My research topic is the application of machine learning algorithms to wireless sensing and localization to improve system performance. My thesis covers three main areas: ML(machine learning)-based channel estimation, ML-based wireless sensing, and ML-based wireless positioning.
What is the most fascinating or interesting with your thesis subject?
In my thesis, I develop theoretical algorithms and conduct practical measurements to validate the results. This dual approach allows us to directly assess the performance of the proposed algorithms in practical applications.
Do you believe some results from your research will be applied in practice eventually? And if so, how?
I am confident that some of the results from my research will be applied in practice. The combination of machine learning and traditional signal processing algorithms represents a promising direction for future wireless systems, and relevant standardization organizations have already begun planning and discussing this topic.
What are your plans?
Currently, I am working full-time in Ericsson Sweden. My career plan is to be a standardization engineer so that I can contribute to the standard and push the frontier of wireless technology even further.
Länk till avhandling (på engelska, Lunds universitets forskningsportal).