Anna Petrovskaia

Graduated from: Moscow State University, geographical faculty

Research interests: Digital soil mapping, machine learning methods in agriculture

Thesis title: Machine learning and modeling for prediction of spatial organization of the soil cover on a local scale

Publications:

1. “Maxvol algorithm for soil sampling design based on topographical features” A. Petrovskaia, G. Ryzhakov, I. Oseledets

2. “Reconstruction of soil structure imaged by X‐Ray using Generative Adversarial Network” A. Petrovskaia, R. Jana, A. Burukhin, P. Tregubova, I. Oseledets

Conferences:

1.”Sampling design for large-scale soil mapping based on MaxVol algorithm and Simulated annealing” – ”Pedometrics 2019”, University of Guelph, Ontario, Canada, 2019

2.”Modified Maxvol algorithm for soil sampling design based on topographical features” – ”The 5-th international conference on Matrix Methods in Mathematics and Applications”, Moscow, 2019

3.”3D representation of soil physical properties using Generative Adversarial Networks” – ”The 3rd annual MIT-Skoltech Conference”, Moscow, 2019

4.”Applying machine learning methods for large-scale soil types prediction” – “21st World Congress of Soil Science”, Brazilian Soil Science Society, Rio-de-Janeiro, Brazil, 2018