November 1, 2019

306 words 2 mins read

The perfect conference: Using stochastic optimization to bring people together

The perfect conference: Using stochastic optimization to bring people together

The goal of RCSA's Scialog conferences is to foster collaboration between scientists with different specialties and approaches, and, working with Datascope, the company has been doing so in a quantitative way for the last six years. Brian Lange discusses how Datasope and RCSA arrived at the problem, the design choices made in the survey and optimization, and how the results were visualized.

Talk Title The perfect conference: Using stochastic optimization to bring people together
Speakers Brian Lange (Datascope)
Conference Strata + Hadoop World
Conf Tag Big Data Expo
Location San Jose, California
Date March 14-16, 2017
URL Talk Page
Slides Talk Slides
Video

One of the most valuable parts of attending a conference is the opportunity to meet others and build your network—and potentially even find new partners. The explicit goal of the Research Corporation for Scientific Advancement’s (RCSA) Scialog conferences is to foster collaboration between scientists with different specialties and approaches, and, working together with Datascope, the company has been doing so in a quantitative way for the last six years. Datascope designed a survey to run before and after each conference to determine the level of familiarity between each attendee, as well as the topics they were most interested in and the other attendees they’d like to discuss those topics with. After the survey, Datascope implemented and continues to adapt an optimization tool that takes the survey data along with other metadata to choose optimal large topic discussion groups and small breakout groups for the conference. Afterward, a second survey is taken to see the effects on the network of attendees. Brian Lange discusses how Datasope and RCSA arrived at the problem, the design choices made in the survey and optimization, and how the results were visualized. Along the way, Brian covers lessons learned and other problems where optimization may prove to be fruitful.

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