Kiri L. Wagstaff

Time 2020-07-20 22:04:17

Web Name: Kiri L. Wagstaff

WebSite: http://www.wkiri.com

ID:29932

Keywords:

Kiri,Wagstaff,

Description:

Ph.D. in Computer Science, Cornell University, 2002 Intelligent Clustering with Instance-Level ConstraintsM.S. in Geological Sciences, University of Southern California, 2008Biogenicity Analysis of Stromatolite StructuresMaster of Library and Information Science, San Jose State University, 2017 Automated Classification to Improve the Efficiency of Weeding Library CollectionsPrivate pilot's license (airplane single-engine land), 2016My background is in Computer Science, Planetary Science, andGeology. I am most interested in problems that lie at the interfacesbetween these fields, such as automated methods (artificialintelligence, machine learning) to investigate science questions usingplanetary data (orbital and in situ).I work at the JetPropulsion Laboratory in Pasadena, CA, as a researcher in the Machine Learning and InstrumentAutonomy Group, investigating ways that machine learning can beused to increase the autonomy of space missions. From 2013 to 2017, I also served as a tactical planner and uplink lead for theMars Exploration Rover Opportunity. Since 2018, I have also served as the PDS Imaging Node Technologist. I am also an Associate Research Professor at Oregon State University, where I have the pleasure of teaching classes in Computer Science and doing research on competency-aware machine learning. My research projects at JPL have included:Onboard science for Europa Clipper: Developing and testing methods to quickly analyze data as it is collected during a flyby of Europa toassign high downlink priorities to the most scientifically valuable observations and to enable cross-instrument collaborationMars Target Encyclopedia: Information extraction from scientific publications for planetary scienceV-FASTR: Efficient machine learning to detect transient radio phenomena (e.g., pulsars and Fast Radio Bursts) in real timeCollaborative machine learning for sensor networksAutomatic 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 environmentsPredicting county-level crop yield from Earth orbital imagesModeling 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 MarsNews 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) andsee the slides from a subsequent invited AAAI talk:Challenges for Machine Learning Impact on the Real World (1.6M).Recently published or posted: Visualizing Image Content to Explain Novel Image Discovery (free view-only access to full text). Jake H. Lee and Kiri L. Wagstaff. Data Mining and Knowledge Discovery, 2020, DOI 10.1007/s10618-020-00700-0. We combine novelty detection with CNN image features to achieve rapid discovery with interpretable explanations of novel image content. We also report on a user study of explanation utility. Visit the paper website for code, data, etc. Comparison of Novelty Detection Methods for Multispectral Images in Rover-based Planetary Exploration Missions. Hannah R. Kerner, Kiri L. Wagstaff, Brian D. Bue, Danika F. Wellington, Samantha Jacob, Paul Horton, James F. Bell III, Chiman Kwan, and Heni Ben Amor. Data Mining and Knowledge Discovery, 2020, DOI 10.1007/s10618-020-00697-6. We compare multiple novelty detection methods on multispectral (6-channel) images collected by a Mars rover. We find that some methods are more sensitive to spectral (compositional) novelty, while others are more sensitive to morphological (shape-based) novelty. Code: Novelty Detection in Multispectral Mastcam Images (github) Data: Mars novelty detection Mastcam labeled dataset Automated Classification to Improve the Efficiency of Weeding Library Collections. Kiri L. Wagstaff and Geoffrey Z. Liu. Journal of Academic Librarianship, 44(2), p. 238-247, 2018. We evaluated several machine learning classifiers in terms of their ability to predict which books are most likely to be weeded from a collection. We applied this method to a collection of more than 80,000 items from an academic library and found statistically significant agreement (p = 0.001) between classifier and librarian decisions. Marginalia in the digital age: Are digital reading devices meeting the needs of today's readers? Melanie Ramdarshan Bold and Kiri L. Wagstaff. Library & Information Science Research, 39(1), 16-22, 2017. We surveyed readers to find out about their attitudes toward marginalia, and whether and how often they indulged in it themselves. We also investigated whether marginalia translates into electronic books and which features are most desired by users of e-readers.The Early History of the Monrovia Library, my term paper for LIBR 280 (pdf, 16 pages, 1.0M)The Evolution of Marginalia, my term paper for LIBR 200 (pdf, 14 pages, 1.1M)2019 Senior Member of AAAI2017 Calvert N. Ellis Memorial Lectureship from Juniata College in Huntingdon, PAI won the 2017 National Adult Spelling Bee!I was elected to the AAAI Executive 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 Medal2012 AAAI Outstanding Program Committee Member Award (one of four people chosen)2012 Young Alumni Par Excellence Award from the University of Utah2008 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 andKids Building Things.I traveled to Guatemala to volunteer with Librarians Without Borders in April 2018.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.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).1-minute video for my Mars One application is available. I'd love to hear what you think!Read this great writeup in The Times-Independent (my hometown newspaper) (Aug. 22, 2013)I served as part of Crew 89 at the Mars Desert Research Station, from January 22 to February 7, 2010. You can read our blog to find out what we did, see pictures, and watch videos!

TAGS:Kiri Wagstaff 

<<< Thank you for your visit >>>

Hot Websites