Oregon Master
Naturalist (in progress)
I am an avid learner, researcher, and educator.
I spent 19 years at the Jet
Propulsion Laboratory in Pasadena, CA, as a Principal Researcher in the
Machine Learning and Instrument
Autonomy Group (2003 to 2022). At JPL, I focused on investigating ways
that machine learning can be used to enable scientific discoveries
and increase the autonomy of space missions. It has been a richly rewarding,
exciting position working with stellar colleagues from planetary science,
radio astronomy, cosmology, agriculture, library science, and other fields. In
addition, I had the unusual chance to serve as a
tactical planner and uplink lead for the Opportunity
Mars Exploration Rover (2013 to 2017) and as the
PDS Imaging Node
Technologist (2018 to 2022).
In 2022 I made the decision to retire from JPL and identify additional
areas in which I could have impact. From 2019 to 2023 I
taught courses at Oregon
State University. I am now serving as
a AAAS
Congressional Fellow in Artificial Intelligence for
Senator Mark Kelly in Washington D.C.
I am passionate about keeping machine learning efforts relevant to our
society's needs.
My research projects have included:
- Onboard science for Europa Clipper: Developing and testing methods
to quickly analyze data as it is collected during a flyby of Europa to
assign high downlink priorities to the most scientifically valuable
observations and to enable cross-instrument collaboration
-
Mars Target Encyclopedia: Information extracted from scientific
publications for planetary science
(MTE GitHub)
- V-FASTR: Efficient machine learning to detect transient radio phenomena (e.g., pulsars and Fast Radio Bursts) in real time
- Collaborative machine learning for volcano 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: