ITMO Student Creates Best Algorithm for Space Navigation in American Contest

Ammar Ali, a Master's student at ITMO took first place in a contest where he had to create a model that predicts disturbances in the Earth's geomagnetic field. The competition was held by the American National Oceanic and Atmospheric Administration with support from NASA.

As a contestant of the MagNet: Model the Geomagnetic Field competition, Ammar Ali, a second-year Master's student at ITMO's Information Technology and Programming Faculty, developed a model to forecast the disturbance-storm-time (Dst) index which measures the severity of geomagnetic storms. The algorithm created by Ammar will help effectively deal with errors in magnetic navigation that is directly affected by geomagnetic disturbances.

Participants of the competition had to create a machine learning model whose forecasts were congruent with the data from the NASA: Advanced Composition Explorer (ACE) and Deep Space Climate Observatory (DSCOVR) satellites.

Ammar Ali succeeded in creating the algorithm for real-time satellite data processing that had the smallest amount of errors when compared to the actual satellite data. His project outperformed over 600 other solutions from contestants all over the world.

"Naturally, I was very pleased to win a contest of this level—supported by NASA themselves. Their involvement with the competition actually persuaded me to participate. I got into machine learning two years ago and I thought that such contests could be really useful in my studies. That's why I started looking for them on Driven Data—this resource has many projects in data science," shares Ammar.

Currently, Ammar is in the second year of his Master's program at ITMO, but he is planning to continue his studies with a Ph.D. degree. He is going to work with machine learning and computer vision.

Provided by ITMO University