Celebrating Women Leading the ML4EO Community

Meet the rising stars of women around the world at the forefront of machine learning for Earth observation.

Radiant Earth
Radiant Earth Insights
11 min readMar 8, 2021


Happy International Women’s Day!

Today, we celebrate the women who break barriers and expand the frontiers of machine learning for Earth observation. This essential field can help us understand the planet’s ecosystem, its different elements, interactions, and changes.

These 15 leading women were selected from 56 outstanding nominations from the ML4EO community. The Radiant Earth Foundation selection committee created a set of criteria to rank the nominees.

The first criterion required nominees to work in machine learning for the Earth observation sector. Second, the nominee must have been nominated by the community. People nominated by more than one person received 2 points.

We prioritized nominees whose work is of global importance. We gave a point to nominees working on topics related to the Sustainable Development Goals or research that transcends geographic boundaries, such as climate change and food security. We gave another point to nominees if their work had an element of diversity, either diversifying applications, training data, or human resources.

We gave one point to nominees leading a global project or founded projects and start-ups and another to those who have received international recognition for their work.

We want to thank all the nominators for their excellent recommendations!

Featured below is the final list of leading women in machine learning for Earth observation for 2021.

Congratulations to the finalists!

We’ve put together a Twitter list with all the nominees and women nominators. Give the list a follow if you like.

Catherine Nakalembe, NASA Harvest (United States & Uganda)

Dr. Catherine Nakalembe is the program director of NASA Harvest Africa and an assistant research professor at the University of Maryland. Catherine uses remote sensing, machine learning, and Earth observation to assess food insecurity and disaster risk in Africa to aid smallholder farmers throughout the continent. Leading the Agriculture and Food Security Thematic group with NASA’s SERVIR Applied Sciences team, she has created a range of satellite-dependent crop monitoring systems in Tanzania, Uganda, Kenya, and Rwanda. In 2020, she was awarded the Africa Food Prize for her instrumental efforts in increasing sustainable food security. Just one of Catherine’s achievements has been developing a disaster risk assessment related to droughts in Uganda that led to the support of over 370,000 individuals by estimating the number of people who would become food insecure. Her research saved the government from an extensive and costly emergency program. Follow Catherine’s work via her LinkedIn Profile.

Xiaoxiang Zhu, Technical University of Munich (Germany & China)

Dr. Xiaoxiang Zhu is a professor at the Technical University of Munich, heads the EO Data Science department in the Earth Observation Center at the German Aerospace Center, and leads its Big Data Analytics team. Xioaxiang uses machine learning, data science, and signal processing on satellite data to map and monitor cities. Her work tracks the progress of global urbanization to assess natural hazards and climate change. Xiaoxiang has led several achievements, including the first 3D and 4D global urban models for risk management, planning, and various other applications. She was awarded the 2018 PRACE Ada Lovelace Award for HPC for her research contributions and models. Along with her other duties, Xiaoxiang is the IEEE Transactions on Geoscience and Remote Sensing’s associate editor. Follow Xiaoxiang’s work on her Technische Universität München Profile page.

Miriam Gonzalez, Humanitarian OpenStreetMap and UP42 (Germany & Mexico)

Miriam Gonzalez is the board president of Humanitarian OpenStreetMap Team, Partnership Manager at UP42, and co-founder of Geochicas, a community of women who collaborate with OpenStreetMap. She has played an essential role in diversifying the geospatial field with more women and representation from Mexico and Latin America through educational workshops and collaborations. Miriam has been a key player in increasing the availability and promotion of open data. At OpenStreetMap, she has coordinated various global projects to combat disease, aid in disaster relief, and use maps to help remote communities. She was also an early advocate in incorporating machine learning algorithms to OpenStreetMap. Miriam was named one of the 50 Digital Leaders of Mexico in 2014 by then-President Enrique Peña Nieto for her technological contributions. Follow Miriam’s work via her LinkedIn Profile.

Morgan Crowley, University of McGill (Canada)

As a Ph.D. candidate at the University of McGill, Morgan Crowley uses remote sensing to monitor wildfire disturbances. She is also the founder of Ladies of Landsat, a community of women in geosciences promoting more diversity and inclusivity within the field. Morgan also co-founded the GeoMixer, a web-based virtual event to engage different people in earth observation. Aside from her success in organizing, Crowley is a groundbreaking scientist researching the use of satellite imagery to assess and map wildfires for better management. Her algorithms have been essential to the advancement of fire monitoring and addressing the issues associated with analyzing wildfires. She was recently named a Geospatial World 50 Rising Star 2021 by Geospatial World Media for her commitment to diversity and methodologies in wildfire assessment. Follow Morgan’s work on ResearchGate.

Chelle Gentemann, Farallon Institute (United States)

Dr. Chelle Gentemann is a senior scientist with the Farallon Institute, an affiliate of the Applied Physics Laboratory at the University of Washington, and has served on several boards and committees, including NASA, NOAA, and AGU. Chelle’s focuses on oceanography. She uses machine learning and remote sensing data to research and monitor sea surface temperatures, air-sea relationships, microwave and infrared sensor data, and more. She is also a staunch advocate for inclusivity throughout the cloud computing industry for better collaboration and more voices. Chelle received the 2013 American Geophysical Union Charles S. Falkenberg Award for her international leadership, making surface temperature research more accessible and accurate and for being devoted to the planet’s well-being. Follow Chelle’s work via her LinkedIn Profile.

Hannah Kerner, NASA Harvest (United States)

Dr. Hannah Kerner is an assistant professor at the University of Maryland, the machine learning lead, and the U.S. domestic co-lead at NASA Harvest. She is devoted to developing food insecurity solutions through crop classification and machine learning on remote sensing data. Her innovative methods have been instrumental in assessing crop damage and aiding in decision-making. Throughout her career, Hannah has created methods using machine learning for planetary exploration on Mars, Earth, and the Moon. Along with her passion for monitoring agriculture and advancing scientific discoveries, Hannah is committed to increasing the representation of those underrepresented in computer science-related fields. Hannah was named one of Forbes Magazine’s 30 Under 30 for 2021 in Science and received the Google Women Techmakers award in 2018 for her work in encouraging gender equality in computer science. Follow Hannah’s work on Google Scholar.

Rebecca Moore, Google Earth (United States)

As the creator and leader of the Google Earth Outreach Program, Rebecca Moore shows individuals, communities, non-profits, and organizations worldwide how to use Google’s mapping services for their communities’ needs. Rebecca is also the Director of Engineering at Google Earth Engine, where she heads the development of the widely-recognized platform. She uses Google Earth tools to understand satellite data through cloud computing and machine learning to address global issues. Rebecca also uses the platform as a way to narrate the story of climate change for action visually. For example, her work led to preserving hundreds of acres filled with redwood trees and has extensively documented global tree cover change. In 2016, Rebecca received the Audubon Society’s Rachel Carson Award for her visionary storytelling. Follow Rebecca’s work on ResearchGate.

Stella Mutai, United Nations (Kenya)

Stella Mutai is a GIS and Earth observation analytics consultant working with multilateral organizations such as the United Nations’ International Fund for Agricultural Development. She analyses geospatial data to promote sustainable agriculture and food security in Africa. Stella uses that data to speak with small farm stakeholders about managing their land and water for long-term sustainable use. Stella co-created GeoM&E, a system that collects open-access satellite data for statistical analysis on crop health and growth for farmers to use. She received the Special Africa Prize 2020 from Farming by Satellite for GeoM&E’s success in aiding coffee farmers in Kenya who had trouble accessing vegetation data before developing this system. Stella is also a great advocate for increasing the number of women in geospatial-related fields and acts as a mentor for other young women in Kenya. Read more about Stella’s work on the NL Alumni network.

Keiko Nomura, Space Intelligence (Scotland & Japan)

As a senior analyst at Space Intelligence, Dr. Keiko Nomura uses machine learning and satellite data to develop software solutions for climate change obstacles. Keiko’s work has highlighted the development of plantations in forests, carbon emissions from deforestation, and oil palm demand’s effect on Myanmar’s forest. She has a range of experience within the field as a data expert and policy analyst. She previously developed climate change mitigation tactics and sustainable solutions for countries in Asia and the Pacific with the United Nations. There, she worked to prevent illegal logging, implemented a climate change mitigation and adaptation program, and collaborated with government agencies to meet sustainable energy goals. Her policy background, coupled with her remote sensing expertise, has improved forest monitoring data. She is currently leading projects on carbon monitoring and estimation, Earth observation, and natural capital accounting. Follow Keiko’s work on GitHub.

ZhuangFang NaNa Yi, Development Seed (United States & China)

Dr. ZhuangFang NaNa Yi is the geoAI team lead and a machine learning engineer at Development Seed. Her work focuses on developing machine learning algorithms using open mapping and satellite data for environmental solutions and social good. Nana’s inspiration comes from witnessing the devastating social, economic, and ecological impacts from deforestation in favor of rubber tree crops in Dai/Tai Lue, her hometown, which borders China, Laos, and Myanmar. She was the first woman of her ethnicity to hold a Ph.D., and her projects have aided wildlife conservation, supported equal-access educational opportunities in the global south, and urbanization policies in Ethiopia. Follow Nana’s work on Google Scholar.

Gopika Suresh, Nanyang Technological University (Germany)

Dr. Gopika Suresh is a research fellow at the Asian School of Environmental and Earth Observatory of Singapore, Nanyang Technological University, where she maps coasts, natural disasters, and oil spills in Southeast Asia using satellite imagery. Most recently, Gopika compiled a machine learning-based automatic oil seep location estimator to detect the whereabouts of oil seeps using ocean SAR features and images. She is also passionate about sustainable development, working on land classification tools using the European Union’s Copernicus data to meet the SDGs. Along with her devotion to the environment, Gopika is a co-organizer for Sisters of SAR, a community of women in SAR empowering other women to join the remote sensing field. She is also the founder and coordinator of 500 Women Scientists — Singapore that focuses on increasing the number of women in STEM. She was recently named a Geospatial Media 50 Rising Star 2021 by Geospatial World Media for her remote sensing and diversity work. Follow Gopika’s work on Google Scholar.

Sylvia Makario, Hepta Analytics (Kenya & Rwanda)

Sylvia Makario co-founded Hepta Analytics with her peers at Carnegie Mellon University-Africa to provide solutions for Africa’s biggest hurdles through machine learning. Hepta Analytics aids institutions in developing more cost-effective strategies through data. Sylvia and the Hepta Analytics team have worked with the Samburu Girls Foundation to prevent female genital mutilation throughout Kenya using technology to connect individuals with social workers through mobile while mapping calls. Along with providing gender-based solutions through mapping and data, Sylvia promotes women’s inclusion within the machine learning and geospatial fields. An Industry Innovation Lab Fellow at Carnegie Mellon University-Africa, she mentors at Google’s Launchpad Africa Accelerator, a global shaper with the World Economic Forum’s Kigali, Rwanda Hub. Sylvia is the local lead for NASA’s International Space Apps Challenge in Kigali and is a Mandela Washington Fellow for Young African Leaders alumna. Follow Sylvia’s work via her LinkedIn Profile.

Linda Ochwada, AfroAI (Kenya & Germany)

Linda Ochwada is the founder and managing director of AfroAI, a software consulting company based in Berlin that uses AI to overcome geospatial software challenges. She works to develop products to aid challenges in Africa, such as agriculture, through machine learning. Recently, Linda worked on developing a proximity alert system to alert property owners when a car is coming into proximity. The system is for the African market to provide homes in the continent with security. Other projects included detecting, mapping and monitoring seasonal changes of shallow water ponds using SAR data. Linda is also the co-founder and vice president of Kenderaalala Women Group (KAWG), a community-based organization in Kenya that teaches climate change mitigation tactics to Samia women. Additionally, Linda acts as a mentor and educator for other women who want to learn to program. Follow Linda’s work via her LinkedIn Profile.

Karen Seto, Yale University (United States)

Dr. Karen Seto is a geography and urbanization science professor at Yale University, where she uses satellite data and modeling to showcase how urbanization is affecting the planet with research concentrated in India and China. Her projects include tracking spatiotemporal urbanization patterns in China, understanding the global impacts of urbanization on biodiversity and carbon pools, and developing urban land models with socioeconomic data. In 2019, Karen received the Outstanding Contribution Award from the American Association of Geographers for her remote sensing research and education. She is a member of the National Academy of Sciences and has served on several U.S. and international committees and groups. Karen was also a coordinating lead author for the Urban Chapter of Working Group III of the Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report for policymakers. Follow Karen’s work on Google Scholar.

Claire Krause, Geoscience Australia (Australia)

Dr. Claire Krause is the assistant director of product development for Digital Earth Australia (part of Geoscience Australia). She works with governments, organizations, and other stakeholders to preserve Australia’s biodiversity and natural resources through satellite imagery. Claire has mapped all the open water bodies in Australia using satellite imagery, developing a tool for farmers, wetland conservationists, and other decision-makers to assess water quantity. She has also worked on detecting crop paddock boundaries using image segmentation of processed satellite imagery products. She is also passionate about science communications and enjoys teaching others about her field. In 2015, she received the Robert Hill Award for excellence in science communication by the Research School of Earth Science, Australian National University. Follow Claire’s work via her LinkedIn Profile or Twitter (@Claire_science).



Radiant Earth
Radiant Earth Insights

Increasing shared understanding of our world by expanding access to geospatial data and machine learning models.