ML4EO
Machine Learning for Earth Observation
14-16 June 2027
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ML4EO 2027
Overview
Advances in remote sensing have shifted the paradigm of Earth observation from data scarcity to data abundance, offering enormous potential for economic, environmental, and social benefits. Artificial intelligence and machine learning present new opportunities to harness this data, enabling automated extraction of insights, trend predictions, and identification of key environmental and policy factors. AI/ML also brings increasing challenges
Building on the success of the four previous conferences, this three-day conference will bring together experts and practitioners from remote sensing, data science, and industry to reflect on the state of the art in remote sensing and identify the most promising directions for future innovation. Hosted at the University of Exeter, the event welcomes participants from academia, the public sector, and industry, at all career stages, to create a vibrant research community.
Together we will
- Share scientific discoveries, good practice, and industry perspectives
- Explore emerging applications and new opportunities for remote sensing and machine learning
- Foster collaborations, build networks, share opportunities and provide hands-on training
Our Sponsors
The Machine Learning for Earth Observation (ML4EO) conference brings together researchers and practitioners from academia and industry working at the intersection of machine learning, Earth observation, remote sensing, and geospatial analysis. The conference provides a focused forum for sharing cutting-edge research, practical applications, and emerging challenges, alongside training workshops and networking opportunities.
Hosted annually at the University of Exeter, UK, since 2021, ML4EO has grown steadily in scale and impact. The 4th ML4EO (2026) attracted 135 participants from 18 countries. Participants included early-career researchers, established academics, industry practitioners, and returning members of the ML4EO community. The conference consistently receives outstanding feedback for its scientific programme and collaborative atmosphere.
ML4EO aims to foster an open community where participants share ideas, best practice, and the latest advances in machine learning for Earth observation. We welcome sponsorship and workshop contributions to support the conference and its continued growth. If you are interested in becoming a sponsor or contributing to the programme, please see our sponsorship information.
Supporters
Testimonials
We’re so grateful for everyone who joined ML4EO 2026. Your voices made it a truly impactful event. Here’s what some of our participants had to share about their experience:
“It was an amazingly useful get together and the presentations really showcased the opportunities that are being developed and managed by the University and key partners”
“I really found the talks interesting and I really appreciated the balance between presentations, workshops, and panel discussions. I like the community and I think that I will definitely come back.”
“Sharing recordings of talks and especially workshops is a great addition. Thanks for a well-run and interesting conference.”
The broad range of topics covered, different presentation styles (e.g. posters, talks, panels, workshops), good size (there were plenty of delegates to network and discuss with, but did not feel too overwhelming), the food was great!
“The conference was highly valuable and well-organised. As a returning participant, I appreciate the consistent quality, welcoming atmosphere and inclusivity.”
“The schedule struck a nice balance between presentations, mingling, panel discussions and workshops. The workshops were also highly relevant and easy to follow.”
The event is hosted by the University of Exeter with support from the Centre for Environmental Intelligence, and the Global Systems Institute
