AskSME: Dr. Hannah Kerner - Artificial Intelligence Lead I am currently an Assistant Professor in the School of Computing and Augmented Intelligence at Arizona State University. My research focuses on developing machine learning systems for real-world data and use cases. This includes remote sensing and spatial datasets, fairness (particularly w.r.t. geographic bias), scientific discovery and exploration, agriculture and food security, and other topics. I am the Machine Learning Lead and U.S. Domestic Co-Lead for NASA Harvest, NASA’s agriculture and food security initiative run as a consortium out of the University of Maryland. I was recognized on the Forbes 30 Under 30 list in Science in 2021. I also write and speak about challenges for developing AI/ML applications for real world problems, such as in this recent article in MIT Technology Review.

Prior to joining the faculty at ASU, I was an Assistant Research Professor at the University of Maryland, College Park. I did my Ph.D. at Arizona State University on machine learning methods (especially novelty detection) for planetary exploration missions. I received my B.S. in computer science from the University of North Carolina at Chapel Hill where I conducted research on 3D motion planning for autonomous agents. I have worked at NASA’s Jet Propulsion Laboratory, Goddard Space Flight Center, and Langley Research Center, as well as the commercial remote sensing company Planet, Inc. I am passionate about advancing opportunities for people who have traditionally been underrepresented in or excluded from computer science and devote much of my time outside of research to these efforts.

You can download my CV here.


  • Top 10 of 100 projects solving problems related to the UN SDGs with AI, International Research Centre on Artificial Intelligence (IRCAI), for NASA Harvest (2021)
  • Forbes 30 Under 30 in Science (2021)
  • Outstanding Research Faculty department award (2021)
  • Radiant Earth Foundation’s 15 Leading Women in ML4EO (2021)
  • Google Women Techmakers award (2018)


  • Dec 2022: Our proposal for the Machine Learning for Remote Sensing workshop at ICLR 2023 was accepted!
  • Nov 2022: Our paper “OpenMapFlow: A Library for Rapid Map Creation with Machine Learning and Remote Sensing Data” was accepted for AAAI 2023!
  • Nov 2022: Our paper “Multi-Region Transfer Learning for Segmentation of Crop Field Boundaries in Satellite Images with Limited Labels” was accepted for the 2nd Annual AAAI Workshop on AI to Accelerate Science and Engineering (AI2ASE)!
  • Nov 2022: Inbal Becker-Reshef and I gave an invited talk for the AI Helps Ukraine fundraiser conference! See recording here
  • Nov 2022: Our NASA proposal for “NASA ACRES: A Climate Resilient Ecosystem Approach to Strengthening US Agriculture” (PI: Whitcraft/UMD) was awarded! (NASA Earth Science Applications: Agriculture program)
  • Oct 2022: Our NASA proposal for “NASA Harvest: NASA Food Security and Agriculture Consortium” (PI: Becker-Reshef/UMD) was awarded!
  • Oct 2022: I was a selected participant in the first U.S.-Africa Frontiers of Science, Engineering, and Medicine symposium, held in partnership with the African Academy of Sciences in Nairobi, Kenya!
  • Sep 2022: We traveled to Rwanda for the AGRF Summit held in Kigali!
  • Sep 2022: Our NASA proposal for “EO-Enabled Regional and National Agricultural Monitoring in West Africa” (PI: Nakalembe/UMD) was awarded! (NASA SERVIR program)
  • Sep 2022: Our NASA proposal for an “EO-Enabled Food Security Dashboard to Close Critical Data Gaps in Highly Food Insecure Maui County” (PI: Kerner/ASU) was awarded! (NASA ROSES Equity and Environmental Justice program)
  • Aug 2022: Our paper on “Spectral Diversity of Rocks and Soils in Mastcam Observations Along the Curiosity Rover’s Traverse in Gale Crater, Mars” was accepted to JGR: Planets!
  • Aug 2022: I started a new faculty position at ASU School of Computing and Augmented Intelligence!
  • Aug 2022: Catherine Nakalembe and I gave an invited talk for the Computer Vision for Ecology summer school! See recording here
  • July 2022: We presented our invited paper on “Guiding Field Exploration on Earth and Mars with Outlier Detection” at IGARSS!
  • July 2022: Our paper on “High-Resolution Regional Digital Elevation Models and Derived Products from MESSENGER MDIS Images” was accepted to Remote Sensing!
  • June 2022: I gave an invited talk for the AgricultureVision workshop at CVPR 2022!
  • June 2022: We gave an invited tutorial on Machine Learning for Remote Sensing at CVPR 2022! Materials and recordings here
  • June 2022: Our paper “Phenological normalization can improve in-season classification of maize and soybean: A case study in the central US Corn Belt” was accepted to Science of Remote Sensing!
  • May 2022: We traveled to Bonn, Germany and gave several oral and poster presentations for the Living Planet Symposium hosted by the European Space Agency!
  • May 2022: Our paper “Domain-Agnostic Outlier Ranking Algorithms—A Configurable Pipeline for Facilitating Outlier Detection in Scientific Datasets” was accepted to Frontiers in Astronomy and Space Sciences!
  • April 2022: I gave the keynote speech for the AI for Earth Observations (AI4EO) Food Security Challenge awards ceremony! See recording here
  • March 2022: Our book on “Machine Learning for Planetary Science” was published by Elsevier!
  • March 2022: I gave a Hyperwall talk at the NASA booth in the Commodity Classic conference held in New Orleans!
  • Feb 2022: Kicked off our project on “Optimizing Crop Yield Data Collection for Supply Chain Enhancement”, funded by Tetra Tech and Bill & Melinda Gates Foundation! (PI: Nakalembe/UMD)
  • Feb 2022: Our paper “Applications and Considerations for AI-EO for Agriculture in Sub-Saharan Africa” was accepted for an oral presentation at AAAI 2022, International Workshop on Social Impact of AI for Africa!
  • Jan 2022: Our CVPR 2022 workshop proposal was accepted for the 3rd International Workshop and Prize Challenge on Agriculture-Vision: Challenges & Opportunities for Computer Vision in Agriculture!
  • Dec 2021: Our team at NASA Harvest was recognized in the Top 10 of 100 projects solving problems related to the UN SDGs with AI, International Research Centre on Artificial Intelligence (IRCAI)!
  • Dec 2021: Our paper on task-informed meta-learning for crop type mapping was accepted for the AI for Agriculture and Food Systems (AIAFS) workshop at AAAI!
  • Nov 2021: Our paper on Foundation Models for Earth Monitoring: Proposal for a Climate Change Benchmark was accepted for the Climate Change AI workshop at NeurIPS!
  • Oct 2021: Our NASA E-Clips educational videos explaining how NASA data is used for agriculture and food security are live!
  • Oct 2021: Our work on rapid response cropland mapping with ML/EO in Togo was featured in Radiant Earth’s article on Discoverable and Reusable ML Workflows for Earth Observation!
  • Sep 2021: Our paper on the new CropHarvest dataset was accepted for NeurIPS Datasets and Benchmarks track!
  • Aug 2021: Kicked off our project on planted area change estimation using ML/EO in Ethiopia and Sudan, part of FEWS NET East Africa virtual crop tour! (PI: Kerner/UMD)
  • Jul 2021: Field data collection campaign in Uganda for Street2Sat/Helmets Labeling Crops project completed! (PI: Nakalembe/UMD)
  • Apr 2021: Profile article featured on NASA Applied Sciences website!
  • Apr 2021: Kicked off our project on Domain-agnostic Outlier Ranking Algorithms (DORA) with JPL, funded by NASA SMD as a Cross-Divisional AI/ML Use Case Demonstration! (PI: Kerner/UMD)