Kuat Zharykbayev

Built an end-to-end Russian-language NLP pipeline over 125,894 Telegram messages, fine-tuning RuBERT into a 3-class behavioral-text classifier with 0.84 macro-F1. Developed a multi-stage computer-vision OCR pipeline to digitize handwritten geomagnetic K-index archives and co-architected a real-time multi-camera animal behavior monitoring system.

Co-authored research on human-perception-based dominant color extraction, currently under review at a Q1 Elsevier journal. Contributed to research on retrospective seismicity analysis of the Zailiysky Alatau region, integrating solar-geomagnetic and geochemical precursor data.

Built a Python pipeline ingesting 90+ years of geomagnetic indices and the global USGS earthquake catalog onto a unified time grid, applying a binary event-association framework with permutation testing to evaluate solar–seismic correlations.

Pursuing a Master of Science in Data Science with a focus on Machine Learning, expected to continue through the current academic period.

Completed a Bachelor's degree in Computer Science with a specialization in Machine Learning and Robotics.

Participated in an international exchange program focused on Artificial Intelligence and Machine Learning.

Completed high school with a focus on Physics and Mathematics.