Optimizing for User Experience with Data Science and Machine Learning
Understanding users and optimizing for user experience are critical parts of building successful apps and services. While there had been a tremendous amount of past work studying user and social interactions, in practice, it wasn’t until quite recently that researchers are able to study these interaction mechanisms at scale easily. In this talk, I will illustrate data-driven approaches to understand what are happy engaged users, and present case studies of how we utilize novel machine learning techniques to optimize for long-term user engagements in practice.
Ed H. Chi is a Research Scientist at Google, leading a team focused on recommendation systems, machine learning, and social interaction research. He has launched significant improvements of recommenders for YouTube, Google Play Store and Google+. With over 35 patents and over 100 research articles, he is known for research on Web and online social systems, and the effects of social signals on user behavior. Prior to Google, he was the Area Manager and a Principal Scientist at Palo Alto Research Center's Augmented Social Cognition Group, where he led the group in understanding how social systems help groups of people to remember, think and reason. Ed completed his three degrees (B.S., M.S., and Ph.D.) in 6.5 years from University of Minnesota, and has been doing research on software systems since 1993. He has been featured and quoted in the press, including the Economist, Time Magazine, LA Times, and the Associated Press, and has won awards for both teaching and research. He has a In his spare time, Ed is an avid photographer and snowboarder.