Date: Monday, Nov 16, 2020
Time: 3:00pm-4:00pm Eastern Time (ET)
Join virtually: https://primetime.bluejeans.com/a2m/live-event/xvrbevrh
LinkedIn Data Science - Creating Global Economic Opportunities
At LinkedIn, data plays an essential role in achieving our vision of creating economic opportunity for every member of the global workforce. In this talk, Ya Xu will share perspectives from her experience and will highlight a few interesting problems her team tackles, such as measuring network effects, addressing cannibalization bias on advertising using budget split, forecasting, data privacy, responsible design, and fairness in our products and ML models.
Ya Xu, VP of Engineering and Head of Data Science Team at LinkedIn
Ya joined LinkedIn in 2013 and has since truly helped make LinkedIn a Data First company. She leads an exceptional team of talented data scientists whose work covers metrics, insights, inference and algorithms and they tackle data science challenges across product, sales, marketing, economics, infrastructure, and operations. This centralized group has 300+ data scientists distributed across US (Sunnyvale, Mountain View, San Francisco, New York), India, China, Singapore and Dublin, Ireland. Ya is passionate about bridging science and engineering to create impactful results. She and her team try to keep LinkedIn on the cutting edge while ensuring that its A.I. systems avoid providing biased results while maintaining user privacy. They help the company take active responsibility over the data they collect to ensure fairness and protect privacy.
In addition to her work at LinkedIn, Ya’s contributions outside of her day job, such as the bookshe co-authored on Experimentation and her Stanford commencement speech, are meaningful to the entire industry as well as future Data Scientists. Before LinkedIn, she worked at Microsoft and received a PhD in Statistics from Stanford University.
Ya Xu’s LinkedIn Profile: https://www.linkedin.com/in/ya-xu/
Associate Professor, CSE, College of Computing
Associate Director, MS Analytics
Director of Industry Relations, Institute for Data Engineering and Science (IDEaS)
Associate Director of Corporate Relations, Center for Machine Learning (ML@GT)
2018-2021 Provost Teaching and Learning Fellow