Watson Innovation Course – Invited Lecture by Ken Barker, IBM Watson US

This week, the Watson Innovation course, a collaboration between the Vrije Universiteit, University of Amsterdam and IBM Netherlands, Centre for Advanced Studies (CAS) starts. The course offers a unique opportunity to learn about IBM Watson, cognitive computing and the meaning of such artificial intelligence systems in a real world and big data context. Students from Computer Science and Economics faculties join their complimentary efforts and creativity in cross-disciplinary teams to explore the business and innovation potential of such technologies.


This year, on 13th of November, Ken Barker from IBM Watson US will give an invited lecture. Here is an abstract of his invited lecture entitled “Question Answering Post-Watson”:

There is a long, rich history of Natural Language Processing and Question Answering research at IBM. This research achieved a significant milestone when the autonomous Question Answering system called “Watson” competed head-to-head with human trivia experts on the American television show, “Jeopardy!” Since that event, both Watson and QA/NLP research have barreled forward at IBM, though not always in the same direction.

In this talk, I will give a brief, biased history of Question Answering research and Watson at IBM, before and after the Jeopardy! challenge. But most of the talk will be a more technical presentation of our path of QA research “post-Watson”. The discussion will be in three parts: 1) Continuing research on traditional Question Answering technology beyond Jeopardy! 2) Work on transferring QA technology to Medicine and Healthcare; and 3) Recent research into exploratory, collaborative Question Answering against scientific literature.


Ken Barker Bio:

Ken Barker heads the Natural Language Analytics Department in the Learning Health Systems Organization at IBM Research AI. His current research examines the weaknesses of existing information gathering tools and applies Natural Language Processing to collaborative, exploratory question answering against scientific literature. Before joining IBM in 2011, he was a Research Faculty Member at the University of Texas at Austin, serving as Investigator on DARPA’s Rapid Knowledge Formation and Machine Reading Projects, as well as on Vulcan’s Digital Aristotle Project to build intelligent scientific textbooks. He was also an Assistant Professor of Computer Science at the University of Ottawa. His research there focused on Natural Language Semantics and Semi-Automatic Interpretation of Text.