Private pilot's license (single-engine land)
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 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:
A Machine Learning Classifier for Fast Radio Burst Detection at the VLBA
Kiri L. Wagstaff, Benyang Tang, David R. Thompson, Shakeh Khudikyan, Jane Wyngaard, Adam T. Deller, Divya Palaniswamy, Steven J. Tingay, and Randall B. Wayth.
Publications of the Astronomical Society of the Pacific, 128:966(084503), 2016.
- We describe the classifier used to filter VLBA fast radio burst detections
to reduce the human effort needed to review and classify them manually. We also describe
the web interface used for ongoing reviewing, which you can see for yourself at
the V-FASTR Data Portal. You can also view
the latest classifier results
Creating a Mars Target Encyclopedia by Extracting Information from the Planetary Science Literature.
Kiri L. Wagstaff, Ellen Riloff, Nina L. Lanza, Chris A. Mattmann, and Paul M. Ramirez, February 2016.
- Library science papers:
- Recent awards:
- I was elected to the
Council for 2015-2018
- 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: