About

I am currently an Assistant Professor in the School of Computing and Augmented Intelligence at Arizona State University. My research focuses on advancing the foundations and applications of machine learning to foster a more sustainable, responsible, and fair future for all. Our lab is conducting research projects in machine learning for remote sensing, algorithmic bias, and machine learning theory. I am the AI/Machine Learning Lead for NASA Harvest and NASA Acres as well as Center Faculty for the ASU Center for Global Discovery and Conservation Science (GDCS). 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.

Working with Kerner Lab

If you are interested in any position with the group (Postdoc, PhD, MS, Visitor, Intern, etc), instead of emailing me please fill out the interest survey below so I can better organize my responses. I am unlikely to respond to individual emails. We are actively looking for highly-motivated students to support ongoing projects in algorithmic biases, shortcut learning, and benchmark datasets for ML.

• Use this form if you are at ASU
• Use this form if you are not at ASU

Recognition

• 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)

News

• November 2024: Our paper, “Hotspotter: A Generalizable Pipeline for Automated Detection of Subtle Volcanic Thermal Features in Satellite Images,” was accepted for publication at AAAI 2025 Innovative Applications of AI! (public link coming soon)
• October 2024: Kerner Lab’s Dr. Ana Tarano delivered a testimony to the Maui County Council’s Agriculture, Diversification, Environment, and Public Transportation (ADEPT) committee about our work to support food security and agriculture in Maui county in relation to their strategic plan!
• October 2024: Our research was featured in ASU’s AI Journey report (page 51), showcasing ASU’s vision for harnessing AI’s power to elevate student success, drive groundbreaking research, and redefine the future of education and work.
• October 2024: I gave an invited talk for the first Computer Vision for Ecology workshop at ECCV in Milan!
• September 2024: We published a preprint of our new paper, “Fields of The World: A Machine Learning Benchmark Dataset For Global Agricultural Field Boundary Segmentation”, on Arxiv! This paper introduces our new near-global field boundary segmentation benchmark dataset and demonstrates impressive zero-shot results for FTW-trained models. See more details about the dataset and use it yourself at https://fieldsofthe.world/.
• September 2024: Our team visited Maui, Molokai, and Lanai for our NASA project supporting local farmers and food security in Maui County! We talked story with community leaders and presented a project update at UH Maui County.
• September 2024: I gave a colloquium for the Department of Astronomy and Planetary Science at Northern Arizona University in Flagstaff! NAU is hiring faculty in AI/ML, so please apply if you are on the job market!
• September 2024: I gave an invited talk for the United Nations and ITU AI for Good, watch the recording!
• August 2024: Our NASA proposal, “Enabling Next-Generation Data Science in Planetary Research with Machine Learning Dataset Creation Tools in JMARS”, was selected for a Planetary Data Archiving, Restoration, and Tools (PDART) award!
• July 2024: PhD student Gedeon Muhawenayo was featured in an article, “Emerging machine learning expert leads Kenya AI workshop”, by ASU Full Circle!
• July 2024: PhD student Chenwei Cui presented a poster and I gave an invited talk at ICML 2024 in Vienna!
• June 2024: Our paper, “An All-MLP Sequence Modeling Architecture That Excels at Copying”, was accepted for the Next Generation of Sequence Modeling Architectures Workshop at ICML 2024!
• June 2024: A preprint of our paper, “The Promise and Pitfalls of Machine Learning in Ocean Remote Sensing”, is available now!
• June 2024: Our paper, “Mission Critical – Satellite Data is a Distinct Modality in Machine Learning” will be featured as a Spotlight 🌟 Poster at ICML 2025! (3.5\% acceptance rate for spotlights)
• June 2024: Our paper, Sat2Cap: Mapping Fine-Grained Textual Descriptions from Satellite Images, won the Best Paper Award 🏅 in the EarthVision workshop at CVPR!
• May 2024: We had two position papers accepted for the ICML 2024 conference!
• May 2024: We successfully hosted the 2nd Machine Learning for Remote Sensing workshop at ICLR 2024! Stay tuned for ICLR 2025.
• Apr 2024: Our paper, Sat2Cap: Mapping Fine-Grained Textual Descriptions from Satellite Images, was accepted for the EarthVision workshop at CVPR!
• Mar 2024: Kerner Lab PhD student Mirali Purohit presented about our research on the impact of pre-training data compositions on geospatial foundation model performance at the NASA SMD AI Workshop in Huntsville!
• Mar 2024: I gave a spotlight presentation at the Machine Learning and Data Management for Earth Observation workshop hosted by the BIFOLD (Berlin Institute for the Foundations of Learning and Data) in Berlin!
• Mar 2024: I presented about our work to create solutions using AI and Earth observations for food security and other community challenges in Maui County at the Hawaii Student Success Institute in Honolulu!
• Mar 2024: A preprint of our paper, “Application-Driven Innovation in Machine Learning,” is now available on arxiv!
• Feb 2024: Our paper, “Assessing and addressing the global state of food production data scarcity,” was published in Nature Reviews Earth and Environment!
• Feb 2024: A preprint of our paper, “Mission Critical – Satellite Data is a Distinct Modality in Machine Learning,” is now available on arxiv!
• Jan 2024: I presented about our work to create solutions using AI and Earth observations for food security and other community challenges in Maui County at the Hawaii Data Science Institute!
• Dec 2023: Our proposal for the EarthVision workshop at CVPR 2024 in Seattle was accepted!
• Dec 2023: Our proposal for the 2nd Machine Learning for Remote Sensing Workshop at ICLR 2024 in Vienna was accepted!
• Dec 2023: I was appointed to the NOAA Science Advisory Board (SAB) Data Archiving and Access Requirements Working Group (DAARWG), which is a 3-year Federal Advisory Committee appointment!
• Dec 2023: A preprint of our paper, “Satellite Data Shows Resilience of Tigrayan Farmers in Crop Cultivation During Civil War,” is now available on arxiv!
• Dec 2023: I gave a keynote talk at the NeurIPS Sustainable Computing workshop in New Orleans!
• Dec 2023: I gave three research talks and hosted several sessions on machine learning at the AGU Fall Meeting in San Francisco!
• Nov 2023: Our paper “Lightweight, Pre-trained Transformers for Remote Sensing Timeseries” was accepted for a spotlight presentation at the NeurIPS 2023 Climate Change AI Workshop!
• Oct 2023: Our paper “ConeQuest: A Benchmark for Cone Detection on Mars” was accepted to WACV 2023!
• Oct 2023: Our proposal to Google Research (Collective & Society Centered AI) titled “A Data-Centric Approach to Improve Geographic Equity in Geospatial ML” was awarded!
• Oct 2023: Our paper “Automated Multi-class Crater Segmentation in Mars Orbital Images” was accepted to the GeoAI workshop at SIGSPATIAL 2023!
• Oct 2023: Our collaboration with Maui United Way to support residents impacted by the Maui wildfires was highlighted an article in Maui Times!
• Sep 2023: Our NSF RAPID proposal, “RAPID: Rapid computational modeling of wildfires and management with emphasis on human activity,” was selected!
• Sep 2023: Our proposal, “Lowering the Barriers to Planetary Science Studies with a Large Mars Model,” was selected for the JPL Strategic University Research Program - congrats to PhD student Mirali Purohit on this fellowship!
• Sep 2023: Our paper, “GEO-Bench: Toward Foundation Models for Earth Monitoring,” was accepted for NeurIPS 2023 Datasets and Benchmarks Track!
• Aug 2023: We were awarded a grant from NASA, “Machine Learning Datasets for Public Good with a Data-Centric AI Approach,” to lead the development of new ML datasets using satellite remote sensing data in partnership with NASA and ML Commons!
• Aug 2023: Catherine Nakalembe and I gave a talk on Supporting Global Food Security with Machine Learning and Earth Observations for the 2023 Computer Vision for Ecology summer school!
• Aug 2023: We created a website of satellite data sources in support of the Maui wildfires here
• July 2023: I taught a guest lecture on AI for Agriculture for Climate Change AI’s summer school, which you can watch here
• July 2023: Our latest paper, “How accurate are existing land cover maps for agriculture in Sub-Saharan Africa?” is available on arxiv!
• May 2023: Our NASA Multidomain Reusable Artificial Intelligence Tools proposal titled “Anomaly Visualization for Earth and Heliophysics GNSS Data using DORA” (PI: Rebbapragada/JPL) was selected!
• May 2023: We hosted a successful 1st Workshop on Machine Learning for Remote Sensing at ICLR 2023 and Tutorial on the same at CMU Africa! Read accepted papers on our workshop website
• Apr 2023: Our latest paper, “Lightweight, Pre-trained Transformers for Remote Sensing Timeseries,” is available on arxiv!
• Apr 2023: I am thrilled to be affiliated with the Center for Global Discovery and Conservation Science at ASU! The Center’s mission is to address human-environmental challenges on land and sea.
• Apr 2023: I had fun giving the keynote talk on “Artificial Intelligence: From Sci-Fi to Societal Good” at the Machinery Dealers National Association meeting in Tucson!
• Mar 2023: Catherine Nakalembe and I published a Perspective article titled Considerations for AI-EO for agriculture in Sub-Saharan Africa in Environmental Research Letters [paper link]
• Mar 2023: Kerner Lab group members Manthan Satish, Mirali Purohit, and Aditya Mohan made the winning solution for the Wildfire Risk and Social Disparity track at SpaceHACK for Sustainability
• Mar 2023: I gave an invited talk for the NSF AI Planning Institute Seminar at Carnegie Mellon University!
• Mar 2023: An article was published about our work combatting food security in Maui County using AI!
• Feb 2023: I gave the colloquium talk for the School of Earth and Space Exploration at ASU! See the recording here
• Feb 2023: Our group traveled to Maui, Lanai, and Molokai to kick off our ‘Aina Data Stewards program!
• Dec 2022: Our proposal for the Machine Learning for Remote Sensing workshop at ICLR 2023 was accepted!
• Nov 2022: An article was published about our AI and Earth Observations-enabled food security project in Maui County!
• 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)