Work

As far as my education goes, I have an engineering degree in technical physics and a master's degree in artificial intelligence. I am interested in PhD opportunities.

I am currently in my second year of my two-year data science traineeship at ESA ESAC in Madrid. Here, I focus on using machine learning methods to increase the scientific return from space data. I work with monocular depth estimation, building datasets for digital model elevation prediction from orbit, using singular, optical images. Besides that, I am involved with the ESA Datalabs platform, where I contributed to the initial adoption of GPUs onto the platform. One of my projects was highlighted as a scientific use case for the newly adopted ESA supercomputer SPACE HPC during its inauguration. I also had the pleasure of being one of the initial testers of the supercomputer before its official launch.

Before ESA I completed an internship at GMV Innovating Solutions in Warsaw, where I joined a project aimed at hazardous landing zone identification during lunar landing. I've built the quantization and hyperparameter optimization stages of the model development pipeline. Besides that I was tasked with researching and developing methods of input data fusion with high dimensional disparity.

Before focusing on ML, while finishing my engineering degree and during my master's degree, I worked for 2 years as a C++ developer for an R&D project at the Silesian University of Technology.

I am trying to transition into robotics, where my liking for embedded systems and ML speciality will both be valuable skills. After a few years of developing software, I realized that working close to hardware is essential for my job satisfaction and career fulfillment.

Community stuff

I like learning through implementation and explanation:

• 01/2025 | ESA ML Community | Neural Ordinary Differential Equations
• 06/2024 | ESA ML Community | Kolmogorov-Arnold Neural Networks