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Dear Maciej and Peter,

My name is Sorin Birchi, and I am a third-year student at the University Politehnica of Bucharest, studying Automatic Control and Computer Science. My main interests include machine learning, computer and microprocessor architecture, and operating systems.

Outside of university, I teach Python as part of a CISCO program at my university. This is my fourth semester teaching Python and my first semester teaching operating systems through lab sessions.

Last year, I participated in GSoC 2024 on a project with INCF, where I developed QuantSI, a standalone Python package designed for scientific applications. QuantSI focuses on fundamental units and the International System.

I was first introduced to machine learning last year, when I started learning about it and working on small projects. Last semester, I took a course covering supervised and unsupervised learning, as well as neural networks and their mathematical models. One of the projects I am most proud of is my work on predicting breast cancer in women using SNPs, which helped me deepen my understanding of data management and the human genome.

Through my computer architecture course, I also studied the IEEE 754 standard, and one of my assignments involved creating a simple emulator for it.

I am very interested in the “Precision Recovery in Lossy-Compressed Floating Point Data for High Energy Physics” project for GSoC 2025. Could you please provide guidance on how I should prepare for the selection phase? Additionally, what resources should I read and study to be well-prepared for this stage of the project?

Looking forward to your advice.