Work in artificial intelligence spans more than a decade, beginning during early university studies and evolving into long-term research and applied engineering practice. From early interest in neural networks to advanced deep learning systems, this work reflects sustained engagement with the field rather than short-term specialization.

Experience covers applied machine learning and deep learning across computer vision and data-driven systems, with particular emphasis on problems that require both methodological rigor and practical system design. This includes model development, data preparation, experimentation, and deployment considerations in real-world environments.

Today, work in artificial intelligence is shaped by a combination of academic research and industry application, with a focus on building robust, interpretable, and scalable AI systems that operate reliably within larger technical and organizational contexts.