Kamal Gurbanov is working on a lake model with the Arctic team, drawing on his expertise in mathematical computing to model methane and mercury compounds in Arctic water bodies underlain by permafrost. He is passionate about lifelong learning, and has always wanted to help address the climate crisis.
In college, Gurbanov built skills in software development, data plotting, Python and Java programming, and the basics of machine learning. He would like to pursue a career as a machine learning and artificial intelligence engineer. When he is not working with computers, Gurbanov enjoys playing piano, football, and volleyball.