NASA Insignia
NASA Goddard Workshop on Artificial Intelligence

Agenda

Tue, Nov 27 :: Wed, Nov 28 :: Thu, Nov 29


Day 1 Tuesday, November 27, 2018
7:30 am - 9:00 am ARRIVAL
Goddard Badging for non-NASA Attendees at the Visiting Center
Workshop Check-in for All Outside of Building 8 Auditorium
9:00 am - 10:30 am OPENING CEREMONY
Jacqueline Le Moigne, Chair - General Introduction to the Workshop
Christopher Scolese, Director, NASA Goddard - Welcome and Speaker Introduction

KEYNOTE: David Gunning, DARPA
DARPA's Explainable Artificial Intelligence (XAI) Program
10:30 am - 10:45 am BREAK
10:45 am - 12:25 pm PANEL: AI at NASA
(Session Chair: Jacqueline Le Moigne)
Dan Crichton/JPL - Data Science at JPL: Integrating Data Analytics into the Full Data Lifecycle
James Ecker/LaRC - Deep Learning for Neuro-visualization and Continuous Control in Autonomous Systems
Nikunj Oza/ARC - Artificial Intelligence in the NASA Ames Intelligent Systems Division
Brian Roberts/GSFC - AI & Computer Vision for Satellite Servicing at NASA Goddard
Brian Thomas/HQ - Elements of an AI/ML Architecture for NASA
12:25 pm - 1:30 pm LUNCH
1:30 pm - 2:30 pm KEYNOTE: Kirk Borne, Booz Allen (Introduction: Barbara Thompson)
AI at NASA: From Data to Insights to Actionable Intelligence
2:30 pm - 4:40 pm SESSION 1
Invited Talk: Bart Paulhamus, APL (Introduction: Ron Zellar)
Intelligent Systems Research at JHU/APL

SHORT TALKS: (Session Chairs: Ioana Rus and Dave Batchelor)
3:00 - D. Sekora, AI's Missing Real-World Connection, and Its Essential and Multifaceted Roles
3:10 - J. Nanda, Explainable Machine Learning for Aviation Safety Assurance
3:20 - A. Deane, A Cognitive Processing Enhanced Smart Interface Framework For Situational Awareness
3:40 - W.R. Huang, Data Poisoning Attacks Can Compromise Machine Learning Systems
Break: 3:50 pm to 4:00 pm
(Session Chairs: Alinda Mashiku and Manohar Deshpande)
4:00 - B. Dean, Deep Multi-Layer Networks for Optical Wavefront Sensing and Control
4:10 - S.R. Alimo, Machine Learning Approaches for General Satellite Maneuvers
4:20 - A. Mashiku, Supervised-machine Learning for Intelligent Collision Avoidance Decision-making and Sensor Tasking
4:30 - J. Krishnan, SEVA-OIE: Open Information Extractor for the Systems Engineering Virtual Assistant (SEVA)
4:40 pm - 5:45 pm Introduction Breakout Sessions: Burcu Kosar and Jacqueline Le Moigne
BREAKOUT SESSION: AI for NASA Science Applications

Day 2 Wednesday, November 28, 2018
8:30 am - 9:40 am Introduction: Christyl Johnson, NASA Goddard
KEYNOTE: William Buzz Roberts, NGA
Real World Artificial Intelligence, Automation and Augmentation - Geospatial Intelligence Successes, Challenges and Way Forward
9:40 am - 11:00 am PANEL: AI in Academia
(Session Chair: Grey Nearing)
Cynthia Matuszek/UMBC - Learning Grounded Language For and From Interaction
Ray Ptucha/RIT - Deep Learning on Graph Data
Dinesh Manocha/UMD - Autonomy and AI Research at UMD
11:00 am - 11:30 am BREAK
11:15 am - 12:15 pm KEYNOTE: Henry Kautz, NSF (Introduction: Jacqueline Le Moigne)
Artificial Intelligence: Everything Old is New Again
12:15 pm - 12:45 pm BREAK - Grab Lunch
12:45 pm - 1:15 pm Brown Bag Lunch with Lika Guhathakurta, NASA ARC (Introduction: Michael Kirk)
The Frontier Development Lab (FDL): Applied Artificial Intelligence for Science and Exploration
1:15 pm - 1:30 pm BREAK
1:30 pm - 2:40 pm SESSION 2
Invited Talk: Tom Goldstein, UMD (Introduction: Nargess Memarsdeghi)
Multi-Scale Neural Networks for Image Processing

SHORT TALKS: (Session Chairs: Barbara Thompson and Ryan McGranaghan)
2:00 - Z.liu, Improving NASA Earth Science Data and Information Access Through Natural Language Processing Based Data Analysis and Visualization
2:10 - M. Reiss, Improvements On Coronal Hole Detection Using Supervised Classification
2:20 - K. Tran, X-Net: Bimodal Feature Representation Learning in Satellite Imagery
2:30 - S. Sabogal, Hybrid Semantic Image Segmentation using Deep Learning for On-board Space Processing
2:40 pm - 2:50 pm BREAK
2:50 pm - 4:20 pm SESSION 3
Invited Talk: Victor Pankratius, MIT (Introduction: Sujay Kumar)
Towards Deriving Theories from Data: Frontiers for Model Inference in Astro-&Geophysics

SHORT TALKS: (Session Chairs: Craig Pelissier and Troy Ames)
3:20 - C. Keller, Atmospheric Chemistry Modeling using Machine Learning
3:30 - J. Kouatchou, Implementation of Gaussian Processes in an Hydrological Model
3:40 - D. Josyula, Autonomous Seasonality Adaptation
3:50 - N. Thomas, Machine Learning in Global Scale Classification of Mangrove Forests From remotely sensed imagery
4:00 - T. Maxwell, Machine Learning in the Earth Data Analytic Services (EDAS) Framework
4:10 - M. Halem, RNN/LSTM Ensemble Data Assimilation for the Lorenz Chaotic Models
4:20 pm - 5:10 pm BREAKOUT SESSION: AI for NASA Engineering Applications
5:10pm - 5:30 pm BREAK (and Poster Setup)
5:30 pm - 6:30 pm POSTER SESSION

Day 3 Thursday, November 29, 2018
8:30 am - 9:40 am Introduction: Peter Hughes, NASA Goddard
KEYNOTE: Vikash Mansinghka, MIT
Probabilistic Programming and Artificial Intelligence
9:40 am - 11:25 am PANEL: AI in Industry (Session Chair: Ron Zellar)
John Hebeler/Lockheed Martin - Determining Normal (and Abnormal) using Deep Learning
Graham Katz/IBM - Watson Intelligent Advisors: Discovery and Conversational Technology for Now and the Future
Jon Neff/Aerospace - Overview of Aerospace Corporation AI Initiatives
Susie Adams/Microsoft - Democratizing AI - Amplifying Human Ingenuity With Intelligent Technology
Larry Brown/NVIDIA - GPU Accelerated High Performance Data Analytics for Federal Applications
11:25 am - 11:40 am BREAK
11:40 am - 12:30 pm SESSION 4
BREAKOUT SESSION: AI for Intelligent Mission Autonomy
12:30 pm - 1:30 pm LUNCH
1:30 pm - 3:10 pm SESSION 5 Invited Talk: John Calhoun, Amazon AWS (Introduction: Craig Pelissier)
Improving Time to Science Using AWS Machine Learning

SHORT TALKS: (Session Chairs: Nargess Memarsadeghi and Jorge Pinzon)
2:00 - H. Amiri, Spaced Repetition for Training Artificial Neural Networks
2:10 - T. Yuan, Application of a Deep U-Net to Automatic Detection of Ship-Tracks Multispectral Images from both Polar-Orbiting and Geostationary Satellites
2:20 - R. McGranaghan, Ushering in a New Frontier in Geospace Through Data Science
2:30 - R. Attié, Tracking Optical Flows for Better Data Mining on Solar Images
2:40 - D. Hall, Deep Learning Applied to Satellite Data Processing
2:50 - S. Sharma, Data-driven Modeling, Prediction and Predictability: The Complex Systems Framework
3:00 - A. Annex, Automated Stratigraphic Mapping using Convolution Neural Networks
3:10 pm - 3:30 pm GENERAL DISCUSSION - CONCLUSIONS and ADJOURN
4:00 pm - 5:00 pm SPECIAL TUTORIAL (Organizer: Craig Pelissier)
Thursday, November 29
Python Anaconda Machine Learning Tutorial