My research focuses on applying computational methods to remote sensing and innovative phytoplankton studies. Using modern sensor technology, we can obtain comprehensive, real-time information about the environment and phytoplankton under controlled laboratory conditions. However, robust and reliable models are essential for solving nonlinear inverse problems and making accurate predictions.

The advancement of digital environmental research relies on the parallel development of hardware and computational algorithms. At the same time, sources of variation in ground truth data must be carefully controlled. In addition to leveraging digital technologies and AI models, I conduct both field and experimental research and make extensive use of analytical methods, including spectroscopic techniques—from the microscopic scale to Earth observation from orbit.