Design and development of electronic systems for sensor integration is a core area of my interest. From the creation of analog and digital circuitry to signal conditioning, measurement techniques, and real-time data acquisition — I am especially drawn to building systems that bridge physical processes with interpretable data. Whether developing custom electronics for precise measurements or working with embedded systems for sensor networks, I find this interplay between hardware and data to be both technically challenging and deeply rewarding.

Sustainable development and environment protection. Eager to apply advanced predictive analytics to model and enrich understanding of future events. My goal is to leverage data-driven insights to inform strategies that promote sustainability and resilience in various systems.

From simple optimization techniques to dynamic system modelling through physics-informed neural networks. The future of data science lies in, I believe, understanding the underlying principles. Neural network is not a black box. Just laws are a bit... perplexing. Everybody knows that the answer is 42, but hardly any knows the borders of the answers' subspace.

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