Cognitive modeling explorations with crowdsourced predictions and opinions

Title: Cognitive modeling explorations with crowdsourced predictions and opinions
Speaker: Michael Lee, Professor of Cognitive Sciences, University of California Irvine
Time: 12:30-1:30
Room: NSH 1507

The analysis of crowdsourced data can be treated a cognitive modeling problem, with the goal of accounting for how any why people produced the behaviors that were observed. We explore this cognitive approach in a series of examples, involving Thurstonian models of ranking, calibration models of probability estimation, and attention and similarity models of category learning. Many of the demonstrations use crowd-sourced data from Some involve "wisdom of the crowd" predictions, while others aim to describe and explain the structure of people's opinions. Throughout the talk, we emphasize the tight interplay between theory and application, highlighting not just when existing cognitive theories and models can help address crowd-sourcing problems, but also when real-world applications demand solutions to new basic research challenges in the cognitive sciences.

Michael Lee is a Professor of Cognitive Sciences at the University of California Irvine. His research focuses on modeling cognitive processes, especially of decision making, and the Bayesian implementation, evaluation, and application of those models. He has published over 150 journal and conference papers, and is the co-author of the graduate textbook "Bayesian cognitive modeling: A practical course". He is a former President of the Society for Mathematical Psychology, a winner of the William K. Estes award of that society, and a winner of the best applied paper from the Cognitive Science Society. Before moving the U.S., he worked as a senior research scientist for the Australian Defence Science and Technology Organization, and has consulted for the Australian and US DoD, as well as various universities and companies, including the crowd-sourcing platform Ranker.

Human-in-the-loop Analytics

Title: Human-in-the-loop Analytics
Speaker: Michael Franklin, Liew Family Chair of Computer Science, University of Chicago
Time: 2:30 -3:30pm
Room: NSH 1507

The “P“ in AMPLab stands for "People" and an important research thrust in the lab was on integrating human processing into analytics pipelines. Starting with the CrowdDB project on human-powered query answering and continuing into the more recent SampleClean and AMPCrowd/Clamshell projects, we have been investigating ways to maximize the benefit that can be obtained through involving people in data collection, data cleaning, and query answering.  In this talk I will present an overview of these projects and discuss some future directions for hybrid cloud/crowd data-intensive applications and systems.

Michael J. Franklin is the Liew Family Chair of Computer Science and Sr. Advisor to the Provost for Computation and Data at the University of Chicago where his research focuses on database systems, data analytics, data management and distributed computing systems.  Franklin previously was the Thomas M. Siebel Professor and chair of the Computer Science Division of the EECS Department at the University of California, Berkeley.   He co-founded and directed Berkeley’s Algorithms, Machines and People Laboratory (AMPLab), which created industry-changing open source Big Data software such as Apache Spark and BDAS, the Berkeley Data Analytics Stack.   At Berkeley he also served as an executive committee member for the Berkeley Institute for Data Science.  He currently serves as a Board Member of the Computing Research Association and on the NSF CISE Advisory Committee.  Franklin is an ACM Fellow and a two-time recipient of the ACM SIGMOD “Test of Time” award. His other honors include the Outstanding Advisor award from Berkeley’s Computer Science Graduate Student Association, and the “Best Gong Show Talk” personally awarded by Andy Pavlo at this year’s CIDR conference.

For more information about Dr. Franklin, visit and

Constructing Visual Metaphors: Using the Design Process to Crowdsource a Creative Task

Title: Constructing Visual Metaphors: Using the Design Process to Crowdsource a Creative Task
Speaker: Lydia Chilton, Stanford University (Columbia University starting in Fall 2017)
Date: Tues, March 7
Time: 12:30-1:30pm
Room: NSH 1507

Visual Metaphors are a communication tool used to draw users' attention in print media, ads, public service announcements and art. They involve blending two symbols together visually to convey a new meaning. This is a creative problem with many solutions, but some solutions have more impact and meaning to readers than others.

I will introduce the problem of visual metaphors, and describe our early stages in crowdsourcing this problem. I will discuss how we had to adapt the design process to apply to microtasks and the lessons we have learned so far about designing media that speaks directly to reader’s low-level perceptual processing.

Lydia Chilton is an assistant professor in the Computer Science Department of Columbia University in the City of New York. Actually, she won't technically start that position until July. She is currently a post-doc working with Maneesh Agrawala at Stanford University at the intersection of graphics, HCI and crowdsourcing. She has been doing crowdsourcing for ten years and is excited to see how the original goals of crowdsourcing are being realized by a large community of talented researchers.