About Me
I am Eya Cherif, a PhD researcher at the Institute for Earth System Science and Remote Sensing, Leipzig University, where I work within the Remote Sensing in Geo- and Ecosystem Research team under the supervision of Prof. Hannes Feilhauer and Prof. Teja Kattenborn.
My research sits at the intersection of deep learning and environmental science, with a focus on biodiversity monitoring and vegetation property estimation using hyperspectral remote sensing data, developing novel deep learning approaches that turn raw Earth observation data into scalable, actionable ecological insights with real-world impact.
My background is a Master’s in Computer Science from the University of Passau, part of a double-degree program with Leipzig University, built on a foundation as a Telecommunication Engineer from Sup’Com. My journey into the remote sensing field began with a Master’s thesis internship at Esri. My thesis on deep learning for land cover classification using multispectral and SAR data ignited a passion for bridging cutting-edge research with practical, deployable solutions.
A defining milestone of my PhD. was a research stay at Mila – Quebec Artificial Intelligence Institute, under the supervision of Prof. David Rolnick and Dr. Arthur Ouaknine, a collaboration that culminated in a publication at NeurIPS 2025.
Beyond academia, I am driven by a strong ambition to translate research into industry-ready solutions. I believe technology has the power to reshape how we understand and protect our planet, and I want to be part of that mission. Always seeking new challenges and expanding my expertise, I hold certifications from Esri, Microsoft Azure (AZ-900), DeepLearning.AI, and Ironhack.
If you’re building the future of environmental AI, Earth observation, or sustainable technology, feel free to reach out.
News
- 04/2026: Published paper: Uncertainty Assessment in Deep Learning-based Plant Trait Retrievals from Hyperspectral data at Biogeisciences
- 03/2026: Completed Data science and Machine learning Bootcamp at Ironhack
- 01/2026: Accepted paper: Uncertainty Assessment in Deep Learning-based Plant Trait Retrievals from Hyperspectral data at Biogeisciences
- 12/2025: Poster presentation at NeurIPS 2025 (San Diego, USA) paper