Prof. Fazhi Song | Control Systems | Research Excellence Award

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.*

 

Prof. Fazhi Song | Control Systems & Optimization | Research Excellence Award

Prof. Fazhi Song | Control Systems & Optimization | Research Excellence Award

Professor | Harbin Institute of Technology | China

Dr. Fazhi Song, Professor in the School of Instrumentation Science and Engineering at Harbin Institute of Technology, is a leading specialist in control science and precision motion systems whose work advances high-end manufacturing and inspection technologies. With a Ph.D. in Control Science and Engineering and research expertise spanning motion generation, performance control, learning control, and system accuracy retentivity, he has built a distinguished academic and professional record through roles as researcher, lecturer, associate professor, and project leader on numerous advanced engineering projects. He has authored more than forty peer-reviewed publications, contributed a research monograph, and secured an extensive portfolio of patents and software copyrights, reflecting strong innovation and impact in precision motion control. His scholarly influence is further demonstrated by 432 citations across 367 documents, 45 indexed publications, and an h-index of 9. Dr. Song has been recognized with major honors, including high-level national and provincial awards for technological invention, innovation, and academic contribution, and he maintains active professional service as guest editor, editorial board member, conference session chair, peer reviewer for leading journals, and expert evaluator for national research programs. His contributions exhibit a blend of scientific rigor, technological advancement, and leadership, positioning him as an exemplary candidate for award recognition.

Profiles: Scopus | ORCID

Featured Publications

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

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

Fazhi Song, Identification for precision mechatronics: An auxiliary model-based hierarchical refined instrumental variable algorithm. Int. J. Robust Nonlinear Control, 2025.*

Fazhi Song, 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.*

Assoc. Prof. Dr. Guanlong Jia | Electric Engineering | Research Excellence Award

Assoc. Prof. Dr. Guanlong Jia | Electric Engineering | Research Excellence Award

Associate Professor | Hebei University of Technology | China

Guanlong Jia, Lecturer at Hebei University of Technology and a Member of IEEE, is a researcher specializing in high-power electronics with expertise in circuit breakers, multilevel converters, control algorithms, and pulse-width modulation techniques. He holds a Ph.D. in electrical engineering from Zhejiang University, where he focused on advanced power electronic systems and their reliability. In his professional capacity, he contributes to teaching and research in power conversion technologies, participating in institutional and collaborative projects that enhance innovation in electrical engineering. His research centers on the design, analysis, and optimization of high-power electronic devices, and his contributions are reflected in his scholarly publications and technical advancements in power electronics. He is recognized for his academic engagement and his role in supporting the wider research community through professional membership and ongoing contributions to the field. At the end of his academic profile: 295 citations, 42 documents, and an h-index of 7.

Profile: Scopus

Featured Publications

Jia, Guanlong*, Transient stability enhancement method for virtual synchronous generators using power-angle deviation with a modified reactive-power control loop. Electronics (Switzerland), Accepted.

Jia, Guanlong*, Multi-objective optimization design of fast vacuum switch operating mechanisms for hydrogen-storage power systems. AIP Advances, Accepted.

Jia, Guanlong, Dynamics simulation and fault-characteristic analysis of permanent-magnet repulsion mechanisms for vacuum circuit breakers integrating advanced high-power switching technologies. AIP Advances, Accepted.

Ms. Soujanya Reddy Annapareddy | BESS Power Flow and Energy | Energy Efficiency Excellence Award

Ms. Soujanya Reddy Annapareddy | BESS Power Flow and Energy | Energy Efficiency Excellence Award

Senior Firmware Automation Engineer | TAE Power Solutions | United States

Ms. Soujanya Reddy Annapareddy is a Senior Firmware Automation Engineer at TAE Power Solutions, recognized for her expertise in embedded systems, firmware validation, and automation engineering. She holds advanced degrees in Computer Technology and Electronics and Communication Engineering, forming a strong interdisciplinary foundation that bridges software and hardware innovation. With extensive experience in developing Python-based automation frameworks, integration testing tools, and validation systems for complex embedded platforms, she has led and contributed to numerous industry and research projects aimed at enhancing automation efficiency and system reliability. Her research primarily focuses on firmware automation, embedded systems validation, IoT test architectures, software quality engineering, and cloud-integrated automation solutions. She has authored and co-authored more than twenty papers in international peer-reviewed journals and conferences, presenting impactful findings on energy-efficient embedded systems and adaptive control algorithms for battery energy storage systems. Beyond research, Ms. Annapareddy has served as a peer reviewer and judge for multiple reputed international journals, evaluating technical manuscripts across software automation and data-driven technologies. Her professional affiliations include membership in IEEE and active collaborations with multidisciplinary teams in academia and industry. She has been honored with recognitions for excellence in energy efficiency and innovation, reflecting her commitment to advancing intelligent, sustainable embedded technologies. Through her technical leadership, scholarly contributions, and dedication to continuous innovation, Ms. Soujanya Reddy Annapareddy exemplifies the qualities of a forward-thinking engineer and researcher in the global field of firmware automation and embedded systems engineering.

Profile: Google Scholar 

Featured Publications

Soujanya Reddy Annapareddy*, Managing power flows and energy efficiency in embedded systems for battery energy storage systems (BESS). Int. J. Adv. Innov. Dev. Res., Accepted.

Soujanya Reddy Annapareddy*, Python-based automation frameworks for firmware validation and integration testing in embedded platforms. Int. J. Innov. Res. Comput. Technol., 2024, 8(3), 245–252.

Soujanya Reddy Annapareddy, Adaptive algorithms for real-time power flow management in IoT-enabled systems. Int. J. Autom. Control Technol., 2024, 7(2), 118–129.

Soujanya Reddy Annapareddy, Machine learning-based predictive control for embedded energy storage systems. Int. J. Firmware Modern. Res., 2024, 6(4), 342–350.

Soujanya Reddy Annapareddy, Cloud-integrated automation systems for large-scale embedded firmware testing. Int. J. Latest Res. Publ., 2024, 5(1), 97–105.

Ms. Siqin Liao | Control Systems & Optimization | Best Researcher Award

Ms. Siqin Liao | Control Systems & Optimization | Best Researcher Award

Student | The School of Computer Science, Guangdong University of Technology | China

Siqin Liao is a Ph.D. candidate at the School of Computer Science, Guangdong University of Technology, specializing in control theory and intelligent systems. He holds a Master of Engineering in Control Engineering from Guangdong University of Technology and a Bachelor of Engineering in Electrical Engineering and Automation from Xinyu University, and has completed a visiting research program at the University of Adelaide, Australia. His research focuses on asynchronous control of Markov jump systems, cooperative control of multi-agent systems, and network security control. Liao has published seven SCI-indexed papers in leading journals such as IEEE Transactions on Cybernetics and Systems & Control Letters, contributing novel control methodologies for stochastic and networked systems under uncertainty and cyberattacks. He has participated in provincial-level projects funded by the Guangdong Basic and Applied Basic Research Foundation and collaborates internationally on control design research. His scholarly impact includes over 100 citations, with recognition for his first-author and corresponding-author publications. As a student member of IEEE, he upholds academic excellence and innovation in control system theory. His achievements have earned him awards such as the First Prize in the Siemens Cup China Intelligent Manufacturing Challenge and the Third Prize in the China Robowork Competition, highlighting both his technical expertise and leadership in engineering research. His research record includes 80 citations across 7 publications with an h-index of 2, reflecting his growing academic influence.

Profile: Scopus

Featured Publications

Siqin Liao*, Zheng-Guang Wu, Yuanqing Wu. Constrained quadratic control for Markov jump systems with multiplicative noise. Syst. Control Lett., 2025, 203:06–27.

Siqin Liao*, Yuanqing Wu, Zheng-Guang Wu, Peng Shi. Design on dynamic event and self-triggered control for systems with Markov jumps and denial-of-service attacks. J. Franklin Inst., 2025, doi:10.1016/j.jfranklin.2025.108006.

Siqin Liao, Zheng-Guang Wu, Yuanqing Wu*. Control for Markov jump systems with partially unknown transition probabilities under denial-of-service attacks. Int. J. Robust Nonlinear Control., 2025, doi:10.1002/rnc.70142.