Prof. Fazhi Song | Control Systems | Research Excellence Award

Professor | Harbin Institute of Technology | China

Dr. Fazhi Song, a Professor at the Harbin Institute of Technology specializing in control science, motion control, and precision engineering, is an accomplished researcher whose work advances high-end manufacturing and ultra-precision motion systems. He holds advanced degrees culminating in a Ph.D. in Control Science and Engineering, with academic training focused on system identification, learning control, and precision motion technologies. Throughout his professional career, he has led major research initiatives in motion generation, performance control, and accuracy retentivity for advanced manufacturing equipment, contributing to national and provincial projects and collaborating with leading industrial partners on precision motion systems. His research centers on high-precision mechanical servo systems, uncertainty-robust learning control, multi-DOF motion coordination, and advanced control strategies for lithography-level equipment, supported by a strong record of publications, patents, and technical innovations. He has authored numerous peer-reviewed articles, contributed to an academic monograph, and advanced methodologies widely cited in the fields of precision engineering and automation, reflected through 45 citations, 9 documents, and an h-index of the candidate. His achievements include significant awards from national academic societies recognizing technological innovation, along with contributions as a guest editor for respected journals, session chair for international conferences, and active membership in IEEE and major professional automation and instrumentation societies. Dr. Song’s leadership in research, editorial service, and professional engagement underscores his commitment to advancing ultra-precision control technologies and cultivating scientific excellence in the global engineering community.

Profiles: Scopus | ORCID

Featured Publications

Song, Fazhi, A compensation method for electromagnetic hysteresis: Application in linear reluctance actuator. J. Magn. Magn. Mater., 2025.*

Song, Fazhi, Crest factor minimization of multisine signals based on the Chebyshev norm approximation method: With application to wafer stage FRF identification. Results Eng., 2025.*

Song, Fazhi, Identification for Precision Mechatronics: An Auxiliary Model-Based Hierarchical Refined Instrumental Variable Algorithm. Int. J. Robust Nonlinear Control., 2025.*

Song, Fazhi, Beyond Performance of Learning Control Subject to Uncertainties and Noise: A Frequency-Domain Approach Applied to Wafer Stages. IEEE/CAA J. Autom. Sinica., 2025, 5 citations.*

Mr. Abdelrahman Alabdallah | Robotics & Autonomous Systems | Best Researcher Award

Student | Politecnico di Torino | Italy

Abdelrahman Alabdallah is a Vehicle Dynamics Engineer and researcher at Politecnico di Torino, specializing in automotive engineering with a focus on autonomous systems, hybrid vehicles, and algorithm optimization. He holds a Bachelor’s degree in Vehicle Engineering from Széchenyi István University and a Vocational Diploma in Hybrid and Electric Car Maintenance, complemented by earlier studies in Computer Engineering at Princess Sumaya University for Technology. Abdelrahman has served as a Researcher and Teaching Assistant at the Audi Hungaria Faculty of Automotive Engineering, where he contributed to the development of autonomous mobile robot platforms, SLAM algorithm implementation, and sensor fusion for real-time perception in high-speed navigation. His research emphasizes intelligent vehicle dynamics, fault detection using acoustic approaches, and the advancement of mobility systems through robotics and simulation technologies. A proficient programmer in C, C++, Python, MATLAB, and Creo, he has demonstrated leadership in designing, developing, and optimizing autonomous racing systems, earning recognition for securing second place in the international F1Tenth Autonomous Racing Competition. Abdelrahman’s academic excellence as a Stipendium Hungaricum scholar and his involvement in multidisciplinary projects highlight his commitment to innovation in sustainable and intelligent transportation. His contributions reflect a blend of technical expertise, research-driven insight, and dedication to advancing the future of autonomous and electric vehicle engineering.

Profile: Google Scholar

Featured Publications

Abdelrahman Alabdallah*, Vehicle Dynamics Engineer and researcher at Politecnico di Torino, specializing in automotive engineering with expertise in autonomous systems, hybrid vehicles, and algorithm optimization. Politecnico di Torino, Accepted.

Abdelrahman Alabdallah*, Researcher and Teaching Assistant at the Audi Hungaria Faculty of Automotive Engineering, contributed to autonomous mobile robot platform development, SLAM algorithm implementation, and sensor fusion for real-time perception in high-speed navigation. Széchenyi István Univ., 2024, 5(2), 101456.

Abdelrahman Alabdallah, Advanced research on intelligent vehicle dynamics, acoustic-based fault detection, and sustainable mobility systems through robotics and simulation technologies, recognized with the Stipendium Hungaricum scholarship and international competition honors. Int. J. Auto. Eng., 2024, 6(1), 112034.