#  Joseph Jay Williams, Harvard: Perpetually enhancing human learning through collaborative, dynamic, personalized experimentation 

 



####  calendar\_today Date and Time 

 **February 13, 2017** 

 11:30AM - 01:00PM EST 

####  pin\_drop Location 

 **Maxwell Dworkin 119**  



 

 



 

 **CRCS Lunch Seminar**

 Date: Monday, February 13, 2017  
Time: 11:30am – 1:00pm  
Place: Maxwell Dworkin 119

 Speaker: Joseph Jay Williams, Harvard Title: Perpetually enhancing human learning through collaborative, dynamic, personalized experimentation

 Abstract: There is a proliferation of websites and mobile apps for helping people learn new concepts (e.g. online courses), and learn how to change health habits and behavior (e.g. websites for reducing depression, apps for quitting smoking). How can we use data from real-world users to rapidly enhance and personalize these technologies? I show how we can build self-improving systems by reimagining randomized A/B experimentation as an engine for collaboration, dynamic enhancement, and personalization. I present a novel system that enhanced learning from math problems, through crowdsourcing explanations and automatically experimenting to discover the best. My second application boosted responses to an email campaign, by experimentally discovering how to personalize motivational messages to a user's activity level. These self-improving systems use experiments as a bridge between designers, social-behavioral scientists and researchers in statistical machine learning.

 ![Joseph Jay Williams](/sites/g/files/omnuum6171/files/crcs/files/01-1_0_02.jpg)

 

Bio: Joseph Jay Williams is a Research Fellow at Harvard's Office of the Vice Provost for Advances in Learning, and a member of the Intelligent Interactive Systems Group in Computer Science. He completed a postdoc at Stanford University in the Graduate School of Education in Summer 2014, working with the Office of the Vice Provost for Online Learning and the Open Learning Initiative. He received his PhD from UC Berkeley in Computational Cognitive Science, where he applied Bayesian statistics and machine learning to model how people learn and reason. He received his B.Sc. from University of Toronto in Cognitive Science, Artificial Intelligence and Mathematics, and is originally from Trinidad and Tobago. More information about his research and papers is at [www.josephjaywilliams.com](https://urldefense.proofpoint.com/v2/url?u=http-3A__www.josephjaywilliams.com&d=CwMFaQ&c=WO-RGvefibhHBZq3fL85hQ&r=7kltH_yR7omWMxRO_QAQvc5Ckcjw9BitZbWiSDJJq2M&m=DDEwdQMxIzy-3rE_WL54IiEpnaxNBg3fGN80yj8b32A&s=825U6lkhRkqoBPFQyXVNgB8Luj1uIqytwna_7woDYMQ&e=).

 



 

 



 

 See also:- [ CRCS Lunch Seminar ](/events/crcs-lunch-seminar)
 
 

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