Friday, October 20, 2017
11 AM - 12 PM
Data science has been playing a vital role in the IT industry nowadays. At Snap, we use data to understand how our users are using our products, and gain insights about our users and innovations. Because of the dynamics, heterogeneity and the tremendous volume of real user data, there are many new challenges for the data science research at Snap. In this talk, I will share a few examples on data science effort at Snap, with emphasis on two lines of research. The first is on the methodology, as it is critical to have systematic and scalable approaches to generate trustworthy and reproducible results in data science. The second is on the insights about our user behaviors and user experience in using Snapchat, a social app with unique characteristics - playfulness, ephemerality and creativity. From these examples, we will see how data science applications in practice differ from theories, and how we tackle real-world data science challenges at Snap.
Dr. Xiaolin Shi is currently a senior research scientist leading the Data Science effort at Snap Research. She has over ten years of academic and industrial experience on data science, focusing on online experimentation and metrics, computational social science, social network analysis and data mining. Dr. Shi received her Ph.D. from the University of Michigan. Prior to Snap Inc., she was at Stanford University, Microsoft, and Yahoo! Research. Dr. Shi was the recipient of Microsoft Research Technology Transfer Award (2013) and ACM Douglas Engelbart Best Paper Award (2008).
Dr. Jiliang Tang