Kittikhun Thongpull

Papers

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About

Dr. Kittikhun Thongpull is a researcher at the forefront of intelligent systems, with key contributions spanning robotics, machine learning, and engineering education. His work is distinguished by the innovative application of machine learning techniques to solve complex electromechanical problems. Notably, his most-cited paper, "PMSM Torque Estimation Based on Machine Learning Techniques" (2020, 19 citations), addresses a critical challenge in Permanent Magnet Synchronous Motors (PMSM) used in robotic arms for medical and service applications. By enabling torque estimation without physical sensors, this work enhances operational safety and awareness—a vital requirement for human-interactive robots. Dr. Thongpull also demonstrates a strong commitment to shaping the next generation of engineers. He is a key figure behind the APRIS Robot Challenge (2024), a pioneering Collaborative Online Interdisciplinary and International Learning (COIIL) initiative. This project integrates students from software, electrical, and mechanical engineering to collaboratively control quadcopters, fostering the cross-disciplinary and global skills essential for modern IoT and robotics systems. Through his research and educational leadership, Dr. Thongpull is driving both technical innovation and the future of engineering pedagogy.