Researcher. Developer. Activator.

I'm a PhD student in Computer Science at the University of Minnesota advised by Dr. Vipin Kumar. My research is focused on application of machine learning to Earth science problems, with a particular emphasis on remote sensing imagery.

Currently, I'm working on the problem of spatial upscaling to estimate global carbon and energy fluxes in terrestrial ecosystems.

My broader interests include:

  • Machine Learning & AI
  • Upscaling/Downscaling
  • Multi/Hyperspectral Remote Sensing Imagery
  • Knowledge-Guided Machine Learning (KGML)
  • Big Geospatial Datasets
  • Super-resolution

Affiliations:

  • Research Assistant, 05.2025-present, Data Mining Lab, Department of Computer Science and Engineering, University of Minnesota
  • Research Assistant, 08.2024-present, Real-time GeoInformation Systems Lab, University of Minnesota
  • Private Consultant, 11.2023-08.2024, 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:

  • Ph.D. Computer Science, 2025-present, University of Minnesota, MN, USA
  • M.S. GIS, 2024-2025 (expected), University of Minnesota, 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
Aleksei Rozanov

Blog

Regression Trees

Regression Trees Explained: The Most Intuitive Introduction

May 27, 2025
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Semantic Segmentation

Semantic Segmentation of Remote Sensing Imagery using k-Means

Mar 14, 2024

Read on Medium
Read on Medium

Publications

NorthFlux: Upscaling carbon fluxes in the northern hemisphere using an ensemble of regression machine learning models
Rozanov, A., Gribanov K., Dyukarev E., and Zakharov V.
[under review]
All-Weather Drone Vision: Passive SWIR Imaging in Fog and Rain
Bessonov, A., Rozanov, A., White, R., Suwito, G., Medina-Salazar, I., Lutfullin, M., Gusev, D., Shikov, I.
Drones (2025), 9(8), 553
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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
Rozanov, A., Zadvornykh I., Gribanov K., and Zakharov V.
Atmospheric and Oceanic Optics 37.2 (2024): 199-204
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A neural network model for estimating carbon fluxes in forest ecosystems from remote sensing data
Rozanov, A., and Gribanov, K.
Atmospheric and Oceanic Optics 36.4 (2023): 323-328
Read Paper