The Data Science Economy

Friday, May 8, 2015 - 1:50 pm

In this talk, I will present three distinct aspects of the data science economy:

  1. data, algorithms, systems and humans as the four main drivers of the data science economy
  2. a marketplace of intelligent APIs hosted on the cloud that can be easily consumed to build higher level intelligent applications
  3. data enabled applications on the cloud in traditional industries.

The Data Science Economy - DataEDGE 2015

Director, Algorithms and Data Science Solutions

Vijay K Narayanan leads the Algorithms and Data Science efforts in the Information Management and Machine Learning group in Microsoft, where he works on building and leveraging machine learning platforms, tools and solutions to solve analytic problems in diverse domains. Earlier, he worked as a Principal Scientist at Yahoo! Labs, where he worked on building cloud based machine learning applications in computational advertising, as an Analytic Science Manager in FICO where he worked on launching a product to combat identify theft and application fraud using machine learning, as a  Modeling Researcher at ACI Worldwide, and as a Sloan Digital Sky Survey research fellow in Astrophysics at Princeton University where he co-discovered the ionization boundary and the four farthest quasars in the universe.

He received a Bachelor of Technology degree from IIT, Chennai and a PhD in Astronomy from The Ohio State University. Narayanan has authored or coauthored approximately 55 peer-reviewed papers in astrophysics, 10 papers in machine learning and data mining techniques and applications, and 15 patents (filed or granted). He is deeply interested in the theoretical, applied, and business aspects of large scale data mining and machine learning, and has indiscriminate interests in statistics, information retrieval, extraction, signal processing, information theory, and large scale computing.