Joseph Jay Williams

Joseph Jay Williams

First Name: 
Joseph
Last Name: 
Jay Williams
Title: 
Assistant Professor
Biography : 

My Intelligent Adaptive Interventions lab spans Bayesian & Frequentist statistics, applied machine learning, human-computer interaction, psychology, education and health. Our applied statistics research focuses on designing/modifying algorithms and tests/analyses for Adaptive Experimentation. In an Adaptive Experiment (e.g. randomizing people 50/50 to two arms, like an old vs new version of a website), an algorithm automatically analyses data (e.g. which website get more people to click on paper links) to adapt the probability of assignment (e.g. 50/50 to 70/30 to 90/10). We are investigating "Statistically Considerate" Multi-Armed Bandit algorithms, which trade off giving participants better arms/interventions (e.g. websites) with enabling scientifically and statistically rigorous inferences. We are also investigating which statistical tests are appropriate for analyzing data from Adaptive Experiments. Students can read more.

Personal Website: 
http://www.josephjaywilliams.com/

People Type:

Areas of Interest: 
  • Technology-Based Interventions
  • Education
  • Health
  • Algorithms and Tests for Adaptive Experiments
  • (Bayesian) Multi-Armed Bandits
Cross-Appointments: 
Computer Science