Chapter 1Theoretical Background

From October 2023 to July 2026, I was enrolled in a Computer Science degree programme at Babes-Bolyai University in Cluj-Napoca. While I studied a lot of CS topics, I thoroughly enjoyed learning about x86 Assembly, Data Structures, UNIX, and Computer Networks.

In July 2026 I submitted my Bachelor's thesis, entitled "Evaluating .NET Software Quality through Static, Intermediate Language, and Dependency Analysis".

Chapter 2Field Experience

In July 2024 I started my first professional role at Evozon, as a Fullstack Developer. Beyond technical exposure to React and .NET, as well as cross-continental collaboration between Eastern European and North American time zones, the role gave me a habit of clean code and maintainable architecture. It also sparked a huge interest in performance optimization.

Since May 2026 I've been working at PGI as an AI Developer, working on intelligent document processing pipelines. My focus shifted toward artificial intelligence, a domain I had previously approached only out of curiosity and now research daily.

Chapter 3Case Studies

In my free time I was eager to learn as much as possible from experimenting. I created lots of useless apps, most of which can be found on my git profile.

I enjoy messing around with networking. This led to slowly building a multi-node homelab which today hosts most of the apps I use, from photo backups and file sync to S3-compatible object storage and other open-source tools I rely on. Along the way I got comfortable with containerization, Kubernetes, reverse proxies, and CI/CD.

Now I am pretty used to launching small unpolished projects for me and my friends (like the How to listen to music one).

Related are the more serious projects I work on, such as my Streaming Service server (and the mobile app for it), which was originally a POC for a private client and kept my interest, so I continued developing it for my own use.

Chapter 4Future Work

Practical work and reading have been the main way I've improved over time.

Reading-wise, alongside scientific papers, CLR via C# and The Book of Runtime helped me approach optimization problems in .NET codebases. The habit of researching technical concepts is a thing I intend to keep in the future too, with Deep Learning as the backbone of my AI journey.