Ms. Xiaohua Li | Machine Learning | Excellence in Research Award

Published on by Electrical Engineering

Ms. Xiaohua Li | Machine Learning | Excellence in Research Award

Associate Professor | Shanghai Electric Power University | China

Dr. Li Xiaohua, a distinguished Professor at Sichuan University and leading expert in materials science and structural engineering, is renowned for advancing high-performance composite materials and sustainable structural systems. She holds advanced degrees in materials engineering with specialization in composite behavior and structural performance, complemented by extensive experience in academic leadership, project supervision, and collaborative research initiatives. Her professional portfolio includes directing major institutional projects, mentoring interdisciplinary teams, and contributing to engineering innovations that strengthen the reliability and resilience of modern structures. Dr. Li’s research focuses on composite structures, fire-resistant materials, mechanical behavior, and performance optimization, supported by 297 citations, 34 scholarly documents, and an h-index of 11, reflecting her growing global impact. She has authored influential publications, contributed to high-level research panels, and advanced knowledge dissemination through editorial responsibilities and membership in professional engineering societies. Recognized for excellence in research, innovation, and service, she also holds relevant professional certifications that underscore her commitment to scientific rigor and continued advancement in the engineering sciences.

Profile: Scopus

Featured Publications

Li Xiaohua*, Probabilistic forecasting of coal consumption for power plants under deep peak shaving conditions using Informer with DDPM-based uncertainty modeling. Int. J. Electr. Power Energy Syst., 2025.

Li Xiaohua*, Electromagnetic vibration characteristics of permanent magnet synchronous motors with segmented grain-oriented electrical steel teeth–yoke.

Li Xiaohua, Research on core loss prediction of low-frequency transformer based on Grey Wolf optimisation algorithm optimised Back Propagation neural network. IET Electr. Power Appl., 2025.

 










































































 




	


	

	






	
	

		


Mr. Xiangqi Dong | Nanoelectronics & Nanomaterials | Best Researcher Award
			

				Published on  by Electrical Engineering			

		
	


	

		



	
Mr. Xiangqi Dong | Nanoelectronics & Nanomaterials | Best Researcher Award


PhD Candidate | Fudan University | China






























Xiangqi Dong is a researcher in microelectronics at the School of Microelectronics and the National Key Laboratory of Integrated Chips and Systems at Fudan University, specializing in two-dimensional semiconductors, integrated circuit fabrication, and device–circuit co-optimization. He is pursuing a direct doctoral degree and holds an undergraduate background in Microelectronics Science and Engineering from Northwestern Polytechnical University, with focused academic training in microelectronics and solid-state electronics. His professional experience includes optimizing wafer-scale 2D transistor processes, supervising laboratory tape-out workflows, establishing quality-control procedures, integrating advanced fabrication tools, and leading a research team working on analog circuits and DTCO-driven circuit innovation. His research contributions encompass high-performance 2D gate-stack engineering, sensing-memory-computing fusion devices, neuromorphic electronics, RF systems, and next-generation computing architectures, resulting in significant publications in leading journals, invited conference talks, and contributions to landmark achievements such as 2D microprocessors, high-linearity flash ADCs, and wafer-scale integrated RF transmitters. He has co-filed patents on transistor structures and semiconductor process optimization, and actively participates in academic outreach to promote integrated circuit education. His recognitions include multiple merit-based scholarships and academic excellence awards, reflecting strong research capability and leadership. Citations 92 by 88 documents, 17 documents, h-index 5.


Profile: Scopus


Featured Publications


Xiangqi Dong, Radiation resistant atomic layer scale radio frequency system for spaceborne communication. Nature, Under review.


Xiangqi Dong, A RISC-V 32-bit microprocessor based on two-dimensional semiconductors. Nature, Published.


Xiangqi Dong, High-linearity flash ADC achieved through design-technology co-optimization based on two-dimensional semiconductors. Science Bulletin, Online.


Xiangqi Dong, A bio-inspired neuron with intrinsic plasticity based on monolayer molybdenum disulfide. Nature Electronics, Published.


















































	


	

	






	
	

		


Ms. Keenjhar Ayoob | Reliability Engineering | Best Researcher Award
			

				Published on  by Electrical Engineering			

		
	


	

		



	
Ms. Keenjhar Ayoob | Reliability Engineering | Best Researcher Award


PhD Scholar | National university of sciences and technology | Pakistan


Dr. Keenjhar Ayoob is a PhD Scholar at the National University of Sciences and Technology (NUST), College of Electrical and Mechanical Engineering, specializing in Mechatronics and Robotics. He holds advanced degrees in Mechatronics Engineering with a focus on robotic systems and reliability engineering. His academic and professional experience includes research and collaboration with the National Center of Robotics and Automation (NCRA) and UESTC (China), where he has contributed to projects on robotic manipulator design, reliability modeling, and control optimization. Dr. Ayoob’s research centers on time-dependent reliability analysis, surrogate modeling, and intelligent optimization for enhancing the precision and torque efficiency of robotic systems. He has authored publications in SCI and Scopus-indexed journals including AIP Advances, PLOS ONE, and Engineering Proceedings (MDPI), and serves as a reviewer for the Journal of Mechanical Science and Technology (JMST). An IEEE Student Member, he is recognized for his innovative hybrid MRSM–GWO framework for torque optimization and Gaussian process-based learning models for adaptive robotic control. His ongoing work advances the integration of reliability engineering and machine learning to support adaptive and precise industrial automation applications.


Profile: ORCID


Featured Publications


Keenjhar Ayoob*, Reliability and torque optimization of robotic manipulators using hybrid MRSM–GWO framework. AIP Advances, Accepted.


Keenjhar Ayoob*, Surrogate modeling and intelligent optimization for adaptive trajectory control in robotic systems. PLOS ONE, Published.


Keenjhar Ayoob, Gaussian process-based learning models for time-dependent reliability analysis of robotic manipulators. Engineering Proceedings (MDPI), Published.




	


	

	






	
	

		


Ms. Jingmin Ge | Sensor Networks & Wireless Sensor Technologies | Innovative Research Award
			

				Published on  by Electrical Engineering			

		
	


	

		



	
Ms. Jingmin Ge | Sensor Networks & Wireless Sensor Technologies | Innovative Research Award


Sensors | Zhengzhou university | China


Dr. Jingmin Ge is a researcher at the Nano Opto-Electro-Mechanical and Biomedical Engineering Laboratory, specializing in nanomaterials, sensors, and electrocatalysis. She earned her Ph.D. in Chemistry from Beijing University of Chemical Technology, M.Sc. in Organic Chemistry from Central China Normal University, and B.Sc. in Applied Chemistry from Henan Agricultural University. Dr. Ge has led and contributed to several national and collaborative projects focused on high-performance electrocatalysts, toxic gas and soil sensors, and sustainable environmental monitoring systems. Her research integrates material synthesis, nanostructure design, and DFT simulations to uncover mechanisms in hydrogen evolution, CO₂ reduction, and pollutant detection. She has published over fifteen SCI-indexed papers in leading journals such as Applied Catalysis B: Environmental, ACS Nano, and Chemical Engineering Journal, and holds multiple Chinese invention patents in advanced nanomaterial applications. Recognized for her scientific excellence, Dr. Ge has served as a key contributor in state-level laboratories, advancing green energy and smart sensing technologies. Her professional portfolio demonstrates a sustained commitment to interdisciplinary innovation, bridging theoretical computation and experimental materials science, and positioning her as a distinguished researcher in chemical engineering and nanotechnology. According to Scopus, her research record includes 540 citations across 26 publications with an h-index of 12.


Profile: Scopus


Featured Publications


Ge, Jingmin*, Dual-metallic Single Ru and Ni Atoms Decoration of MoS₂ for High-efficiency Hydrogen Production. Appl. Catal. B-Environ., 2021, 298, 120557.


Ge, Jingmin*, Oxygen Atoms Substituting Sulfur Atoms of MoS₂ to Activate the Basal Plane and Induce Phase Transition for Boosting Hydrogen Evolution. Mater. Today Energy, 2021, 22, 100854.


Ge, Jingmin, Heterostructure Ni₃S₄–MoS₂ with Interfacial Electron Redistribution Used for Enhancing Hydrogen Evolution. RSC Adv., 2021, 11, 19630–19638.


Ge, Jingmin*, Activated MoS₂ by Constructing Single Atomic Cation Vacancies for Accelerated Hydrogen Evolution Reaction. ACS Appl. Mater. Interfaces, 2022, 14, 26846–26857.


Ge, Jingmin, NiFeCu Phosphides with Surface Reconstruction via Topotactic Transformation of Layered Double Hydroxides for Overall Water Splitting. Inorg. Chem. Front., 2023, 10, 3515–3524.