Institute of Information Science, Academia Sinica

In this talk, we will answer questions like what data mining (DM) is, why interested in DM, and how to use DM in the era of big data and cloud computing.  In particular, we will analyze DM applications in the framework of common sense business strategy – find more, win more and keep more.  Then we will illustrate some examples of data mining applications in the areas of marketing, risk, pricing and web analytics.  In addition, we will emphasize the role of hybrid systems in leveraging ensemble of traditional academic disciplines such as computer science, statistics, management science and engineering to develop an integrated solution to real-world business problems.  Finally, the talk will be concluded by outlining the core competency of a data miner in the age of cloud-enabled knowledge discovery – the ability to manage data, make sense of data, build predictive models, prototype analytic engines, and make recommendations and business decisions.

Yu-To Chen (陳毓鐸) is a Sr. Quantitative Analyst at Google and is currently working on Android in Mountain View, CA.  He is working on projects such as Android market metrics and purchase behavior modeling, Android device lifetime value and optimization of Android device energy consumption.  His areas of expertise are analytics, fuzzy logic, data mining and predictive modeling.  Prior to Google, he worked at PayPal, GE Global Research and a number of startups in between - covering risk management, web analytics, pricing and supply chain management.  Once he was a visiting assistant professor at University of Iowa (1993) and an adjunct professor at Union College, NY (2000.)  He has been awarded 26 US patents and published over a dozen of journal/conference papers.  He earned his BS in Mechanical Engineering from National Central University in Taiwan (1985) and PhD in Industrial Engineering with a minor in Computer Science from Penn State University in 1993.