Data Science at Scale: from Theory to Practice
主讲人：Dr. Xiaolin Shi，the University of Michigan
主持人：陈熹 教授，开云官方端网站登录入口
时间：2018年12月18日（周二）下午15:00-16:30
地点：浙江大学紫金港校区行政楼1417会议室
摘要：
Nowadays data science has been playing a vital role in the IT industry, as it has been used to inform the actual business decisions at many IT companies. At Snap, we use data to understand and gain insights on how our users are using our products and make day-to-day business decisions accordingly. Because of the dynamics, heterogeneity and tremendous volume of the real user data, there are many new challenges for data science research at the industrial scale. In this talk, I will share a few examples of the data science effort at Snap, with emphasis on two lines of research. The first line is on the scientific insights about our user behaviors and user experience in using Snapchat for business decisions, and the second line is on the rigorous methodologies for systematic and scalable platforms to generate trustworthy and reproducible results and scale up the data-driven decision-making process. From these examples, we will see how data science applications in practices differ from theories, and how we tackle real-world data science challenges at scale.
主讲人简介：
Dr. Xiaolin Shi is currently the Head of Data Science at Snap Inc, where she leads a team of scientists with expertise in data mining, machine learning, statistics, and economics. She has over ten years of academic and industrial experience in data science and big data, focusing on online experimentation and metrics, data mining, computational social science, and social network analysis. 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).
欢迎广大师生前来参加！
