Aleksei Rozanov
Research Assistant
Real-time GeoInformation Systems Lab,
University of Minnesota, USA
CV
rozan012@umn.edu
Researcher. Developer. Activator.
About me
I am a master student at the University of Minnesota studying Geographic Information Science . Being a geo data scientist I research, model and analyse terrestrial ecosystems using various geospatial data (including remote sensing) and machine learning approaches. My particular interests include fusion of multispectral imagery and novel computer vision techniques and generating of big geospatial datasets.
🤓Interests:
- Machine Learning & AI
- Multi/Hyperspectral Remote Sensing Imagery
- Geospatial Data
- Carbon Fluxes & Carbon Markets
🔎Affiliations:
- Research Assistant, 2024-present, Real-time GeoInformation Systems Lab, University of Minnesota
- Private Consultant, 01.2024-08.2024, Online
- Research Assistant, 05.2021-08.2024, Climate and Environmental Physics Lab, Ural Federal University
- Teaching Assistant, 07.2023 and 07.2024, Climatematch Academy, Online
🎓Education:
- M.S. GIS, 2024-2026, University of Minnesota, Twin Cities, MN, USA
- M.S. Big Data and Machine Learning, 2022-2024, ITMO University, Saint Petersburg, Russia
- B.S. Hydrometeorology, 2018-2022, Ural Federal University, Yekaterinburg, Russia
🏆Recognition and Rewards:
- MVP Challenge Award, 3,000$, MIN-CORPS, University of Minnesota, October, 2024
- University of Minnesota Institute of Environment Graduate Scholar, Agriculture and Climate Cohort, 2024
- Scholarship of Potanin Foundation for Master students, 2023-2024, ITMO University, Saint-Petersburg, Russia
📚Publications:
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Rozanov A., and Gribanov K., "NorthFlux: Upscaling carbon fluxes in the northern hemisphere using an ensemble of regression machine learning models", Advances in Statistical Climatology, Meteorology and Oceanography (under review)
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Rozanov, A. P., et al. "Estimates of Carbon Dioxide Flux into the Forest Ecosystem Based on Results of Ground- Based Hyperspectral Sounding of the Atmosphere and an Artificial Neural Network Model." Atmospheric and Oceanic Optics 37.2 (2024): 199-204. Read
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Rozanov, A. P., and K. G. Gribanov. "A neural network model for estimating carbon fluxes in forest ecosystems from remote sensing data." Atmospheric and Oceanic Optics 36.4 (2023): 323-328. Read
