Kris Hammond

Professor of Electrical Engineering and Computer Science

Prior to joining the faculty at Northwestern, Kris founded the University of Chicago’s Artificial Intelligence Laboratory. His research has been primarily focused on artificial intelligence, machine-generated content and context-driven information systems. Kris currently sits on a United Nations policy committee run by the United Nations Institute for Disarmament Research (UNIDIR). He received his PhD from Yale.


Projects Kris Hammond has worked on.

Automated Fact Checking

There's more information than ever, and often, the audience is left wondering whether they should trust what they hear. What systems could we build that help people simply answer the question, "is that true?"

Conversational Interface for News

Using a combination of raw search and the collections of regular expressions, build a system that would allow a user to ask questions about what is happening in the news and get back answers and pointers to sources. In the vein of Watson, multiple approaches to matching against text for different types of questions would be used to find answers.  This is envisioned as text (rather than voice) driven system.

Fact FlowEfficiency for editing. Credibility and trust for publishing

Editorial fact-checking is a mess at best and readers don't see the benefits. Typically they doubt it happens or don't appreciate the work it takes to make it happen. On the editing side, almost everyone who does it uses an antiquated process derived from print production habits even though most writers and editors are drafting in Google Docs. This can be better. Let's make it better for both editorial and readers!

Story for YouWriting stories for people who don’t want to read them

Studies have shown that people on opposing sides of political issues use fundamentally different language to discuss their views. One of the effects of this is that people living in News Filter Bubbles can immediately notice and then discard stories that use the terms associated with their opposition.

Talking to Data

The aim of this project is to provide users with a conversational interface to data sets that allow them to first describe what the data is about, where the various elements that they can ask about can be found, and then ask questions about the data.

Watch Me WorkSearch driven by your own writing

As we work, we often need information to support our thinking. This often requires turning away from the work, pulling up an engine and then typing in a query. If you are writing, however, the queries that we need are already embedded in the text of the document we are authoring.