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Workshop and Webcast on Machine-Augmented Analysis of Multi-Source Data

 

August 9-10, 2017


Keck Center
500 5th St., NW

Washington, D.C. 20001

 

On August 9-10, 2017, the ICSB organized a two-day workshop on the capabilities and applications of artificial intelligence and machine learning for the intelligence community.  This event, which was sponsored by ODNI, brought together world-class experts and technologists to discuss how machine learning algorithms can augment human analysis to help draw conclusions from large volumes of multi-source data.  Speakers also considered the technical implications as well as cultural, regulatory, policy, and legal issues.

 

Download the Agenda

 

Watch the Recorded Webcast

 

DAY 1

 

Opening Remarks
Dr. David M. Isaacson, ODNI
Dr. Rama Chellappa, UMCP, Planning Committee Chair
Dr. George Coyle, RSO, AFSB/ICSB
Video

 

Progress in Machine Learning
Dr. Tom Dietterich, Oregon State University
Video

 

Industry Perspective
Dr. Josyula R Rao, Watson IBM Fellow
Video

 

Operational Perspective – Project MAVEN
Dr. Travis W Axtell, OSD OUSD (I)
Video

 

Learning from Overhead Imagery
Dr. Joe Mundy, Vision Systems, Inc.
Video

 

Deep Learning for Learning from Images and Videos: Is It Real?
Dr. Rama Chellappa, UMCP
Video

 

Learning about Human Activities from Images and Videos
Dr. Anthony Hoogs, Kitware, Inc.
Video

 

Machine Learning from Text: Applications
Dr. Kathy McKeown, Columbia University
Video

 

Deep Learning for NLP
Dr. Dragomir Radev, Yale University
Video

 

Machine Learning from Conversational Speech
Dr. Amanda Stent, Bloomberg
Video

 

Situational Awareness from Multiple Unstructured Sources
Dr. Boyan Onyshkevych, DARPA
Video

 

Closing Discussion
Video
 

 

DAY 2

 

Opening Remarks
Dr. David Honey, Director of Science & Technology, ODNI
Video

 

Harnessing Machine Learning for Global Discovery at Scale
Dr. Mikel Rodriguez, MITRE
Video

 

Large Scale Multi-Modal Deep Learning
Dr. Rob Fergus, NYU
Video

 

What can we learn from Social Media posts?
Dr. Benjamin Van Durme, Johns Hopkins University
 

 

Sensemaking Systems and Models
Dr. Peter Pirolli, Institute for Human and Machine Cognition
Video

 

Crowd Sourcing for Natural Language Processing
Dr. Chris Callison-Burch, University of Pennsylvania
Video

 

Toward Socio-Cultural Machine Learning
Dr. Mark Riedl, George Institute of Technology
Video

 

Panel on Evaluation of machine-generated products
Dr. Anthony Hoogs, Kitware
Dr. Jason Duncan, MITRE
Mr. Jonathan Fiscus, NIST
Dr. Rob Fergus, NYU
Video


Machine Learning for Energy Applications
Dr. Devanand Shenoy, DOE
Video

 

Using Metrology to Improve Access to 'Unstructured' Data
Dr. Ellen Voorhees, NIST
Video

 

Challenge Problems for Multi-Source Insights
Dr. Travis W Axtell, OSD OUSD (I)
Video

 

An Overview of NSF Research in Data Analytics
Mr. James Donlon, NSF
Video

 

Closing Remarks
Video