Put AI to Work
April 15-18, 2019
New York, NY
Bruno Goncalves

Bruno Goncalves
Chief Data Scientist, Data For Science

Website | @bgoncalves

Bruno Gonçalves is a chief data scientist at Data For Science, working at the intersection of data science and finance. Previously, he was a data science fellow at NYU’s Center for Data Science while on leave from a tenured faculty position at Aix-Marseille Université. Since completing his PhD in the physics of complex systems in 2008, he’s been pursuing the use of data science and machine learning to study human behavior. Using large datasets from Twitter, Wikipedia, web access logs, and Yahoo! Meme, he studied how we can observe both large scale and individual human behavior in an obtrusive and widespread manner. The main applications have been to the study of computational linguistics, information diffusion, behavioral change and epidemic spreading. In 2015, he was awarded the Complex Systems Society’s 2015 Junior Scientific Award for “outstanding contributions in complex systems science” and in 2018 was named a science fellow of the Institute for Scientific Interchange in Turin, Italy.

Sessions

1:45pm–5:15pm Tuesday, April 16, 2019
Recurrent neural networks for time series analysis
Implementing AI
 Location: Trianon Ballroom
Secondary topics:  Models and Methods, Temporal data and time-series
Bruno Goncalves (Data For Science)
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Time series are everywhere around us. Understanding them requires taking into account the sequence of values seen in previous steps and even long-term temporal correlations. Join Bruno Gonçalves to learn how to use recurrent neural networks to model and forecast time series and discover the advantages and disadvantages of recurrent neural networks with respect to more traditional approaches. Read more.