Dr. Azamat Yeshmukhametov, Nazarbayev University, Kazakhstan.
Azamat Yeshmukhametov 
holds a Ph.D. and Doctorate in Engineering and specializes in mechatronics, robotics, and AI-driven sensors. Skilled in 3D mechanical design, ROS, Arduino, and PCB circuitry, he integrates engineering and technology to innovate smart systems. With international experience across academic and industrial sectors, including Satbayev University and Nazarbayev University, his work emphasizes the development of robotics for diverse applications. Azamat is proficient in Kazakh, Russian, English, and Japanese, showcasing his global perspective in both language and technical expertise. 
Publication profile
Education and Experience
- Bachelor | Kazakh National Technical University (2008–2012)
Almaty, Kazakhstan
- Pre-master Foundation | Newcastle University (2013–2014) Newcastle, UK
- Master | Tokai University (2014–2016) Hiratsuka, Japan
- Ph.D. | Tokai University (2017–2020) Hiratsuka, Japan
- Dual Ph.D. Program | Satbayev University (2017–2020) Almaty, Kazakhstan
- Research Assistant | Kazakh National Technical University (2012) Almaty, Kazakhstan
- Technician | Amazon.jp (2016) Odawara, Japan
- Lecturer | Satbayev University (2016–2017) Almaty, Kazakhstan
- Teacher Assistant | Tokai University (2019–2020) Hiratsuka, Japan
- Associate Professor | Satbayev University (2020–2021) Almaty, Kazakhstan
Suitability For The Award
Dr. Azamat Yeshmukhametov, a Ph.D. and Doctor of Engineering, demonstrates a high level of expertise in robotics, sensor integration, and AI-driven systems, making him an outstanding candidate for a Young Scientist Award. His interdisciplinary research experience, academic background, and contributions to social and scientific outreach exemplify the qualities of a promising scientist. His projects focus on impactful applications in robotics and sensor technology, with specific emphasis on tensegrity robots, in-pipe inspection robots with AI capabilities, and triboelectric sensor integration, all of which address critical technological and engineering challenges.
Professional Development
Azamat has consistently advanced in his field through various positions and professional initiatives worldwide. His tenure at institutions like Satbayev University and Nazarbayev University, along with hands-on roles in companies such as Amazon Japan, has equipped him with a unique blend of academic and industry experience. Azamat is deeply involved in projects focusing on robotics, AI, and self-powered sensor systems. His international internships, including those at Cambridge University and Nissan Motors, highlight his dedication to mastering cutting-edge technology. Through conferences across Asia, Europe, and the USA, he stays connected to advancements in robotics and engineering. 
Research Focus
Azamat Yeshmukhametov’s research encompasses mechatronics, robotics, AI, and triboelectric MEMS sensors. His projects often involve designing AI-integrated inspection robots and self-powered MEMS sensors. Passionate about innovation, Azamat has served as Principal Investigator (PI) and Co-PI on research grants focused on multilayer tensegrity robots and in-pipe robots for complex inspections. He also explores applications of triboelectric phenomena in MEMS, aiming to create next-generation, self-sustaining robotic components. His initiatives bridge cutting-edge technology and practical applications, positioning him as a leader in AI and robotics research. 
Awards and Honors
- PI | Multilayer Tensegrity Robot Project (Grant No. AP19574394, 2023-2025)
- PI | AI-Based In-Pipe Robot Inspection (Grant No. AP19679380, 2023-2025)
- Co-PI | Smart Robotic Grippers with Triboelectric Sensors (FDCRPG, 2023-2025)
- Co-PI | Integration of Triboelectric MEMS Sensors (MHES, 2024-2026)
Publications
- Smart Pipe Inspection Robot with In-Chassis Motor Actuation Design and Integrated AI-Powered Defect Detection System | IEEE Access, 2024 |
Cited by: 0
- Design of a Fully Pulley-Guided Wire-Driven Prismatic Tensegrity Robot: Friction Impact to Robot Payload Capacity | IEEE Robotics and Automation Letters, 2023 | Cited by: 1
- A Simplified Kinematics and Kinetics Formulation for Prismatic Tensegrity Robots: Simulation and Experiments | Robotics, 2023 | Cited by: 3
- Development of Mobile Robot with Autonomous Mobile Robot Weeding and Weed Recognition by Using Computer Vision | ICCAS, 2023 | Cited by: 2
- Design and Development of an In-Pipe Mobile Robot for Pipeline Inspection with AI Defect Detection System | ICCAS, 2023 | Cited by: 1
- Stiffness and Vibration Resistance Analysis of Isotropic Stewart Platform (ISP) and Common Stewart Platform (CSP) | ICCAS, 2023 | Cited by: 0
- Six-bar Pulley-Guided Node Based Prismatic Tensegrity Robot Form-finding Analysis and Experiment | AIM, 2023 | Cited by: 0
- Development of Continuum Robot Arm and Gripper for Harvesting Cherry Tomatoes | Applied Sciences (Switzerland), 2022 | Cited by: 20