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.
Brian Lange is a partner and data scientist at Datascope, where he leads design process exercises and works on algorithms, web interfaces, and visualizations. Brian has contributed to projects for P&G, Thomson Reuters, Motorola, and other well-known companies, and his work has been featured on Nathan Yau’s FlowingData. While he’s not nerding out about typography and machine-learning techniques, Brian enjoys science and comedy podcasts, brewing beer, and listening to weird music.
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