Applied Machine Learning
Mentoring is important for learning but the mentor’s attention is divided between students. I developed a LLM powered code reviewing tool that is always available. The tool aims to help first year students gain clean-code experience.
The bulk of my academic and industry activity is focused on computer vision. These are some questions that I am addressing. Of course, different data, different contexts.
Time series and biosignals are crucial in healthcare for continuous monitoring, early detection of anomalies, and personalized treatment plans.
Earth observation satellites generate a lot of data and most analytic solutions are automated. I briefly touched two sensitive areas of research in this field, the cloud detection and land labeling.
Other interests
I ventured into PCB design as a software engineer, to bridge the gap between software and hardware, gaining a holistic skill set crucial skills but also to tap into every IoTa of performance potential.
Around 2021 I embarked into a short adventure in blockchain. The project was pretty awesome. LBRY is a place where users can find great videos, music, ebooks, and more: imagine a vast digital library that is available on all of your devices.
In some of my roles, I utilized Java EE and Python Django to create and maintain web applications. An example is here: hn-sorter.com