Master of Library and Information Science, San Jose State University, in progress
My background is in Computer Science, Planetary Science, and
Geology. I am most interested in problems that lie at the interfaces
between these fields, such as automated methods (artificial
intelligence, machine learning) to investigate science questions using
planetary data (orbital and in situ).
I work at the Jet
Propulsion Laboratory in Pasadena, CA.
I have two roles at JPL:
I have also taught classes in Computer Science at Cal State L.A.
and Oregon State University.
My research projects at JPL have included:
- Efficient machine learning to detect transient radio phenomena (e.g., pulsars) in real time
- Collaborative machine learning for sensor networks
- Automatic landmark identification and change detection in Mars orbital images (dark slope streaks, dust devil tracks, etc.)
- Analyzing the sensitivity of machine learning algorithms to high-radiation environments
- Predicting county-level crop yield from Earth orbital images
- Modeling user preferences for sets, rather than individual items
(like music playlists or rover image downlink sets)
- Modeling flight software with state charts and using automatic code generation to convert them into C/C++ (for implementation) or Promela (for model checking)
- Tracking the north polar ice caps (water and CO2) on Mars
News and upcoming events:
- The New Scientist magazine published an article about our recent paper describing automated methods for detecting plumes from moons and comets:
- I was selected as one of 1058 candidates for
Mars One's second round of astronaut selections (Dec. 30, 2013), which were then whittled down to 705 candidates (May 5, 2014). However, I was not selected for round 3 (100 candidates).
- The video for my controversial ICML 2012 talk is no longer available (lost in a server crash).
However, you can read the original paper:
Machine Learning that Matters (pdf, 6 pages, 234K) and
see the slides from a subsequent invited AAAI talk:
Challenges for Machine Learning Impact on the Real World (1.6M).
- Recently published or posted:
Onboard Machine Learning Classification of Images by a Cubesat in
David R. Thompson, Alphan Altinok, Ben Bornstein, Steve A. Chien,
Joshua Doubleday, John Bellardo, and Kiri L. Wagstaff.
AI Matters, 1(4), 38-40, 2015.
A Framework for Collaborative Review of Candidate Events in High Data Rate Streams: The V-FASTR Experiment as a Case Study.
Andrew F. Hart, Luca Cinquini, Shakeh E. Khudikyan, David R. Thompson, Chris A. Mattmann, Kiri Wagstaff, Joseph Lazio, and Dayton Jones.
Astronomical Journal, 149(1), 2015.
Landmark Classification and Content-Based Search for Mars Orbital Imagery.
Kiri L. Wagstaff, Gary B. Doran, Ravi Kiran, Lukas Mandrake, Norbert Schorghofer, and Alice Stanboli.
2nd Planetary Data Workshop, June 2015.
- Library science papers:
- Recent awards:
- I was promoted to Principal at JPL in January 2015
- 2014 NASA Group Achievement Award (Mars Exploration Rover Science and Operations Team)
- 2014 NASA Group Achievement Award (IPEX/CP-8 CubeSat Flight Team)
- 2012 NASA Exceptional Technology Achievement Medal
- 2012 AAAI Outstanding Program Committee Member Award (one of four people chosen)
- 2012 Young Alumni Par Excellence Award from the University of Utah
- 2008 Lew Allen Award for Excellence in Research for "advancing the performance and application of machine learning methods to onboard Earth science missions and spacecraft engineering."
- Extracurricular activities:
- I volunteer in support of the
Monrovia Public Library and
Kids Building Things.
- I am working on my private pilot's license.
- I served as Editor in Chief of
AI Matters, the SIGAI Newsletter, from April 2014 to June 2015.
- I taught Space Camp to middle school students in South Korea in the summer of 2014.