I'm Cristian, a junior machine learning engineer currently based in the Netherlands.
I build machine learning/deep-learning models while striving to maintain a balanced trade-off between performance and viability ("boring" aspects such as inference speed, decision-making transparency, and memory footprint all do count as vital to me).
So, if I sense a problematic gap, I like to do a bit of assessment beforehand of building something. Understanding the why, the constraints, and the needs (which hopefully are not entirely based on HIGHHHH ACURRACY IS ALL WE NEED) is always what constitutes the first step to me.
As for my tech stack (or "arsenal") it is really accommodating tools I really like working with such as, PyTorch, Keras, scikit-learn, sktime, cuda-python, pystata, pyspark, (the data science "basics" like numpy, matplotlib...), docker and some APIs (Claude, Gemini, GreenPT and OpenAI)
I am currently working on a dashboarding system that could help me keep track of my spending and optimize both my investment portfolio and purchasing behavior.
Now, my favorite project is this one.
What else?
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I am into writing poetry and reading beautiful
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I am into MOVIES (e.g., hate Disney for twisting Star Wars; love Pixar for their last Toy Story movie release).
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I am into investing (stocks and crypto), of course...
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I love well-established AI (developers also think of some other key points not fully locked in accuracy), not HYPED AI.
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I do play basketball and run and like to chop wood with my father's axe.
LASTLY:
AI could do tremendous good. It's just a matter of enabling it to domains, industries, and niches whose development is imperative/crucial to us. (e.g., cancer detection or investment loss minimisation dah)