Talgat Sundetov

Institute of Information and Computational Technologies

Papers

Total Citations

H-Index

About

Talgat Sundetov is a researcher advancing the intersection of machine learning, robotics, and human-computer interaction, with a particular focus on natural language processing and gesture recognition. His work centers on developing integrated information systems that enable more intuitive communication between humans and machines, especially through verbal robots. Sundetov’s most notable contributions include the design of an information system incorporating machine learning modules for verbal robots, and the development of a hand gesture recognition system tailored to the Kazakh language. This latter work, which analyzes major sign languages and proposes a system using touch sensors to interpret Kazakh sign language, represents a significant step toward culturally inclusive assistive technology. While his citation counts (3 each for his top papers) reflect an emerging career, the applied nature of his research—bridging machine learning, robotics, and linguistic diversity—positions him as a contributor to more accessible and regionally relevant AI systems. His achievements demonstrate a commitment to making human-robot interaction more natural and inclusive, particularly for underrepresented languages.