Please register for eLUCID8

Wisconsin Institute for Discovery, Madison, WI
August 14th – August 15th, 2017

eLUCID8 will feature interactive presentations, talks, and roundtables intended to discuss LUCID related projects and potential collaborations with government agencies, non-profits and industry groups.


Keynote Speakers


Monday, August 14th

Bob Mankoff
Former Cartoon Editor of The New Yorker,
Present Cartoon and Humor Editor of Esquire

“Crowdsourcing Humor”

Humor is traditionally at the hands of its author. What happens when the audience picks the punchline?

Each week, on the last page of the magazine, The New Yorker provides a cartoon in need of a caption. Readers submit captions, the magazine chooses three finalists, readers vote for their favorites. It’s humor—crowdsourced—and with more than 3 million submissions provided by 600,000 participants, it provides tremendous insight as to what makes us laugh.

In a fast-paced and funny talk, Bob Mankoff, The New Yorker‘s cartoon editor, will analyze the lessons we learn from crowdsourced humor. Along the way, he’ll explore how cartoons work (and sometimes don’t); how he makes decisions about what cartoons to include; and what crowds can tell us about a good joke.


mozer-largeTuesday, August 15th
Michael C. Mozer
Department of Computer Science 
University of Colorado
“Predicting and boosting memory retention”Cognitive psychology has long aimed to understand mechanisms of human memory, with the hope that such an understanding will yield practical techniques that support long-term retention of newly learned material.

Mozer is interested both in developing machine learning algorithms that leverage insights from human cognition, and in developing software tools to optimize human performance using machine learning methods.

He argues that despite the power of big data, psychological theory provides essential constraints on models. In a year-long intervention in middle-school foreign language courses, he demonstrates the value of adaptive review that leverages data from a population of learners to personalize recommendations based on an individual’s study history and past performance. Mozer will also present ongoing work that leverages theories of human memory to improve recurrent neural nets that predict event sequences.

This work is a joint collaboration with Robert Lindsey and Karl Ridgeway at the University of Colorado.
Michael Mozer received a Ph.D. in Cognitive Science at the University of California at San Diego in 1987.  Following a postdoctoral fellowship with Geoffrey Hinton at the University of Toronto, he joined the faculty at the University of Colorado at Boulder and is presently an Professor in the Department of Computer Science and the Institute of Cognitive Science.  He is secretary of the Neural Information Processing Systems Foundation and has served as chair of the Cognitive Science Society.



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