Between inquiry
and implementation.
Working on Kazakh-language models has brought questions of evaluation and language into the same frame. A model’s behavior needs to be examined in the setting where it will be used, including the language and the people relying on its answers.
That interest carries into my work on source-grounded historical knowledge, trust-to-authorization policies, and safety-sensitive evaluation. The applications differ; the concern with evidence and reliability connects them.
I also care about the path from an idea to a working system. Orbitum began as an EdTech hackathon concept with Yerkezhan. After the competition, we continued, formed a new team, and developed the idea further. I lead the AI work while teammates contribute frontend, backend, content, and project publication.
Beyond the lab, I have represented Bangladesh at International Mother Language Day at the United Nations Centre in Almaty, taught visiting students, and explored climate-aware AI through the Climate Change AI Summer School. Language, education, and climate resilience are recurring interests across these experiences.
My next academic step is graduate study, with a continuing focus on trustworthy AI, NLP, and rigorous evaluation methods.