Yue Ning leads a group of engineers and machine learning scientists at Qualtrics. The group focuses on the Text iQ product, which helps Qualtrics clients discover actionable insights from unstructured text feedbacks of their customers/employees. The team covers the product end-to-end, from neural network models, search engine and data pipelines, to databases, web services and UIs.
Prior to Qualtrics, Yue was a software engineer with Twitter, working on big data pipelines on Twitter Ads platform. He holds a master's degree in Computer Science from the University of Pennsylvania and bachelor's degree in Physics from Peking University.
AI and machine learning are driving a revolution in text analytics that could be a game-changer for the way people interact with brands and employers. In this session, we will explore the latest developments on topic detection and sentiment analysis at Qualtrics and how we are using them to develop advanced text analytics.
The talk is open to audience of all levels. We will briefly introduce word embedding first, which is the basic building block for many of the recent neural network models. And then for topic detection and sentiment analysis, we will discuss in high level about some of the popular neural network based models targeting these two tasks, and the learnings from productizing these research models for real-life problems.