in numeric computation and software; over 10 years of experience creating and working with Stan; and has spent the last 5 years working on pharma-related models including joint models for estimating oncology treatment efficacy and PK/PD models. Past projects have covered estimating vote share for state and national elections; clinical trials for rare diseases and non-small-cell lung cancer; satellite control software for television and government; retail price sensitivity; data fusion for U.S. Navy applications; sabermetrics for an MLB team; and assessing “clutch” moments in NFL footage. Daniel has led workshops and given talks in applied statistics and Stan at Columbia University, MIT, Penn State, UC Irvine, UCLA, University of Washington, Vanderbilt University, Amazon, Climate Corp, Swiss Statistical Society, IBM AI Systems Day, R/Pharma, StanCon, PAGANZ, ISBA, PROBPROG, and NeurIPS. He holds a B.S. in Mathematics with Computer Science from MIT, and a Master of Advanced Studies in Statistics from Cambridge University. Twitter: https://twitter.com/djsyclik Presented at the 2022 New York R Conference (June 9, 2022)